Battery identification systems and methods

Abstract

A method for identifying and sorting batteries comprising receiving a stream of mixed batteries, spatially separating the stream of mixed batteries into a plurality of batteries, directing a non-destructive beam of neutrons at a battery of a plurality of batteries, sensing an electromagnetic signature emitted in response to the non-destructive beam of neutrons directed at the battery, analyzing the electromagnetic signature to determine a composition of the battery, and sorting the battery to a location based on the composition.

Description

BATTERY IDENTIFICATION SYSTEMS AND METHODSTimothy Schott, Saint Paul, USAJoseph Grogan, Eagan, USAJoseph Trouba, Saint Paul, USADaniel Graf, Tampa, USACROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 63 / 616,049, filed December 29, 2023, entitled “Lithium Battery Identification,” which is incorporated by reference herein in its entirety for all purposes.FIELD

[0002] The disclosed process, methods, and systems are directed to battery identification, and more specifically to sortation of mixed batteries, which may be predominantly lithium batteries, into groups based on the detected or identified bulk chemistry of each battery. In one example, the disclosed sortation process may be manual, automated, or partially automated and the means for detecting the respective battery chemistries may be nondestructive.BACKGROUND

[0003] When batteries are recycled the purity or quality of the post-recycling product, the valuable product stream, affects the value of the saleable product. In the case of lithium batteries, when recycled an intermediate product often referred to as black mass may be produced. Black mass may include a mixture of metals present in the respective lithium batteries. For example, lithium batteries may be comprised of lithium titanate (LTO batteries), lithium iron phosphate (LFP batteries), lithium manganese oxide (LMO batteries), lithium cobalt oxide (LCO batteries), lithium nickel manganese cobalt oxide (NMC batteries), lithium nickel cobalt aluminum oxide (NCA batteries), lithium metal, etc. The metals may be, after further processing, purified and reused and thus represent avaluable product stream. However, battery recycling facilities often receive a mixed feed of batteries, including lithium batteries that have different compositions, chemistries, or elemental make-ups, nickel cadmium (NiCd) batteries, nickel metal hydride (NiMH) batteries and / or lead acid batteries. Black mass may vary in value, depending on the value of, type, and concentration of metals present in the black mass. If non-lithium batteries were to be processed with the lithium battery stream the value of the black mass would be negatively impacted. Likewise, if lithium batteries are processed through a lead battery processing facility, safety issues could arise during the comminution step.

[0004] Currently, batteries are not sorted based on the bulk chemistry of the battery. Manual identification of battery chemistry is costly, slow, and very labor intensive, limiting overall processing capacity of a recycling facility and greatly increasing recycling costs. Thus, what is needed is a battery identification process that is capable of rapidly and economically identifying batteries chemistries from a mixed stream of batteries based upon the elemental make-up of the respective batteries which could then be sorted, either manually or coupled with an automated or semi- automated sorting system or device.SUMMARY

[0005] Disclosed herein are processes and systems useful for sorting batteries and battery scrap, such as predominately lithium batteries, lithium battery scrap, and non-lithium batteries. As used herein, “non-lithium batteries” include batteries where lithium is not present, or may be present in trace amounts but is not a predominant component of the energy storage and conversion reactions of the batteries. Examples of non-lithium batteries include, but arc not limited to: NiCd, NiMH, lead acid, silver oxide, zinc air, sodium-ion, sodium sulfur, magnesium, mercury, cadmium, and vanadium redox batteries. Non-lithium batteries may be either primary (non-rechargeable) or secondary (rechargeable) batteries. An embodiment of the present disclosure may include a method for identifying and sorting batteries based on the identification. The method may include receiving a stream of mixed batteries, some of which are lithium batteries. The method may include spatially separating each battery of the stream of mixed batteries into a plurality of individual batteries. The method may include directing a non-destructive beam of neutrons at an individual battery of the plurality of individual batteries. The method may include sensing, from the individualbattery, an electromagnetic signature emitted in response to the non-destructive beam of neutrons. The method may include analyzing the electromagnetic signature to determine the composition of the individual battery. The method may include directing the individual battery to a location based on the composition.

[0006] Embodiments of the present disclosure may also include a battery identification and sortation system. The battery identification and sortation system may include a separator that may spatially separate batteries of a stream of mixed batteries. The battery identification and sortation system may include a sensor that may detect an electromagnetic signature from an individual battery of the separated batteries. The electromagnetic signature may be emitted in response to a non-destructive beam of neutrons directed at the individual battery. The battery identification and sortation system may include a sorting device that may direct the individual battery to a predetermined location based on the electromagnetic signature.

[0007] Embodiments of the present disclosure may also include a sensor device, which may include a sensing / receiving / detecting device and an emitter / source that may produce neutrons. In these embodiments, the sensor may also include a device or structure for directing a non-destructive beam of neutrons at a battery. The sensor / detector / receiver may measure an electromagnetic spectrum or signature from the battery. In many cases, a signature may be comprised of various individual spectra of the various elements within the battery. The sensor device may include a computer system with a processor that may determine the composition of the battery based on the electromagnetic signature.

[0008] Embodiments of the present disclosure include a method for identifying and sorting batteries, the method including receiving a stream of mixed batteries, spatially separating the stream of mixed batteries into a plurality of individual batteries, directing a nondestructive beam of neutrons at an individual battery of the plurality of individual batteries, sensing an electromagnetic signature emitted in response to the non-destructive beam of neutrons directed at the individual battery, analyzing the electromagnetic signature to determine a composition of the individual battery, and sorting the individual battery to a location based on the composition.

[0009] Optionally, in some embodiments, the method is at least partially automated. Optionally, in some embodiments, the stream of mixed batteries is spatially separated a sufficient distance to prevent compromising the electromagnetic signature emitted in response to the non-destructive beam of neutrons directed at the battery. Optionally, in some embodiments, the stream of mixed batteries is spatially separated into a single file line. Optionally, in some embodiments, a battery type of the battery is determined by an absolute measurement of at least an element of the composition. Optionally, in some embodiments, a battery type is determined by a composition of an element of the battery relative to one or more of a composition of a plurality of other elements of the battery. Optionally, in some embodiments, a battery type is determined by a measurement of an element of the composition and a threshold value. Optionally, in some embodiments, the threshold value may be chosen to minimize or prevent false positives.

[0010] Optionally, in some embodiments, a battery may be determined as a lithium titanate battery if the composition includes at least 2% titanium. Optionally, in some embodiments, a battery may be determined as a lithium titanate battery if the composition includes at least 1% to at least 10% titanium.

[0011] Optionally, in some embodiments, a battery may be determined as a lithium manganese oxide battery if the composition includes at least 3.5% manganese and less than or equal to 3.5% cobalt. Optionally, in some embodiments, a battery may be determined as a lithium manganese oxide battery if the composition includes a composition of manganese at least 0.1% to at least 10% manganese, and a composition of cobalt less than or equal to 3.5%. Optionally, in some embodiments, a battery may be determined as a lithium manganese oxide battery if the composition includes more manganese than cobalt or nickel. Optionally, in some embodiments, a battery may be determined as a lithium manganese oxide battery if the composition includes at least 7.5% manganese and less than or equal to 2% cobalt.

[0012] Optionally, in some embodiments, a battery may be determined as a lithium iron phosphate battery if the composition includes at least 1% phosphorous. Optionally, in some embodiments, a battery may be determined as a lithium iron phosphate battery if the composition includes at least 0.5% to at least 5% phosphorous.

[0013] Optionally, in some embodiments, a battery may be determined as a lithium cobalt oxide battery if the composition includes at least 10% cobalt. Optionally, in some embodiments, a battery may be determined as a lithium cobalt oxide battery if the composition includes at least 5% to at least 20% cobalt. Optionally, in some embodiments, a battery may be determined as a lithium cobalt oxide battery if the composition includes a composition of cobalt greater than a composition of nickel multiplied by a factor, wherein the factor is greater than 1. Optionally, in some embodiments, a battery may be determined as a lithium cobalt oxide battery if the composition includes a composition of cobalt greater than a composition of nickel multiplied by a factor, wherein the factor is equal to or between 1.5 and 2.

[0014] Optionally, in some embodiments, a battery may be determined as a lithium nickel manganese cobalt oxide battery if the composition includes at least 0.3% manganese. Optionally, in some embodiments, a battery is determined as a lithium nickel manganese cobalt oxide battery if the composition includes at least 0.05% to at least 5% manganese. Optionally, in some embodiments, a battery may be determined as a lithium nickel manganese cobalt oxide battery if the composition includes a composition of manganese greater than or about equal to 0.3%, and a composition of cobalt, wherein the composition of manganese is at least half the composition of cobalt, and the composition of manganese is less than double the composition of cobalt.

[0015] Optionally, in some embodiments, a battery may be determined as a lithium nickel cobalt aluminum oxide battery if the composition includes at least 4% nickel. Optionally, in some embodiments, a battery may be determined as a lithium nickel cobalt aluminum oxide battery if the composition includes at least 1% to at least 10% nickel. Optionally, in some embodiments, a battery may be determined to be a lithium nickel cobalt aluminum oxide battery if the composition includes one or more of a composition of nickel greater than or equal to 4%, a composition of cobalt more than two times a composition of manganese, or a composition of cobalt greater than or equal to 1%. Optionally, in some embodiments, a battery may be determined to be a lithium nickel cobalt aluminum oxide battery if the composition includes one or more of a composition of nickel greater than or equal to 6%, a composition of cobalt more than four times a composition of manganese, or a composition of cobalt greater than or equal to 2%.

[0016] Optionally, in some embodiments, a battery may be determined as a lithium metal battery if the composition includes at least 4% vanadium. Optionally, in some embodiments, a battery may be determined as a lithium metal battery if the composition includes at least 1% to at least 10% vanadium.

[0017] Optionally, in some embodiments, a battery may be determined as a lead acid battery if the composition includes at least 0.5% lead.

[0018] Optionally, in some embodiments, a battery is determined as a NiCd battery if the composition includes at least 0.5% cadmium.

[0019] Optionally, in some embodiments, a battery may be determined as an “other” battery if the composition does not conform to a known composition of a battery type. In some embodiments, the methods disclosed may further comprise individually inspecting other batteries to identify a battery type.

[0020] Embodiments of the present disclosure may include a battery identification and sortation system that includes a separator configured to spatially separate batteries of a stream of mixed batteries, a sensor configured to detect an electromagnetic signature from a battery of the stream of mixed batteries, wherein the electromagnetic signature is emitted in response to a non-destructive beam of neutrons bombarding the battery, and a sorting device configured to direct the battery to a predetermined location based on the electromagnetic signature.

[0021] Optionally, in some embodiments, the system may further include a location for each of a battery type identified. Optionally, in some embodiments, the sorting device may include a deflector bar. Optionally, in some embodiments, the sensor may include a radiometric sensor. Optionally, in some embodiments, the sensor may include a promptgamma neutron activation analysis sensor, a pulsed fast thermal neutron activation sensor, or a similar device.

[0022] Optionally, in some embodiments, the system may include a computer system. Optionally, in some embodiments, the computer system may configure at least one of the separator, the sensor, or the sorting device.

[0023] Embodiments of the present disclosure may also include a sensor device that includes an emitter configured to emit or produce a plurality of non-destructive neutrons, adirector configured to direct the plurality of non-destructive neutrons at a battery, a receiver configured to measure an electromagnetic signature from the battery, and a processor configured to determine a composition of the battery based on the electromagnetic signature.BRIEF DESCRIPTION OF THE DRAWINGS

[0024] FIG. 1 is an annotated flow chart of one embodiment of the disclosed processes and systems.

[0025] FIG. 2 is a flow diagram of radiometric sensing.

[0026] FIG. 3 is a sample readout from a sensor system.

[0027] FIGS. 4-7 are annotated flow charts of embodiments of methods of sorting a battery into a sortation group of a plurality of sortation groups, suitable for use with the system of FIG. 1.

[0028] FIG. 8 is a table depicting detection limits for various elements.

[0029] FIG. 9 is a simplified block diagram of components of a computing system of the system of FIG. 1.

[0030] FIG. 10 shows an example of measured electromagnetic data of four different battery types in accordance with the processes and systems disclosed herein.

[0031] FIG. 11 shows an example of measured electromagnetic data of the same battery in two different orientations in accordance with the processes and systems disclosed herein.DETAILED DESCRIPTION

[0032] The disclosed devices, methods, processes, and systems are directed to identifying and sorting a stream of mixed batteries into groups of batteries based on the identified bulk chemistry, composition, or elemental make-up of each battery of the stream. The respective battery chemistries may be detected in a non-destructive manner and the detection means may also be automated or partially automated. In some embodiments, the disclosed streams may include predominantly lithium batteries, batteries of unknown or non-conforming type, and / or non-lithium batteries.

[0033] The disclosed methods, processes and systems are useful in identifying and grouping together batteries with substantially the same or similar elemental composition and / or chemical make-up. For example, batteries with a lithium-titanate composition may be identified and grouped with like batteries, batteries with a lithium manganese oxide composition may be grouped with like batteries, batteries with a lithium cobalt oxide composition may be grouped with like batteries, and so on. The batteries may be sorted and grouped prior to the batteries being recycled or otherwise prior to the destruction of the battery. In this way, the resulting black mass from the sorted / grouped batteries may be less heterogeneous compared to a black mass produced from the original mixed stream. The resulting black mass may, therefore, have higher purity with regard to the concentration of individual metals. This higher purity may result in the resulting black mass having a greater value, compared to black mass resulting from the original mixed stream. The resulting black mass may also more closely conform to material specifications related to the reuse of the metals.

[0034] In at least one example, the battery identification and sortation system may include a separator configured to spatially separate batteries of a stream of mixed batteries. In this way, each battery of the stream of mixed batteries may be separated into a plurality of individual batteries, or, in examples where the mixed stream of batteries includes predominantly lithium batteries, lithium individual batteries (LIBs). The battery identification and sortation system may include a sensor device that may scan each individual battery. The sensor device may include an emitter configured to direct a nondestructive beam of neutrons at an individual battery of the plurality. The neutrons may enter and excite the nucleus of atoms of the individual battery, which may make the atom unstable until the extra neutron is ejected. Upon ejection of the extra neutron, a Gamma ray may be emitted. The sensor device may include a receiver configured to detect an electromagnetic signature from the individual battery. For example, the receiver may measure the energy of the Gamma rays being emitted in MeV. The sensor device may include a processor configured to determine the composition of the individual battery based on the electromagnetic signature. For example, each element that can be measured has a different MeV spectrum and thus the processor may determine elements that are present in the individual battery based on the MeV spectrum measured by the sensor. In manyembodiments, the energy range of the spectrum detected by the sensor is generally below 1 MeV. However, in some embodiments, the energy range of the spectrum may be up to and including 1.5 MeV. Thus, the processor may determine the composition of the individual battery. The sensor device may include a computer system. The computer system may include a processor, a memory component, an interface, a network interface, a display, and an external device. In some embodiments, the computer system of the sensor device may allow a user to configure settings of the sensor device, including the sensitivity ranges and detection limits for elements. In some embodiments, the computer system may allow a user to interface with the processor of the sensor device, which may allow the user to control the configuration of the processor of the sensor device. The computer system may also allow the user to control maintenance of the sensor device. The battery identification and sortation system may include a sorting device configured to direct the individual battery to a predetermined location based on the electromagnetic signature. For example, the sorting device may direct batteries with the same or similar composition to the same location so that batteries with the same or similar compositions may be compiled and then subsequently recycled as a batch. By recycling batteries with the same or similar compositions together, the black mass produced from each respective battery may include the same or similar mixture of metals and may have higher purity with regard to the metal concentrations.

[0035] Optionally, some embodiments of the battery identification and sortation system may include a computer system. The computer system may include a processor, a memory component, an interface, a network interface, a display, and an external device. A user may interface with the computer system and direct the method executed by the system. In some embodiments, the user may control the spatial separation of batteries by interfacing with the computer system. In some embodiments, the user may interface with the computer system to designate determinations included in a method, such as threshold values or relative amount values used to determine a battery type, a system may execute. In some embodiments, a user may interface with the computer system to configure a sorting device and determine where a system will sort a battery based on an identification of the battery, including battery composition.

[0036] Turning to the figures, illustrative embodiments of the present disclosure will now be discussed in more detail. FIG. 1 is an annotated flow chart of a process 100 for batterysortation. For example, the process 100 can sort a stream of mixed batteries and separate each battery of the stream into groups based on the composition of each respective battery such that each group includes batteries with the same or similar composition.

[0037] The process 100 may include receiving or obtaining a stream of mixed batteries (Block 105). For example, a battery recycling facility, equipment at a battery recycling facility such as a conveyor belt, or the like can receive the stream of mixed batteries. The stream of mixed batteries may be or may include predominantly mixed lithium batteries. The stream may also include other batteries, such as batteries of unknown or nonconforming type. The stream may also include non-lithium batteries. The stream of mixed batteries may include end-of-life batteries and battery scrap, e.g., batteries and battery scrap discarded, recycled, or otherwise not in use. In some examples, the stream of mixed batteries may include batteries having a structural material that may not prohibit the measurements or sensing described herein. The stream of mixed batteries may include different types of batteries, e.g., with different chemical structures or chemistries such that the batteries have different compositions or elemental make-ups. For example, the stream of mixed batteries may include a variety of lithium batteries.SINGULATION DEVICE

[0038] The process 100 may include spatially separating each battery of the stream of mixed batteries (Block 110). For example, the stream of mixed batteries may be fed into a singulation device that may spatially separate the batteries into a plurality of individual batteries. For one example, the singulation device may align the batteries to one or more single file lines, c.g., on a conveyor bclt(s). In some embodiments, the singulation device aligns the single file line of batteries with the direction of a device to move the batteries from one process to another, e.g., along the longitudinal axis of conveyor belts. Optionally, the singulation device may create parallel single file lines to allow a system to analyze multiple batteries in parallel. In some embodiments, the singulation device aligns the batteries to increase the efficiency of a sensor device of the system. In another example, the stream of mixed batteries may be manually spatially separated.SENSOR DEVICE

[0039] The process 100 may include passing an individual battery of the plurality of individual batteries through a sensor or sensor device (Block 115). In some examples, the sensor may be a radiometric sensor. For example, the sensor may be a prompt-gamma neutron activation analysis (PGNAA) sensor, a pulsed fast thermal neutron activation (PFTNA) sensor, and the like. The sensor may detect the elemental make-up of the individual battery, for example, by detecting and analyzing an electromagnetic signature from the individual battery.

[0040] FIG. 2 is an annotated flow chart of a process 200 of the sensor device, e.g., of radiometric sensing. The sensor may include an emitter that may produce neutrons and a device that may help direct a non-destructive beam of neutrons at the individual battery. In some embodiments, the sensor may include a director to direct the beam of non-destructive neutrons. For example, as depicted in FIG. 2, a “Thermal Neutron” is directed towards a “Nucleus”. The neutrons may be directed at, or bombard, the individual battery such that the neutrons may be captured by nuclei of various atoms within the individual battery. This capture results in the “Excited Nucleus” depicted in FIG. 2. The bombardment of the neutrons is non-destructive because the battery is not physically breached, broken, or destroyed. Rather, while many neutrons pass through the battery, some of those neutrons are captured by individual atom’s nucleus rendering that nucleus unstable. The unstable nucleus returns to a stable state by emitting a gamma ray. Different elements produce characteristic gamma ray spectra that may be useful in identifying the element. The “Stable Nucleus” is depicted in FIG. 2.

[0041] The sensor may include a receiver that may measure an electromagnetic signature from the individual battery, e.g., emitted in response to the non-destructive beam of neutrons. For example, the electromagnetic signature may correspond to gamma rays emitted by a battery in response to the non-destructive beam of neutrons. For example, the sensor may measure the energy of the gamma rays being emitted. In one example, the sensor may measure the energy emitted in the MeV range. In another example, the sensor may measure the energy of the gamma rays being emitted in the giga-eV, kilo-eV range or other range suitable to identify a battery chemistry. A sample readout from the sensor device isdepicted in FIG. 3. Each element that can be measured has a different energy spectrum, indicative of that element. However, not all elements can be measured. For example, the periodic table depicted in FIG. 6 includes the detection limits for each element based for a PGNAA type sensor.

[0042] The sensor may include a processor that may determine the composition of the individual battery based on the electromagnetic signature, e.g., based on the energy of the gamma rays emitted from a battery. For example, the processor may detect and analyze the electromagnetic signature, e.g., the detected spectrum, of the individual battery and determine the composition of the individual battery based on known energy values in gamma ray spectra of specific elements. For example, since each element that can be measured has a different spectra, the processor may determine elements that are present in the individual battery based on the measured energy values and thus may determine the composition of the individual battery. FIGS. 10 and 11 show examples of such spectra.

[0043] Each individual battery of the plurality of individual batteries may be passed through the sensor. For example, the singulation device may spatially separate the batteries of the stream of mixed batteries a sufficient distance from one another such that each battery may pass through the sensor individually. In some embodiments, the system may use a singulation device to separate each battery a sufficient distance from other batteries so the sensor device of the system can analyze each battery and prevent or reduce compromising or confusing a measured electromagnetic signature from the battery with a measured electromagnetic signature from a different battery.SORTING DEVICE

[0044] The process 100 may include passing the individual battery through a sorting device (Block 120). In some examples, the sorting device may include deflector bars or robotic sorting means. In other examples, the sorting device may include manual sortation. The sorting device may receive information from the sensor. For example, the sorting device may receive the composition of the individual battery determined by the sensor.

[0045] The process 100 may include directing the individual battery to a location based on the composition or the electromagnetic signature of the individual battery (Blocks 125-155). The location may be a predetermined location. For example, a battery with a composition of lithium-titanate may be directed to a first location (Block 125); a battery with a composition of lithium ferrous phosphate or lithium iron phosphate be directed to a second location (Block 130); a battery with a composition of lithium manganese oxide may be directed to a third location (Block 135); a battery with a composition of lithium cobalt oxide may be directed to a fourth location (Block 140); a battery with a composition of lithium nickel-manganese-cobalt oxide may be directed to a fifth location (Block 145); a battery with a composition of lithium nickel-cobalt-aluminum oxide may be directed to a sixth location (Block 150); and a battery with a composition of other, such as lithium metal, unknown, or non-conforming may be directed to a seventh location (Block 155). The process 100 may be structured such that not every Block 125-155 is included. Additionally, the Blocks 125-155 are only examples of possible sortation groups, but are not limiting in any way. For example, the process 100 may include sortation groups in addition to the Blocks 125-155.

[0046] In this way, the sorting device may direct batteries with the same or similar composition to the same location so that batteries with the same or similar compositions may be compiled and then subsequently recycled as a batch. By recycling batteries with the same or similar compositions together, the black mass produced from each respective battery may include the same or similar mixture of metals and may have higher purity with regard to the metal concentrations.

[0047] Optionally, some embodiments may include a sorting device that includes a computer system. For example, a user may control or configure the sorting device by interfacing with the computer system.

[0048] FIG. 4 is an annotated flow chart 400 of one embodiment of sortation groups and one embodiment of how the battery type corresponding to the elemental make-up and composition of the battery may be determined. It is understood that the order and / or values presented in FIG. 4 may be varied within the disclosed method. A sensor may detect an electromagnetic signature from an individual battery that is emitted in response to a nondestructive beam of neutrons bombarding the individual battery, and a sorting device may direct the individual battery to a predetermined location based on the electromagneticsignature. The predetermined location may be or may correspond to one of the various sortation groups 415, 425, 435, 445, 455, 465, 475, 480 depicted in FIG. 4, for example, and can correspond to the battery type and thus composition of the individual battery.

[0049] The flow chart 400 may begin with operation 405 and a stream of mixed batteries may be received. The stream of mixed batteries may be or may include predominantly mixed lithium batteries. The stream may also include other batteries, such as lithium metal and batteries of unknown or non-conforming type. The stream of mixed batteries may include non-lithium batteries. The stream of mixed batteries may include end-of-life batteries and battery scrap, e.g., batteries and battery scrap discarded, recycled, or otherwise not in use. In some examples, the stream of mixed batteries may include batteries having a structural material that may not prohibit the measurements or sensing described herein. The stream of mixed batteries may include different types of batteries, e.g., with different chemical structures or chemistries such that the batteries have different compositions or elemental make-ups. For example, the stream of mixed batteries may include a variety of lithium batteries.

[0050] Each battery of the stream of mixed batteries may be spatially separated. For example, all of the batteries of the stream of mixed batteries may be separated a sufficient distance from one another such that each battery may individually pass through a sensor, e.g., a radiometric sensor as described herein. The batteries may be separated via a separation device or manually. Each individual battery may pass through the sensor and the sensor may detect an electromagnetic signature from each individual battery, e.g., emitted in response to the non-destructive beam of neutrons, and the elemental make-up of each individual battery may be determined.

[0051] The type of each individual battery may be determined according to the composition of the individual battery, and each individual battery may be directed to a sortation group based on the determined battery type and composition. For example, the output from the radiometric sensor may be automatically analyzed and, based on the analysis, each individual battery scanned may be directed into one of the categories or sortation groups 415, 425, 435, 445, 455, 465, 475, 480.

[0052] For example, as depicted by line 405 A, once the elemental make-up of the individual battery is determined via the sensor, the process may proceed to operation 410 and a determination of whether a threshold amount / value / concentration of titanium is present in the individual battery may be made. In various embodiments the threshold may be from about 10% to 1% titanium, wherein the threshold may be selected to minimize or prevent false positives - i.e., identifying a battery being lithium-titanate type that is not lithium-titanate. For the example depicted in FIG. 4, a determination of whether greater than or equal to about 2% titanium is present in the individual battery may be made. In various embodiments, if titanium is present, such as greater than or equal to about 2% titanium is present, then the process may proceed to operation 415 as depicted by arrow 410A, and the individual battery may be categorized as a lithium-titanate battery. For example, the battery chemistry of lithium-titanate type batteries may be known and may include greater than or equal to about 2% titanium. Thus, in the event that the individual battery includes greater than or equal to about 2% titanium, then the individual battery may be categorized as a lithium-titanate type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium-titanate type batteries are directed. In this way, all lithium-titanate type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 410 titanium is not present, such as less than about 2% titanium is present, then the process may proceed, for example, to operation 420 as depicted by arrow 410B.

[0053] In some examples, at operation 420 a determination of whether a threshold amount of manganese and / or cobalt is present in the individual battery may be made. In various embodiments the threshold may be from about 10% to 0.1% manganese or cobalt, wherein the threshold may be selected to minimize or prevent false positives. For the example shown in FIG. 4, a determination of whether greater than or equal to about 3.5% manganese and whether less than or equal to about 3.5% cobalt is present in the individual battery may be made. If manganese is present, such as greater than or equal to about 3.5% manganese is present, and if less than or equal to about 3.5% cobalt is present, or no cobalt is present, then the process may proceed to operation 425 as depicted by arrow 420A, and the individual battery may be categorized as a lithium manganese oxide battery. For example, the battery chemistry of lithium manganese oxide type batteries may be known and mayinclude greater than or equal to about 3.5% manganese and less than or equal to about 3.5% cobalt. Thus, in the event that the individual battery includes greater than or equal to about 3.5% manganese and less than or equal to about 3.5% cobalt, then the individual battery may be categorized as a lithium manganese oxide type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium manganese oxide type batteries are directed. In this way, all lithium manganese oxide type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 420 manganese is not present, such as less than about 3.5% manganese is present, or greater than 3.5% cobalt is present, then the process may proceed to operation 430 as depicted by arrow 420B.

[0054] In some examples, at operation 430 a determination of whether a threshold amount of phosphorus is present in the individual battery may be made. In various embodiments the threshold may be from about 5% to 0.5% phosphorous, wherein the threshold may be selected to minimize or prevent false positives. For the example shown in FIG. 4, a determination of whether greater than or equal to about 1% phosphorus is present in the individual battery may be made. If phosphorus is present, such as greater than or equal to about 1% phosphorus is present, then the process may proceed to operation 435 as depicted by arrow 430A, and the individual battery may be categorized as a lithium ferrous phosphate or lithium iron phosphate battery. For example, the battery chemistry of lithium ferrous phosphate or lithium iron phosphate type batteries may be known and may include greater than or equal to about 1% phosphorus. Thus, in the event that the individual battery includes greater than or equal to about 1% phosphorus, then the individual battery may be categorized as a lithium ferrous phosphate or lithium iron phosphate type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium ferrous phosphate or lithium iron phosphate type batteries are directed. In this way, all lithium ferrous phosphate or lithium iron phosphate type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 430 phosphorus is not present, such as less than about 1% phosphorus is present, then the process may proceed to operation 440 as depicted by arrow 430B.

[0055] In some examples, at operation 440 a determination of whether a threshold amount of cobalt is present in the individual battery may be made. In various embodiments thethreshold may be from about 20% to 5% cobalt, wherein the threshold may be selected to minimize or prevent false positives. For the example shown in FIG. 4, a determination of whether greater than or equal to about 10% cobalt may be made. If cobalt is present, such as greater than or equal to about 10% cobalt is present, then the process may proceed to operation 445 as depicted by arrow 440A, and the individual battery may be categorized as a lithium cobalt oxide battery. For example, the battery chemistry of lithium cobalt oxide type batteries may be known and may include greater than or equal to about 10% cobalt. Thus, in the event that the individual battery includes greater than or equal to about 10% cobalt, then the individual battery may be categorized as a lithium cobalt oxide type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium cobalt oxide type batteries are directed. In this way, all lithium cobalt oxide type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 440 cobalt is not present, such as less than about 10% cobalt is present, then the process may proceed to operation 450 as depicted by arrow 440B.

[0056] In some examples, at operation 450 a determination of whether a threshold amount of manganese is present in the individual battery may be made. In various embodiments the threshold may be from about 5% to 0.05% manganese, wherein the threshold may be selected to minimize or prevent false positives. For the example shown in FIG. 4, a determination of whether greater than or equal to about 0.3% manganese may be made. If manganese is present, such as greater than or equal to about 0.3% manganese is present, then the process may proceed to operation 455 as depicted by arrow 450A, and the individual battery may be categorized as a lithium nickel-manganese-cobalt battery. For example, the battery chemistry of lithium nickel-manganese-cobalt type batteries may be known and may include greater than or equal to about 0.3% manganese. Thus, in the event that the individual battery includes greater than or equal to about 0.3% manganese, then the individual battery may be categorized as a lithium nickel-manganese-cobalt type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium nickel-manganese-cobalt type batteries are directed. In this way, all lithium nickel-manganese-cobalt type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 450 manganese is notpresent, such as less than about 0.3% manganese is present, then the process may proceed to operation 460 as depicted by arrow 450B.

[0057] In some examples, at operation 460 a determination of whether a threshold amount of nickel is present in the individual battery may be made. In various embodiments the threshold may be from about 10% to 1% nickel, wherein the threshold may be selected to minimize or prevent false positives. For the example shown in FIG. 4, a determination of whether greater than or equal to about 4% nickel may be made. If nickel is present, such as greater than or equal to about 4% nickel is present, then the process may proceed to operation 465 as depicted by arrow 460A, and the individual battery may be categorized as a lithium nickel-cobalt-aluminum oxide battery. For example, the battery chemistry of lithium nickel-cobalt-aluminum oxide type batteries may be known and may include greater than or equal to about 4% nickel. Thus, in the event that the individual battery includes greater than or equal to about 4% nickel, then the individual battery may be categorized as a lithium nickel-cobalt-aluminum oxide type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium nickel- cobalt-aluminum oxide batteries are directed. In this way, all lithium nickel-cobalt- aluminum oxide type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 460 nickel is not present, such as less than about 4% nickel is present, then the process may proceed to operation 470 as depicted by arrow 460B.

[0058] In some examples, at operation 470 a determination of whether a threshold amount of vanadium is present in the individual battery may be made. In various embodiments the threshold may be from about 10% to 1 % vanadium, wherein the threshold may be selected to minimize or prevent false positives. For example, a determination of whether greater than or equal to about 4% vanadium may be made. If vanadium is present, such as greater than or equal to about 4% vanadium is present, then the process may proceed to operation 475 as depicted by arrow 470A, and the individual battery may be categorized as a lithium metal battery. For example, the battery chemistry of lithium metal type batteries may be known and may include greater than or equal to about 4% vanadium. Thus, in the event that the individual battery includes greater than or equal to about 4% vanadium, then the individual battery may be categorized as a lithium metal type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithiummetal type batteries are directed. In this way, all lithium metal type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 470 vanadium is not present, such as less than about 4% vanadium is present, then the process may proceed to operation 480 as depicted by arrow 470B.

[0059] In the event that a battery proceeds to operation 480, the battery may be categorized as “other”, which may include lithium metal batteries and batteries of unknown or nonconforming type. In some embodiments, “other” batteries may include batteries with a composition that does not conform to a known composition of a battery type or a known battery chemistry. In some embodiments, “other” batteries may include batteries with compositions that do not match a known composition of a battery type. In some embodiments, “other” batteries may include lithium batteries with compositions different from known compositions for lithium batteries. Batteries categorized as “other” may be individually inspected. Further, after an elemental identification is made, a determination operation, similar to operations 410, 420, 430, 440, 450, 460, 470, may be developed and added to the disclosed processes, methods, and devices. For example, additional determination operations may be added to the example flow chart 400 once more known battery chemistries are determined. Likewise, after an elemental identification is made, a sortation group or categorization, similar to sortation groups or categorizations 415, 425, 435, 445, 455, 465, 475, 480, may be added to the disclosed processes, methods, and devices. For example, additional sortation groups or categorizations may be added to the example flow chart 400 once more known battery chemistries are determined.

[0060] Operations 410, 420, 430, 440, 450, 460, 470 may be based on information corresponding to known battery chemistries. FIG. 4 depicts one embodiment of detection limits based on known battery chemistry data. The system, devices and methods described herein may be structured such that not every operation 410, 420, 430, 440, 450, 460, 470 is included and / or the operations are ordered differently or one or more performed in parallel. Additionally, the operations 410, 420, 430, 440, 450, 460, 470 are only examples of possible determinations that may be made, but are not limiting in any way. For example, the system, devices and methods described herein may include determinations in addition to the operations 410, 420, 430, 440, 450, 460, 470.

[0061] The system, devices and methods described herein may be structured such that not every group or categorization 415, 425, 435, 445, 455, 465, 475, 480 is included. Additionally, the groups 415, 425, 435, 445, 455, 465, 475, 480 are examples of possible sortation groups, but are not limiting in any way. For example, the system, devices and methods described herein may include sortation groups in addition to the groups 415, 425, 435, 445, 455, 465, 475, 480.

[0062] FIG. 5 is an annotated flow chart 500 of one embodiment of sortation groups and one embodiment of how the battery type corresponding to the elemental make-up and composition of the battery may be determined. Whereas FIG. 4 depicts a sortation method based on threshold or absolute values of exemplary elements in a battery, the flow-chart of FIG. 5 may describe a method demonstrating identification using a combination of absolute measurement and / or the use of amounts of various elements relative to each other. A sensor may detect an electromagnetic signature from an individual battery that is emitted in response to a non-destructive beam of neutrons bombarding the individual battery, and a sorting device may direct the individual battery to a predetermined location based on the relative values of elements in the battery as determined from the electromagnetic signature. For example, the relative amount values of elements in the battery may be used to identify the battery type of the individual battery and the sorting device may direct the individual battery to the predetermined location based on the identified battery type. The predetermined location may be or may correspond to one of the various sortation groups 515, 525, 535, 545, 555, 565, 575, 580 depicted in FIG. 5, for example, and can correspond to the battery type and thus composition of the individual battery. It is understood that the values in FIG. 5, like those in FIG. 4 described above, represent one value within a wider range of possible values.

[0063] The flow chart 500 may begin with operation 505 and a stream of mixed batteries may be received. The stream of mixed batteries may be or may include predominantly mixed lithium batteries. The stream may also include other batteries, such as lithium metal batteries and batteries of unknown or non-conforming type. The stream of mixed batteries may include non-lithium batteries. The stream of mixed batteries may include end-of-life batteries and battery scrap, e.g., batteries and battery scrap discarded, recycled, or otherwise not in use. In some examples, the stream of mixed batteries may include batteries having astructural material that may not prohibit the measurements or sensing described herein. The stream of mixed batteries may include different types of batteries, e.g., with different chemical structures or chemistries such that the batteries have different compositions or elemental make-ups. For example, the stream of mixed batteries may include a variety of lithium batteries.

[0064] Each battery of the stream of mixed batteries may be spatially separated. For example, all of the batteries of the stream of mixed batteries may be separated a sufficient distance from one another such that each battery may individually pass through a sensor, e.g., a radiometric sensor as described herein. The batteries may be separated via a separation device or manually. Each individual battery may pass through the sensor and the sensor may detect an electromagnetic signature from each individual battery, e.g., emitted in response to the non-destructive beam of neutrons, and the elemental make-up of each individual battery may be determined.

[0065] The type of each individual battery may be determined according to the composition of the individual battery, and each individual battery may be directed to a sortation group based on the determined battery type and composition. For example, the output from the radiometric sensor may be automatically analyzed and, based on the analysis, each individual battery scanned may be directed into one of the categories or sortation groups 515, 525, 535, 545, 555, 565, 575, 580.

[0066] For example as depicted by line 505A, once the elemental make-up of the individual battery is determined via the sensor, the process may proceed to operation 510 and a determination of whether titanium is present in the individual battery may be made. For example, a determination of whether greater than or equal to about 2% titanium is present in the individual battery may be made. In various embodiments, the determination at operation 510 may be similar to or the same as the determination made at operation 410 and a determination of whether a threshold amount of titanium, such as between 10% to 1% for example, is present in the individual battery may be made. If titanium is present, such as greater than or equal to about 2% titanium is present, then the process may proceed to operation 515 as depicted by arrow 510A, and the individual battery may be categorized as a lithium-titanate battery. For example, the battery chemistry oflithium-titanate type batteries may be known and may include greater than or equal to about 2% titanium. Thus, in the event that the individual battery includes greater than or equal to about 2% titanium, then the individual battery may be categorized as a lithium-titanate type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium-titanate type batteries are directed. In this way, all lithium-titanate type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 510 titanium is not present, such as less than about 2% titanium is present, then the process may proceed, for example, to operation 520 as depicted by arrow 510B.

[0067] In some examples, at operation 520 a determination of whether manganese and / or cobalt is present in the individual battery may be made. For example, a determination of whether more manganese is present than cobalt, and more manganese is present than nickel, may be made. If manganese is present, such as more than cither cobalt or nickel, then the process may proceed to operation 525 as depicted by arrow 520A, and the individual battery may be categorized as a lithium manganese oxide battery. For example, the battery chemistry of lithium manganese oxide type batteries may be known and may include greater compositions with more manganese than either cobalt or nickel. Thus, in the event that the individual battery includes more manganese than either cobalt or nickel, then the individual battery may be categorized as a lithium manganese oxide type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium manganese oxide type batteries are directed. In this way, all lithium manganese oxide type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 520 manganese is not present, or there is less manganese than either cobalt or nickel, then the process may proceed to operation 530 as depicted by arrow 520B.

[0068] In some examples, at operation 530 a determination of whether phosphorus is present in the individual battery may be made. For example, a determination of whether greater than or equal to about 1% phosphorus is present in the individual battery may be made. In various embodiments, the determination at operation 530 may be similar to or the same as the determination made at operation 430 and a determination of whether a threshold amount of phosphorus, such as between 5% to 0.5% for example, is present in the individualbattery may be made. If phosphorus is present, such as greater than or equal to about 1% phosphorus is present, then the process may proceed to operation 535 as depicted by arrow 53OA, and the individual battery may be categorized as a lithium ferrous phosphate or lithium iron phosphate battery. For example, the battery chemistry of lithium ferrous phosphate or lithium iron phosphate type batteries may be known and may include greater than or equal to about 1% phosphorus. Thus, in the event that the individual battery includes greater than or equal to about 1% phosphorus, then the individual battery may be categorized as a lithium ferrous phosphate or lithium iron phosphate type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium ferrous phosphate or lithium iron phosphate type batteries are directed. In this way, all lithium ferrous phosphate or lithium iron phosphate type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 530 phosphorus is not present, such as less than about 1% phosphorus is present, then the process may proceed to operation 540 as depicted by arrow 530B.

[0069] In some examples, at operation 540 a determination of whether cobalt is present in the individual battery may be made. For example, a determination of whether more cobalt is present than a factor, labeled “X” in FIG. 5, multiplied by the amount of nickel may be made. If cobalt is present, such as more cobalt than the factor, labeled “X” in FIG. 5, multiplied by the amount of nickel, then the process may proceed to operation 545 as depicted by arrow 540A, and the individual battery may be categorized as a lithium cobalt oxide battery where “X” is greater than 1. For example, the battery chemistry of lithium cobalt oxide type batteries may be known and may include more cobalt than a factor multiplied by the amount of nickel. Thus, in the event that the individual battery includes more cobalt than the factor multiplied by the amount of nickel, then the individual battery may be categorized as a lithium cobalt oxide type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium cobalt oxide type batteries are directed. In this way, all lithium cobalt oxide type batteries may be compiled and may be subsequently recycled together as a batch. In other examples, the factor may be between 1.5 and 2. If at operation 540 the concentration of cobalt is not greater than the factor multiplied by the concentration of nickel, then the process may proceed to operation 550 as depicted by arrow 540B.

[0070] In some examples, at operation 550 a determination of whether manganese is present in the individual battery may be made. For example, a determination of whether greater than or equal to about 0.3% manganese is present may be made and a determination of whether manganese is at least half the concentration of cobalt, but not more than double the concentration of cobalt may be made. If manganese is present, such as greater than or equal to about 2% manganese is present, then the process may proceed to operation 555 as depicted by arrow 550A, and the individual battery may be categorized as a lithium nickelmanganese-cobalt battery. For example, the battery chemistry of lithium nickel-manganese- cobalt type batteries may be known and may include greater than or equal to about 0.3% manganese. Thus, in the event that the individual battery includes greater than or equal to about 0.3% manganese, and lithium manganese oxide batteries have already been identified, then the individual battery may be categorized as a lithium nickel-manganese-cobalt type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium nickcl-mangancsc-cobalt type batteries arc directed. In this way, all lithium nickel-manganese-cobalt type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 550 manganese is not present, such as less than about 0.3% manganese is present, then the process may proceed to operation 560 as depicted by arrow 550B.

[0071] In some examples, at operation 560 a determination of whether nickel is present in the individual battery may be made. For example, a determination of whether greater than or equal to about 4% nickel may be made, a determination of whether more cobalt than two times the amount of manganese may be made, and / or a determination of whether greater than or equal to about 1% cobalt may be made. If nickel is present, such as greater than or equal to about 4% nickel is present, then the process may proceed to operation 565 as depicted by arrow 560A, and the individual battery may be categorized as a lithium nickel- cobalt-aluminum oxide battery. For example, the battery chemistry of lithium nickel-cobalt- aluminum oxide type batteries may be known and may include greater than or equal to about 4% nickel. Thus, in the event that the individual battery includes greater than or equal to about 4% nickel, and all NMC batteries have already been identified, then a remaining unidentified individual battery may be categorized as a lithium nickel-cobalt-aluminum oxide type battery. The individual battery may be directed to a predetermined location inwhich all individual batteries identified as lithium nickel-cobalt-aluminum oxide batteries are directed. In this way, all lithium nickel-cobalt-aluminum oxide type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 560 nickel is not present, such as less than about 4% nickel is present, then the process may proceed to operation 570 as depicted by arrow 560B.

[0072] In some examples, at operation 570 a determination of whether vanadium is present in the individual battery may be made. For example, a determination of whether greater than or equal to about 4% vanadium may be made. In various embodiments, the determination at operation 570 may be similar to or the same as the determination made at operation 470 and a determination of whether a threshold amount of vanadium, such as between 10% to 1% for example, is present in the individual battery may be made. If vanadium is present, such as greater than or equal to about 4% vanadium is present, then the process may proceed to operation 575 as depicted by arrow 570A, and the individual battery may be categorized as a lithium metal battery. For example, the battery chemistry of lithium metal type batteries may be known and may include greater than or equal to about 4% vanadium. Thus, in the event that the individual battery includes greater than or equal to about 4% vanadium, then the individual battery may be categorized as a lithium metal type battery. The individual battery may be directed to a predetermined location in which all individual batteries identified as lithium metal type batteries are directed. In this way, some lithium metal type batteries may be compiled and may be subsequently recycled together as a batch. If at operation 570 vanadium is not present, such as less than about 4% vanadium is present, then the process may proceed to operation 580 as depicted by arrow 570B.

[0073] In the event that a battery proceeds to operation 580, the battery may be categorized as “other”, which may include batteries of unknown or non-conforming type. Batteries categorized as other may be individually inspected. Further, after an elemental identification is made, a determination operation, similar to operations 510, 520, 530, 540, 550, 560, 570, may be developed and added to the disclosed processes, methods, and devices. For example, additional determination operations may be added to the example flow chart 500 once more known battery chemistries are determined. Likewise, after an elemental identification is made, a sortation group or categorization, similar to sortation groups or categorizations 515, 525, 535, 545, 555, 565, 575, 580, may be added to thedisclosed processes, methods, and devices. For example, additional sortation groups or categorizations may be added to the example flow chart 500 once more known battery chemistries are determined.

[0074] Operations 510, 520, 530, 540, 550, 560, 570 may be based on information corresponding to known battery chemistries. FIG. 5 depicts one embodiment of detection limits that are relative to other elements. The system, devices and methods described herein may be structured such that not every operation 510, 520, 530, 540, 550, 560, 570 is included and / or the operations are ordered differently or one or more performed in parallel. Additionally, the operations 510, 520, 530, 540, 550, 560, 570 are examples of possible determinations that may be made, but are not limiting in any way. For example, the system, devices and methods described herein may include determinations in addition to the operations 510, 520, 530, 540, 550, 560, 570.

[0075] The system, devices and methods described herein may be structured such that not every group or categorization 515, 525, 535, 545, 555, 565, 575, 580 is included. Additionally, the groups 515, 525, 535, 545, 555, 565, 575, 580 are examples of possible sortation groups, but are not limiting in any way. For example, the system, devices and methods described herein may include sortation groups in addition to the groups 515, 525, 535, 545, 555, 565, 575, 580.

[0076] FIG. 6 is an annotated flow chart of a method 600 of one embodiment of sorting batteries into sortation groups suitable for execution by a sortation system, such as the system 100. The method 600 depicts an embodiment of how a battery type corresponding to the elemental make-up and composition of the battery may be determined by the system 100. The method 600 is based on threshold or absolute values of exemplary elements in a battery. In some embodiments, a system 100 executing the method 600 may choose certain threshold values to limit the number of false positive battery identifications. A sensor 115 may detect an electromagnetic signature from an individual battery or plurality of batteries emitted in response to a non-destructive beam of neutrons bombarding the battery. A sorting device 120 may sort a battery to a predetermined location based on the absolute values of elements in the battery as determined from the electromagnetic signature. For example, the method 600 may use absolute amount values of elements present in the battery to identifythe battery type of the battery and the sorting device 120 may sort the battery to the predetermined location based on the identified battery type. The predetermined location may be or may correspond to one of the various sortation groups 615, 625, 635, 645, 655, 665, 675, and / or 680, as depicted in FIG. 6 for example, and can correspond to the battery type and / or the composition of the battery. The values in FIG. 6, like those in the previous figures described herein, represent one value within a wider range of possible values.

[0077] The method 600 may begin with operation 605 and a system 100 receives a stream of mixed batteries. The stream of mixed batteries may be or may include predominantly mixed lithium batteries. The stream may also include other batteries, such as lithium metal batteries and batteries of an unknown or a non-conforming type. The stream of mixed batteries may include non-lithium batteries. The stream of mixed batteries may include end- of-life batteries and battery scrap, e.g., batteries and battery scrap discarded, recycled, or otherwise not in use. In some examples, the stream of mixed batteries may include batteries having a structural material that may not prohibit the measurements or sensing described herein. The stream of mixed batteries may include different types of batteries, e.g., with different chemical structures or chemistries such that the batteries have different compositions or elemental make-ups. For example, the stream of mixed batteries may include a variety of lithium batteries.

[0078] According to the method 600, the system 100 may spatially separate each battery of the stream of mixed batteries. For example, the system 100 may separate all of the batteries of the stream of mixed batteries a sufficient distance from one another such that each battery may individually pass through the sensor 115, e.g., a radiometric sensor as described herein. In some embodiments of the method 600, the system 100 may use a singulation device 110, e.g., a separation device, to separate the batteries. Alternatively, a user may separate the batteries manually. Each battery may pass through the sensor 115, and the sensor 115 may detect an electromagnetic signature from each battery, e.g., emitted in response to the non-destructive beam of neutrons, and the system 100 determines the elemental make-up of each battery according to the method 600.

[0079] The system 100 may determine the type of each battery according to the method 600 by determining the composition of the battery. The system 100 may sort the battery to asortation group based on the determined battery type and composition. For example, the system 100 may automatically analyze the output from the radiometric sensor 115, and based on the analysis, the system 100 executing the method 600 may sort each battery scanned into one of the sortation groups 615, 625, 635, 645, 655, 665, 675, and 680, e.g., by a sortation device 120. roo8o] For example, as depicted by line 605 A, once the system 100 determines the elemental make-up of the battery via the sensor 115, the method 600 may proceed to operation 610 and the system 100 may determine whether the battery includes a threshold amount of titanium. For example, the system 100 may determine whether the battery includes greater than or equal to 8% titanium. In various embodiments, the method 600 may make a determination at operation 610 similar to or substantially the same as the determination made at operation 410 of method 400. For example, the system 100 may determine whether a battery includes a threshold amount of titanium, such as between 10% to 1%. If a battery includes titanium, such as greater than or equal to about 8% titanium, then the system may place the battery into the sortation group 615 as depicted by arrow 610A, and the system 100 may categorize the battery as a lithium-titanate battery according to the method 600. For example, the battery chemistry of lithium-titanate type batteries may include greater than or equal to about 2% titanium. Thus, in the event the battery includes greater than or equal to about 8% titanium, the system 100 executing the method 600 may categorize the battery as a lithium-titanate type battery and may reduce the risk of a false positive. The system 100 may then sort the battery to a predetermined location where the method 600 sorts all batteries identified as lithium-titanate type batteries. In this way, the system 100 may compile all lithium-titanate type batteries and may subsequently recycle the batteries together as a batch. If at operation 610 the system 100 does not detect a threshold amount of titanium, such as less than about 8% titanium, then the method 600 may proceed, for example, to operation 620 as depicted by arrow 610B.

[0081] In some examples, the system 100 executing the method 600 may, at operation 620, determine whether a battery includes a threshold amount of manganese and / or cobalt. In various embodiments, the method 600 may include a threshold from about 10% to 0.1% manganese and / or cobalt. For example, FIG. 6 depicts threshold values of greater than or equal to 7.5% manganese, and less than or equal to 2% cobalt. If the system 100 determinesthe composition of manganese is greater than or equal to 7.5% and the composition of cobalt is less than or equal to 2%, then according to method 600, the system 100 may place the battery into the sortation group 625 as depicted by arrow 620A, and the system 100 may categorize the battery as a lithium manganese oxide battery. For example, lithium manganese oxide type batteries may be known and may include compositions of manganese 3.5% and greater and less than 3.5% cobalt. The method 600, may choose threshold values greater than 3.5% manganese and less than 3.5% cobalt to reduce false positives of lithium manganese oxide batteries. Thus, for example, if the system 100 determines the battery includes at least 7.5% manganese and less than or equal to 2% cobalt, then the system 100 executing method 600 may categorize the battery as a lithium manganese oxide type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 600 sorts all batteries identified as lithium manganese oxide type batteries. In this way, the system 100 according to the method 600 compiles all lithium manganese oxide type batteries and may subsequently recycle the batteries together as a batch. If at operation 620 the battery does not include a threshold amount of manganese, and / or the battery includes more than a threshold amount of cobalt, such as the battery includes less than 7.5% manganese and / or greater than 2% cobalt, then the system 100 executing the method 600 may proceed to operation 630 as depicted by arrow 620B.

[0082] In some examples, the system 100 executing method 600 may, determine whether a battery includes a threshold amount of phosphorus at operation 630. For example, the system 100, according to method 600, may determine whether a battery includes greater than or equal to about 2% phosphorus. In various embodiments, the method 600 may make a determination at operation 630 similar to or substantially the same as the determination made at operation 430 according to the method 400. For example, the method 600 may include a determination of whether a battery includes a threshold amount of phosphorus, for example between 5% to 0.5%. If a battery includes phosphorus, such as greater than or equal to about 2% phosphorus, then the system executing method 600 may place the battery into the sortation group 635 as depicted by arrow 630A, and the system 100 may categorize the battery as a lithium ferrous phosphate or lithium iron phosphate battery. For example, the battery chemistry of lithium ferrous phosphate or lithium iron phosphate type batteriesmay be known and may include greater than or equal to about 1% phosphorus. A threshold value of greater than 1 % phosphorous may reduce false positives of lithium ferrous phosphate or lithium iron phosphate batteries. Thus, in the event the battery includes greater than or equal to about 2% phosphorus, the system 100 executing the method 600 may categorize the battery as a lithium ferrous phosphate or lithium iron phosphate type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 600 sorts all batteries identified as lithium ferrous phosphate or lithium iron phosphate type batteries. In this way, the system 100 executing the method 600 compiles all lithium ferrous phosphate or lithium iron phosphate type batteries and may subsequently recycle the batteries together as a batch. According to the method 600, if at operation 630 the system 100 does not determine the battery includes a threshold amount of phosphorus, such as the battery includes less than about 2% phosphorus, then the method 600 may proceed to operation 640 as depicted by arrow 630B.

[0083] In some examples, the system 100 executing the method 600 may determine whether a battery includes a threshold amount of cobalt at operation 640. In various embodiments, the method 600 may include a threshold amount from 20% to 5% cobalt, wherein the threshold value may minimize or prevent false positives. For example, operation 640 may select a threshold value of 18% or greater of cobalt. The battery chemistry of lithium cobalt oxide type batteries may be known and may include greater than or equal to 10% cobalt. A threshold value greater than 10% cobalt may reduce the number of false positives of lithium cobalt oxide batteries. If, the system 100 determines a battery includes a threshold amount of cobalt, such as 18% or greater, then the system may place the battery into the sortation group 645 as depicted by arrow 640A, and the system 100 may categorize the battery as a lithium cobalt oxide battery. Thus, in the event the battery includes 18% or more cobalt, then the system 100 may categorize the battery as a lithium cobalt oxide type battery and reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location, where the method 600 sorts all batteries identified as lithium cobalt oxide type batteries. In this way, the system 100 executing the method 600 compiles all lithium cobalt oxide type batteries and may subsequently recycle the batteries together as a batch. If operation 640 does not determine the battery includes the thresholdamount of cobalt, such as less than about 18% cobalt is present, then the method 600 may proceed to operation 650 as depicted by arrow 640B.

[0084] In some examples, the system 100 executing method 600 determines at operation 650 whether a battery includes a threshold amount of manganese. In some examples, the method 600 may select a threshold amount from 5% to 0.05% manganese. For example, the system 100 executing the method 600 may determine whether a battery includes greater than or equal to about 2% manganese. If the system 100 determines the battery includes a threshold amount of manganese, such as greater than or equal to about 2% manganese, then the system may place the battery into the sortation group 655 as depicted by arrow 650A, and the system 100 may categorize the battery may as a lithium nickel-manganese-cobalt battery. A threshold value may limit false positives. For example, the battery chemistry of lithium nickel-manganese-cobalt type batteries may be known and may include greater than or equal to about 0.3% manganese. Thus, the method 600 may choose a threshold value greater than 0.3% manganese to reduce the number of false positives of lithium nickelmanganese-cobalt type batteries. In the event the battery includes greater than or equal to about 2% manganese, and the system 100 executing the method 600 has already identified the lithium manganese oxide batteries, then the system 100 may categorize the battery as a lithium nickel-manganese-cobalt type battery according to the method 600, and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location, where the method 600 sorts all batteries identified as lithium nickel-manganese- cobalt type batteries. In this way, the system 100 executing method 600 may compile all lithium nickel-manganese-cobalt type batteries and may subsequently recycle the batteries together as a batch. If operation 650 does not determine the battery includes a threshold amount of manganese, such as less than about 2% manganese, then the method 600 may proceed to operation 660 as depicted by arrow 650B.

[0085] In some examples, the system 100 executing the method 600 determines whether a battery includes a threshold amount of nickel at operation 660. For example, the system 100 executing the method 600 may determines whether a battery includes greater than or equal to about 6% nickel at operation 660. If the battery includes a threshold amount of nickel, such as greater than or equal to about 6% nickel, then the system may place the battery into the sortation group 665 as depicted by arrow 660A, and the system 100 may categorize thebattery as a lithium nickel-cobalt-aluminum oxide battery. A threshold amount may limit false positives. For example, the battery chemistry of lithium nickel-cobalt-aluminum oxide type batteries may be known and may include greater than or equal to about 4% nickel. A threshold value greater than 4% nickel may reduce the number of false positives of lithium nickel-cobalt aluminum oxide batteries. Thus, in the event the battery includes greater than or equal to about 6% nickel, and all NMC batteries have already been identified, then the system 100 executing the method 600 may categorize the battery as a lithium nickel-cobalt- aluminum oxide type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 600 sorts all lithium nickel-cobalt-aluminum oxide batteries. In this way, the system 100 executing the method 600 compiles all lithium nickel-cobalt-aluminum oxide type batteries and may subsequently recycle the batteries together as a batch. If at operation 660 the battery does not include a threshold amount of nickel, such as less than about 6% nickel, then the method 600 may proceed to operation 670 as depicted by arrow 660B.

[0086] In some examples, the system 100 executing the method 600 determines whether a battery includes a threshold amount of vanadium at operation 670. For example, at operation 670, the system 100 executing the method 600 may determine whether a battery includes greater than or equal to about 5% vanadium. In various embodiments, the method 600 at operation 670 may make a similar or substantially the same determination made at operation 470 of the method 400, and determine whether a battery includes a threshold amount of vanadium, such as between 10% to 1%. If the battery includes a threshold amount of vanadium, such as greater than or equal to about 5% vanadium, then the system may place the battery into the sortation group 675 as depicted by arrow 670A, and the system 100 may categorize the battery as a lithium metal battery. A threshold value may limit false positives of lithium metal batteries. For example, the battery chemistry of lithium metal type batteries may be known and may include greater than or equal to about 4% vanadium. A threshold value greater than 4% vanadium may reduce the number of false positives. Thus, if the battery includes greater than or equal to about 5% vanadium, then the system 100 executing the method 600 may categorize the battery as a lithium metal type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 600 sorts all batteries identified as lithium metal type batteries. In thisway, the system 100 executing the method 600 compiles at least some lithium metal type batteries and may subsequently recycle the batteries together as a batch. If the system 100 executing the method 600 at operation 670 does not include a threshold amount of vanadium, such as less than about 5% vanadium, then the method 600 may proceed to operation 680 as depicted by arrow 670B.

[0087] In the event a battery proceeds to sortation group 680, the system 100 executing the method 600 may categorize the battery as “other.” In some embodiments, the system 100 executing the method 600 may individually inspect batteries categorized as other. Optionally, after individual inspection makes an elemental identification, the system 100 and method 600 may add a determination operation, similar to operations 610, 620, 630, 640, 650, 660, and 670 to the disclosed processes, methods, and devices. For example, the system 100 executing the method 600 may add additional determination operations to the method 600 once the system 100 executing the method 600 determines more known battery chemistries. Likewise, after the system 100 makes an elemental identification, the system 100 executing the method 600 may add a sortation group, similar to sortation groups 615, 625, 635, 645, 655, 665, 675, and 680 to the disclosed processes, methods, and devices.

[0088] The method 600 may base operations 610, 620, 630, 640, 650, 660, and 670 on information corresponding to known battery chemistries. FIG. 6 depicts one embodiment of detection limits based on threshold values. The system, devices and methods described herein may be structured such that not every operation 610, 620, 630, 640, 650, 660, and 670 is included and / or the operations are ordered differently or one or more performed in parallel. Additionally, the operations 610, 620, 630, 640, 650, 660, and 670 are only examples of possible determinations the system 100 executing the method 600 may make, but are not limiting in any way. For example, the system, devices and methods described herein may include determinations in addition to the operations 610, 620, 630, 640, 650, 660, and 670.

[0089] The system, devices and methods described herein may be structured such that not every sortation group 615, 625, 635, 645, 655, 665, 675, and 680 is included. Additionally, the sortation groups 615, 625, 635, 645, 655, 665, 675, and 680 are only examples of possible sortation groups, but are not limiting in any way. For example, the system, devicesand methods described herein may include sortation groups in addition to the groups 615, 625, 635, 645, 655, 665, 675, and 680.

[0090] FIG. 7 is an annotated flow chart of a method 700 suitable for execution by a sortation system, such as the system 100. The method depicts an embodiment of how a system may determine a battery type corresponding to the elemental make up and composition of a battery, and sort the battery to a sortation group. The system 100 executing the method 700 may use a combination of absolute measurements and / or the relative amounts of various elements to identify the battery type and battery chemistry. A sensor 115 may detect an electromagnetic signature emitted from a battery in response to a nondestructive beam of neutrons bombarding the battery. A sorting device 120 may sort the battery to a predetermined location based on the threshold and / or relative values of elements in the battery as determined from the electromagnetic signature. For example, the system 100 may use the threshold and / or relative amount values of elements in the battery to identify the battery type according to the method 700. The sorting device may sort the battery to the predetermined location based on the identified battery type. The predetermined location may be or may correspond to one of the various sortation groups 715, 725, 735, 745, 755, 765, 775, and 780, and can correspond to the battery type and / or the composition of the battery. The values in FIG. 7 only represent one embodiment of values within a wider range of possible values.

[0091] The method 700 may begin with operation 705 and the system 100 receives a stream of mixed batteries. The stream of mixed batteries may be or may include predominantly mixed lithium batteries. The stream of mixed batteries may include nonlithium batteries. The stream may also include other batteries, such as lithium metal batteries and batteries of unknown or non-conforming type. The stream of mixed batteries may include end-of-life batteries and battery scrap, e.g., batteries and battery scrap discarded, recycled, or otherwise not in use. In some examples, the stream of mixed batteries may include batteries having a structural material that may not prohibit the measurements or sensing described herein. The stream of mixed batteries may include different types of batteries, e.g., with different chemical structures or chemistries such that the batteries have different compositions or elemental make-ups. For example, the stream of mixed batteries may include a variety of lithium batteries.

[0092] In some embodiments, the system 100 executing the method 700 may spatially separate each battery of the stream of mixed batteries. For example, a singulation device 110 may separate all of the batteries of the stream of mixed batteries a sufficient distance from one another such that each battery may individually pass through a sensor 115, e.g., a radiometric sensor as described herein. The singulation device 110 may separate the batteries via a separation device or manually. Each battery may pass through the sensor 115 and the sensor 115 may detect an electromagnetic signature from each battery, e.g., emitted in response to a non-destructive beam of neutrons, and the system 100 executing the method 700 may determine the elemental make-up and composition of each battery.

[0093] The system 100 executing the method 700 may determine the type of each battery according to the composition of the battery, and the system 100 may sort each battery to a sortation group according to the method 700 based on the determined battery type and composition. For example, the method 700 may have the system 100 automatically analyze the output from the radiometric sensor 115, based on the analysis, the system 100 may sort each battery scanned into one of the sortation groups 715, 725, 735, 745, 755, 765, 775, and 780 according to the method 700.

[0094] For example, once the system 100 determines the elemental make-up of the battery via the sensor 115, the method 700 may proceed to operation 710, as depicted by line 705A, and the system 100 may determine whether the battery includes a threshold amount of titanium. For example, at operation 710, the system 100 may determine whether the battery includes greater than or equal to about 8% titanium. In various embodiments, the method 700 at operation 710 may make a similar or substantially the same determination made at operation 410 of the method 400, and determine whether the battery includes a threshold amount of titanium, such as between 10% to 1%. If the battery includes a threshold amount of titanium, such as greater than or equal to about 8% titanium, then the system may place the battery into the sortation group 715 as depicted by arrow 710A, and the system 100 may categorize the battery as a lithium-titanate battery according to the method 700. For example, the battery chemistry of lithium-titanate type batteries may be known and may include greater than or equal to about 2% titanium. A threshold value greater than 2% titanium may reduce the number of false positives of lithium-titanate batteries. Thus, in the event that the battery includes greater than or equal to about 8% titanium, the system 100executing the method 700 may categorize the battery as a lithium-titanate type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium-titanate type batteries. In this way, the system 100 executing the method 700 may compile all lithium-titanate type batteries and may subsequently recycle the batteries together as a batch. If the battery does not include a threshold amount of titanium at operation 710, such as less than about 8% titanium is present, then the method 700 may proceed, for example, to operation 720 as depicted by arrow 710B.

[0095] In some examples, the system 100 executing the method 700 determines whether a battery includes a relative and / or threshold amount of manganese and / or cobalt and / or nickel at operation 720. For example, the system 100 executing the method 700 may determine whether the battery includes more manganese than cobalt and more manganese than nickel. If the battery includes a relative amount manganese, such as more than cither cobalt or nickel, then the system may place the battery into the sortation group 725 as depicted by arrow 720A, and the system 100 may categorize the battery as a lithium manganese oxide battery. For example, the battery chemistry of lithium manganese oxide type batteries may be known and may include greater compositions with more manganese than either cobalt or nickel. Thus, in the event the battery includes more manganese than either cobalt or nickel, the system 100 executing the method 700 may categorize the battery as a lithium manganese oxide type battery. The system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium manganese oxide type batteries. In this way, the system 100 executing the method 700 may compile all lithium manganese oxide type batteries and may subsequently recycle the batteries together as a batch. If the battery does not include a threshold amount of manganese at operation 720, or includes less manganese than either cobalt or nickel, the method 700 may proceed to operation 730 as depicted by arrow 720B.

[0096] In some examples, the system 100 executing the method 700 may determine whether a battery includes a threshold amount of phosphorus at operation 730. For example, at operation 730 the system 100 executing the method 700 may determine whether the battery includes greater than or equal to about 2% phosphorus. In various embodiments, the determination at operation 730 of the method 700 may be similar to or the substantially thesame as the determination made at operation 430 of the method 400. For example, the method 700 may determine whether a battery includes a threshold amount of phosphorus, such as between 5% to 0.5% at operation 730. If the battery includes a threshold amount of phosphorus, such as greater than or equal to about 2% phosphorus, then the system may place the battery into the sortation group 735 as depicted by arrow 730A, and the system 100 may categorize the battery as a lithium ferrous phosphate or lithium iron phosphate battery. A threshold value may reduce the number of false positives. For example, the battery chemistry of lithium ferrous phosphate or lithium iron phosphate type batteries may be known and may include greater than or equal to about 1% phosphorus. A threshold value greater than 1% phosphorous may limit false positives of lithium ferrous phosphate or lithium iron phosphate batteries. Thus, in the event the battery includes greater than or equal to about 2% phosphorus, the system 100 executing the method 700 may categorize the battery as a lithium ferrous phosphate or lithium iron phosphate type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium ferrous phosphate or lithium iron phosphate type batteries. In this way, the system 100 executing the method 700 may compile all lithium ferrous phosphate or lithium iron phosphate type batteries and may subsequently recycle the batteries together as a batch. If the battery does not include a threshold amount of phosphorous at operation 730, such as less than about 2% phosphorus, then the method 700 may proceed to operation 740 as depicted by arrow 730B.

[0097] In some examples, the system 100 executing the method 700 may determine whether a battery includes a relative amount of cobalt at operation 740. For example, the system 100 may determine whether a battery includes more cobalt than a factor X multiplied by the amount of nickel the battery includes. If the battery includes a relative amount of cobalt, such as more cobalt than X multiplied by the amount of nickel, where X is greater than 1, then system may place the battery into the sortation group 745 as depicted by arrow 740A, and the system 100 may categorize the battery as a lithium cobalt oxide battery. For example, the battery chemistry of lithium cobalt oxide type batteries may be known and may include more cobalt than a factor multiplied by the amount of nickel. In some embodiments, the factor X is greater than one. In some embodiments, the factor may be between 1 .5 and 2. Thus, in the event the battery includes more cobalt than the factormultiplied by the amount of nickel, the system 100 may categorize the battery as a lithium cobalt oxide type battery according to the method 700. The system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium cobalt oxide type batteries. In this way, the system 100 executing the method 700 may compile all lithium cobalt oxide type batteries and may subsequently recycle the batteries together as a batch. If the battery does not include a relative amount of cobalt greater than a factor X multiplied by the amount of nickel at operation 740, then the method 700 may proceed to operation 750 as depicted by arrow 740B.

[0098] In some examples, the system 100 executing the method 700 may determine whether a battery includes a threshold and / or a relative amount of manganese at operation 750. For example, the system 100 executing the method 700 at operation 750 may determine whether a battery includes greater than or equal to about 2% manganese, and whether the battery includes an amount of manganese at least half the concentration of cobalt, but not more than double the concentration of cobalt. If the battery includes a threshold amount of manganese, such as greater than or equal to about 2% manganese, and the amount of manganese is at least half the concentration of cobalt, but not more than double the concentration of cobalt, then the system may place the battery into the sortation group 755 as depicted by arrow 750A, and the system 100 may categorize the battery as a lithium nickel-manganese-cobalt battery. A threshold value may reduce the number of false positives. For example, the battery chemistry of lithium nickel-manganese-cobalt type batteries may be known and may include greater than or equal to about 0.3% manganese. A threshold value of manganese greater than 0.3% may reduce the number of false positives of lithium nickel-manganese-cobalt batteries. Thus, in the event the battery includes greater than or equal to about 2% manganese, and the concentration of manganese is at least half the concentration of cobalt, but not more than double the concentration of cobalt, and lithium manganese oxide batteries have already been identified, then the system 100 executing the method 700 may categorize the battery as a lithium nickel-manganese-cobalt type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium nickel-manganese-cobalt type batteries. In this way, the system 100 executing the method 700 may compile all lithium nickel-manganese-cobalt type batteries and maysubsequently recycle the batteries together as a batch. If the battery does not include a threshold or relative amount of manganese at operation 750, such as less than about 2% manganese is present, then the method 700 may proceed to operation 760 as depicted by arrow 75 OB.

[0099] In some examples, the system 100 executing the method 700 may determine whether a battery includes one or more of a threshold or relative amount of nickel at operation 760. For example, at operation 760, the system 100 executing the method 700 may determine whether the battery includes greater than or equal to about 6% nickel, whether the battery includes more cobalt than four times the amount of manganese, and / or whether the battery includes greater than or equal to about 2% cobalt. If the battery includes a threshold amount of nickel, such as greater than or equal to about 6% nickel, then the system may place the battery into the sortation group 765 as depicted by arrow 760A, and the system 100 may categorize the battery as a lithium nickcl-cobalt-aluminum oxide battery. A threshold value of nickel greater than 4% may reduce the number of false positives of lithium nickel-cobalt-aluminum batteries. For example, the battery chemistry of lithium nickel-cobalt-aluminum oxide type batteries may be known and may include greater than or equal to about 4% nickel. Thus, in the event the battery includes greater than or equal to about 6% nickel, and all NMC batteries have already been identified, then the system 100 executing the method 700 may categorize the battery as a lithium nickel-cobalt- aluminum oxide type battery and may reduce the risk of a false positive. If the battery includes a relative amount of cobalt, such as greater than four times the amount of manganese, then the system may place the battery into the sortation group 765 as depicted by arrow 760 A. For example, the battery chemistry of a lithium nickel-cobalt-aluminum oxide battery may be known and may include a composition with more cobalt than four times the amount of manganese. Thus, in the event the battery includes more cobalt than four times the amount of manganese, the system 100 may categorize the battery as a lithium nickel-cobalt-aluminum oxide type battery according to the method 700. If the battery includes a threshold amount of cobalt, such as greater than or equal to about 2% cobalt, then the system may place the battery into the sortation group 765 as depicted by arrow 760A, and the system 100 may categorize the battery as a lithium nickel-cobalt-aluminum oxide battery. A threshold value of cobalt greater than 1 % may reduce the number of falsepositives of lithium nickel-cobalt-aluminum batteries. For example, the battery chemistry of lithium nickel-cobalt-aluminum oxide type batteries may be known and may include greater than or equal to about 1% cobalt. Thus, in the event the battery includes greater than or equal to about 2% cobalt, and all NMC batteries have already been identified, then the system 100 executing the method 700 may categorize the battery as a lithium nickel-cobalt- aluminum oxide type battery and may reduce the risk of a false positive. If the battery identifies as a lithium nickel-cobalt-aluminum oxide battery from at least one of the threshold or relative determinations of the method 700, then the system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium nickel-cobalt-aluminum oxide batteries. In this way, the system 100 executing the method 700 may compile all lithium nickel-cobalt-aluminum oxide type batteries and may subsequently recycle the batteries together as a batch. If at operation 760, a battery does not include a threshold amount of nickel, such as less than about 6% nickel, and / or a concentration of cobalt less than four times the amount of manganese, and / or docs not include a threshold amount of cobalt, such as less than 2% cobalt, then the method 700 may proceed to operation 770 as depicted by arrow 760B.

[0100] In some examples, the system 100 executing the method 700 may determine whether a battery includes a threshold amount of vanadium at operation 770. For example, the system 100 executing the method 700 may determine whether a battery includes greater than or equal to about 5% vanadium at operation 770. In various embodiments, operation 770 of the method 700 may make a similar or substantially the same determination made at operation 470 of the method 400, and determine whether a battery includes a threshold amount of vanadium, such as between 10% to 1%. If the battery includes a threshold amount of vanadium, such as greater than or equal to about 5% vanadium, then the system may place the battery into the sortation group 775 as depicted by arrow 770A, and the system 100 may categorize the battery as a lithium metal battery. A threshold amount of vanadium greater than 4% may reduce the number of false positives of lithium metal batteries. For example, the battery chemistry of lithium metal type batteries may be known and may include greater than or equal to about 4% vanadium. A threshold value of greater than 4% vanadium may reduce the number of false positives of lithium metal batteries. Thus, in the event the battery includes greater than or equal to about 5% vanadium, the system 100executing the method 700 may categorize the battery as a lithium metal type battery and may reduce the risk of a false positive. The system 100 may sort the battery to a predetermined location where the method 700 sorts all batteries identified as lithium metal type batteries. In this way, the system 100 executing the method 700 may compile at least some lithium metal type batteries and may subsequently recycle the batteries together as a batch. If a battery does not include a threshold amount of vanadium at operation 770, such as less than about 5% vanadium, then the method 700 may proceed to operation 780 as depicted by arrow 770B.

[0101] In some embodiments, in the event a battery proceeds to sortation group 780, the system 100 executing the method 700 may categorize the battery as “other”, which may include batteries of an unknown or a non-conforming type. The system 100 executing the method 700 may include individual inspection of the batteries categorized as other. Optionally, after individual inspection makes an elemental identification, the system 100 executing the method 700 may add a determination operation, similar to operations 710, 720, 730, 740, 750, 760, and 770 to the disclosed processes, methods, and devices. For example, the system 100 executing the method 700 may add additional determination operations to the method 700 once the system 100 executing the method 700 determines more known battery chemistries. Likewise, after the system 100 makes an elemental identification, the system 100 executing the method 700 may add a sortation group, similar to sortation groups 715, 725, 735, 745, 755, 765, 775, and 780 to the disclosed processes, methods, and devices. For example, the system 100 executing the method 700 may include additional sortation groups or categorizations to the method 700 after determining more known battery chemistries.

[0102] The system 100 executing the method 700 may base operations 710, 720, 730, 740, 750, 760, and 770 on information corresponding to known battery chemistries. FIG. 7 depicts one embodiment of detection limits based on threshold values and relative amounts of elements. The system, devices and methods described herein may be structured such that not every operation 710, 720, 730, 740, 750, 760, and 770 is included and / or the operations are ordered differently or one or more performed in parallel. Additionally, the operations 710, 720, 730, 740, 750, 760, and 770 are examples of possible determinations, but are notlimiting in any way. For example, the system, devices and methods described herein may include determinations in addition to the operations 710, 720, 730, 740, 750, 760, and 770.

[0103] The system, devices and methods described herein may be structured such that not every sortation group, including 715, 725, 735, 745, 755, 765, 775, and 780 is included. Additionally, the sortation groups 715, 725, 735, 745, 755, 765, 775, and 780 are examples of possible sortation groups, but are not limiting in any way. For example, the system, devices and methods described herein may include sortation groups in addition to the sortation groups 715, 725, 735, 745, 755, 765, 775, and 780.

[0104] FIG. 8 depicts a periodic table annotated with element detection guidelines for an embodiment of a sensor 115. In this example, the sensor 115 is a radiometric sensor, more specifically a PGNAA sensor. Other embodiments of a sensor 1 15 may have different detection limits. Other examples of a PGNAA sensor may have different detection limits.

[0105] FIG. 8 depicts a detectability of an element, including an excellent detectability, corresponding to a detectability of less than 0.01% of the element, a very good detectability, corresponding to a detectability from 0.01% to 0.1% of the element, a good detectability, corresponding to a detectability of 0.1% to 0.3% of the element, a moderate detectability, corresponding to a detectability of 0.3% to l.% of the element, a nominal detectability, corresponding to a detectability of 1% to 3% of the element, a minimal detectability, corresponding to a detectability of 3% to 10% of the element, a none detectability, corresponding to a detectability of greater than 10% of the element, and an unknown detectability, corresponding to a detectability that is unknown for the element.

[0106] FIG. 8 depicts the detectability of chlorine, scandium, titanium, nickel, cadmium, mercury, samarium, gadolinium, dysprosium, and holmium as excellent.

[0107] FIG. 8 depicts the detectability of sulfur, argon, vanadium, chromium, manganese, iron, cobalt, copper, krypton, rhodium, silver, indium, xenon, hafnium, iridium, gold, neodymium, europium, erbium, ytterbium, and plutonium as very good.

[0108] FIG. 8 depicts the detectability of hydrogen, nitrogen, sodium, aluminum, silicon, potassium, calcium, gallium, selenium, yttrium, cesium, lanthanum, wolfram, rhenium, osmium, platinum, praseodymium, and thulium as good.

[0109] FIG. 8 depicts the detectability of lithium, beryllium, magnesium, phosphorous, zinc, arsenic, molybdenum, tellurium, iodine, barium, tantalum, lead, cerium, terbium, lutetium, thorium, and uranium as moderate.

[0110] FIG. 8 depicts the detectability of carbon, germanium, bromine, strontium, zirconium, ruthenium, palladium, antimony, and thallium as nominal.

[0111] FIG. 8 depicts the detectability of neon, rubidium, niobium, technetium, and tin as minimal.

[0112] FIG. 8 depicts the detectability of helium, boron, carbon, oxygen, fluorine, bismuth, and promethium as none.

[0113] FIG. 8 depicts the detectability of remaining elements as unknown.

[0114] FIG. 9 is a simplified block diagram of components of a computing system 900 which an embodiment of the disclosed system may include. For example, the processing element 902 and the memory component 908 may be located at one or in several computing systems 900. This disclosure contemplates any suitable number of such computing systems 900. For example, the disclosed systems may include a processor which may be a desktop computing system, a mainframe, a blade, a mesh of computing systems 900, a laptop or notebook computing system 900, a tablet computing system 900, an embedded computing system 900, a system-on-chip, a single-board computing system 900, or a combination of two or more of these. Where appropriate, a computing system 900 may include one or more computing systems 900; be unitary or distributed; span multiple locations; span multiple machines; span multiple data centers; or reside in a cloud, which may include one or more cloud components in one or more networks. A computing system 900 may include one or more processing elements 902, an input / output I / O interface 904, one or more external devices 912, one or more memory components 608, and a network interface 910. Each of the various components may be in communication with one another through one or more buses or communication networks, such as wired or wireless networks. The components in FIG. 9 are exemplary only. In various examples, the computing system 900 may include additional components and / or functionality not shown in FIG. 9.

[0115] The processing element 902 may be any type of electronic device capable of processing, receiving, and / or transmitting instructions. For example, the processing element902 may be a central processing unit, microprocessor, processor, or microcontroller. Additionally, it should be noted that some components of the computing system 900 may be controlled by a first processing element 902 and other components may be controlled by a second processing element 902, where the first and second processing elements may or may not be in communication with each other. roii6] The I / O interface 904 allows a user to enter data in to computing system 900, as well as provides an input / output for the computing system 900 to communicate with other devices or services. The I / O interface 904 can include one or more input buttons, touch pads, touch screens, and so on.

[0117] The external device 912 are one or more devices that can be used to provide various inputs to the computing systems 600, e.g., mouse, microphone, keyboard, trackpad, sensing element (e.g., a thermistor, humidity sensor, light detector, etc. The external devices 912 may be local or remote and may vary as desired. In some examples, the external devices 912 may also include one or more additional sensors.

[0118] The memory components 908 are used by the computing system 900 to store instructions for the processing element 902 such as determinations for known battery compositions for battery chemistries, or threshold values for determinations of battery type, such as the microclimate model 128, the application 402 and / or user interface 404, as well as store data, such as regional weather data 130, microclimate conditions, environmental characteristics, user preferences, alerts, etc. The memory components 908 may be, for example, magneto-optical storage, read-only memory, random access memory, erasable programmable memory, flash memory, or a combination of one or more types of memory components.

[0119] The network interface 910 provides communication to and from the computing system 900 to other devices. The network interface 910 includes one or more communication protocols, such as, but not limited to Wi-Fi, Ethernet, Bluetooth, etc. The network interface 910 may also include one or more hardwired components, such as a Universal Serial Bus (USB) cable, or the like. The configuration of the network interface 910 depends on the types of communication desired and may be modified to communicate via Wi-Fi, Bluetooth, etc.

[0120] The display 906 provides a visual output for the computing system 900 and may be varied as needed based on the device. The display 906 may be configured to provide visual feedback to the process 100 and may include a liquid crystal display screen, light emitting diode screen, plasma screen, or the like. In some examples, the display 906 may be configured to act as an input element for the process 100 through touch feedback or the like.

[0121] Embodiments of the system 100 may include computer system 900 to interface with one or more of the system 100 components. In some embodiments, the computer system 900 may configure the singulation device. For example, the computer system 900 may configure the singulation device to control a distance between each battery of a stream of mixed batteries. In some embodiments, computer system 900 may configure the sensor device 120. For example, a computer system 900 may configure the sensor device 120 to execute a different method based on known battery compositions. In some embodiments, a computer system 900 may configure the sorting device 120. For example, the computer system 900 may configure the sorting device 120 to add new sortation groups. In some embodiments, a user may interface with the computer system 900 to configure the system 100 or its components, or to direct a method executed by the system 100. In some embodiments, a computer system 900 may be automated to configure the system 100 and / or its components, and / or execute a method based on communication with the system 100 and its components.

[0122] It is intended that all matter contained in the above description or shown in the accompanying drawings shall be interpreted as illustrative only and not limiting. Changes in detail or structure can be made without departing from the spirit of the present disclosure as defined in the appended claims. In methodologies directly or indirectly set forth herein, operations can be performed in any order, unless explicitly claimed otherwise or a specific order is inherently necessitated by the claim language. Additionally, some of the operations described can be skipped or not included in the process 100.

[0123] The description of certain embodiments included herein is merely exemplary in nature and is in no way intended to limit the scope of the disclosure or its applications or uses. In the included detailed description of embodiments of the present systems and methods, reference is made to the accompanying drawings which form a part hereof, and which are shown by way of illustration specific to embodiments in which the describedsystems and methods may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice presently disclosed systems and methods, and it is to be understood that other embodiments may be utilized, and that structural and logical changes may be made without departing from the spirit and scope of the disclosure. Moreover, for the purpose of clarity, detailed descriptions of certain features will not be discussed when they would be apparent to those with skill in the art so as not to obscure the description of embodiments of the disclosure. The included detailed description is therefore not to be taken in a limiting sense, and the scope of the disclosure is defined only by the appended claims.

[0124] From the foregoing it will be appreciated that, although specific embodiments of the invention have been described herein for purposes of illustration, various modifications may be made without deviating from the spirit and scope of the invention.

[0125] The particulars shown herein are by way of example and for purposes of illustrative discussion of the preferred embodiments of the present disclosure and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of various embodiments of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the invention, the description taken with the drawings and / or examples making apparent to those skilled in the art how the several forms of the invention may be embodied in practice.

[0126] As used herein and unless otherwise indicated, the terms “a” and “an” are taken to mean “one”, “at least one” or “one or more”. Unless otherwise required by context, singular terms used herein shall include pluralities and plural terms shall include the singular.

[0127] Unless the context clearly requires otherwise, throughout the description and the claims, the words ‘comprise’, ‘comprising’, and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to”. Words using the singular or plural number also include the plural and singular number, respectively. Additionally, the words “herein,” “above,” and “below” and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of the application.

[0128] All relative, directional, and ordinal references (including top, bottom, side, front, rear, first, second, third, and so forth) are given by way of example to aid the reader’ s understanding of the examples described herein. They should not be read to be requirements or limitations, particularly as to the position, orientation, or use unless specifically set forth in the claims. Connection references (e.g., attached, coupled, connected, joined, and the like) are to be construed broadly and may include intermediate members between a connection of elements and relative movement between elements. As such, connection references do not necessarily infer that two elements are directly connected and in fixed relation to each other, unless specifically set forth in the claims.

[0129] Of course, it is to be appreciated that any one of the examples, embodiments or processes described herein may be combined with one or more other examples, embodiments and / or processes or be separated and / or performed amongst separate devices or device portions in accordance with the present systems, devices and methods.

[0130] Finally, the above discussion is intended to be merely illustrative of the present system and should not be construed as limiting the appended claims to any particular embodiment or group of embodiments. Thus, while the present system has been described in particular detail with reference to exemplary embodiments, it should also be appreciated that numerous modifications and alternative embodiments may be devised by those having ordinary skill in the art without departing from the broader and intended spirit and scope of the present system as set forth in the claims that follow. Accordingly, the specification and drawings are to be regarded in an illustrative manner and are not intended to limit the scope of the appended claims.

[0131] As used herein, the terms “about” and “substantially”, when referring to a value or to an amount of a composition, mass, weight, temperature, time, volume, concentration, percentage, etc., are meant to encompass variations of in some embodiments ±20%, in some embodiments ±10%, in some embodiments ±5%, in some embodiments ±1%, in some embodiments ±0.5%, and in some embodiments ±0.1% from the specified amount, as such variations are appropriate to perform the disclosed methods or employ the disclosed compositions.

[0132] Every range of values (of the form, "from about a to about b," or, equivalently, "from approximately a to b," or, equivalently, "from approximately a-b" or, equivalently, "greater than about a and less than about b", for example) disclosed herein is to be understood to set forth every number and range encompassed within the broader range of values.

[0133] As used herein, the term “and / or” when used in the context of a listing of entities, refers to the entities being present singly or in combination. Thus, for example, the phrase “A, B, C, and / or D” includes A, B, C, and D individually, but also includes any and all combinations and subcombinations of A, B, C, and D.EXAMPLES

[0134] FIG. 10 depicts an example data plot 1000, which demonstrates example spectra emitted by batteries of different bulk chemistries as measured by the sensor device 115. The X-axis 1002 refers to channels of varying energy levels used by sensor device 115. The Y- axis 1004 refers to the measured number of counts detected by sensor device 115 at the corresponding energy level, i.e., channel. The example data plot 1000 demonstrates LFP, lead-acid, NiCd, and LCO batteries, which legend 1006 differentiates, emitting different eV spectra that distinguish and identify the batteries. The unique measured spectra allow the systems disclosed herein, such as the system 100, to execute the methods and processes disclosed herein to identify a battery from a mixed stream of batteries.

[0135] FIG. 1 1 depicts an example data plot 1 100, which shows the spectra emitted by the same battery in two different orientations, 3A and 3B, as measured by sensor device 115. As differentiated in legend 1106, 3A refers the battery in an original position, and 3B refers to the battery rotated 90° from its original position. The X-axis 1102 refers to channels of varying energy levels used by sensor device 115. The Y-axis 1104 refers to the measured number of counts detected by sensor device 115 at the corresponding energy level, i.e., channel. The example data plot 1100 demonstrates the repeatability and stability of measurements made by sensor device 115, as the data points of 3A and 3B substantially overlap with each other. The example data plot 1100 also demonstrates that the orientation of the battery does not significantly affect the energy spectra measured by sensor device 115.

Claims

CLAIMSWhat is claimed is:

1. A method for identifying and sorting batteries, the method comprising: receiving a stream of mixed batteries; spatially separating the stream of mixed batteries into a plurality of batteries; directing a non-destructive beam of neutrons at a battery of a plurality of batteries; sensing an electromagnetic signature emitted in response to the non-destructive beam of neutrons directed at the battery; analyzing the electromagnetic signature to determine a composition of the battery; and sorting the battery to a location based on the composition.

2. The method of claim 1, wherein the method is at least partially automated.

3. The method of claim 1, wherein the stream of mixed batteries is spatially separated a sufficient distance to prevent compromising the electromagnetic signature emitted in response to the non-destructive beam of neutrons directed at the battery.

4. The method of claim 1 , wherein the stream of mixed batteries is spatially separated into a single file line.

5. The method of claim 1, wherein a battery type of the battery is determined by an absolute measurement of at least an element of the composition.

6. The method of claim 1, wherein a battery type is determined by a composition of an element of the battery relative to one or more of a composition of a plurality of other elements of the battery.

7. The method of claim 1, wherein a battery type is determined by a measurement of an element of the composition and a threshold value.

8. The method of claim 7, wherein the threshold value is chosen to minimize or prevent false positives.

9. The method of claim 1, wherein the battery is determined as a lithium titanate battery if the composition includes at least 2% titanium.

10. The method of claim 1, wherein the battery is determined as a lithium manganese oxide battery if the composition includes at least 3.5% manganese and less than or equal to 3.5% cobalt.

11. The method of claim 1, wherein the battery is determined as a lithium iron phosphate battery if the composition includes at least 1% phosphorous.

12. The method of claim 1, wherein the battery is determined as a lithium cobalt oxide battery if the composition includes at least 10% cobalt.

13. The method of claim 1, wherein the battery is determined as a lithium nickel manganese cobalt oxide battery if the composition includes at least 0.3% manganese.

14. The method of claim 1, wherein the battery is determined as a lithium nickel cobalt aluminum oxide battery if the composition includes at least 4% nickel.

15. The method of claim 1, wherein the battery is determined as a lithium metal battery if the composition includes at least 4% vanadium.

16. The method of claim 1, wherein the battery is determined as a lithium titanate battery if the composition includes at least 1% to at least 10% titanium.

17. The method of claim 1, wherein the battery is determined as a lithium manganese oxide battery if the composition includes: a composition of manganese at least 0.1% to at least 10% manganese; and a composition of cobalt less than or equal to 3.5%.

18. The method of claim 1, wherein the battery is determined as a lithium manganese oxide battery if the composition includes more manganese than cobalt or nickel.

19. The method of claim 1, wherein the battery is determined as a lithium iron phosphate battery if the composition includes at least 0.5% to at least 5% phosphorous.

20. The method of claim 1, wherein the battery is determined as a lithium manganese oxide battery if the composition includes at least 7.5% manganese and less than or equal to 2% cobalt.

21. The method of claim 1, wherein the battery is determined as a lithium cobalt oxide battery if the composition includes at least 5% to at least 20% cobalt.

22. The method of claim 1, wherein the battery is determined as a lithium cobalt oxide battery if the composition includes: a composition of cobalt greater than a composition of nickel multiplied by a factor, wherein the factor is greater than 1.

23. The method of claim 1, wherein the battery is determined as a lithium cobalt oxide battery if the composition includes: a composition of cobalt greater than a composition of nickel multiplied by a factor, wherein the factor is equal to or between 1.5 and 2.

24. The method of claim 1, wherein the battery is determined as a lithium nickel manganese cobalt oxide battery if the composition includes at least 0.05% to at least 5% manganese.

25. The method of claim 1 , wherein the battery is determined as a lithium nickel manganese cobalt oxide battery if the composition includes: a composition of manganese greater than or about equal to 0.3%; and a composition of cobalt, wherein the composition of manganese is at least half the composition of cobalt, and the composition of manganese is less than double the composition of cobalt.

26. The method of claim 1, wherein the battery is determined as a lithium nickel cobalt aluminum oxide battery if the composition includes at least 1% to at least 10% nickel.

27. The method of claim 1, wherein the battery is determined to be a lithium nickel cobalt aluminum oxide battery if the composition includes one or more of a composition of nickel greater than or equal to 4%, a composition of cobalt more than two times a composition of manganese, or a composition of cobalt greater than or equal to 1%.

28. The method of claim 1, wherein the battery is determined to be a lithium nickel cobalt aluminum oxide battery if the composition includes one or more of a composition of nickel greater than or equal to 6%, a composition of cobalt more than four times a composition of manganese, or a composition of cobalt greater than or equal to 2%.

29. The method of claim 1, wherein the battery is determined as a lithium metal battery if the composition includes at least 1% to at least 10% vanadium.

30. The method of claim 1, wherein the battery is determined as an other battery if the composition does not conform to a known composition of a battery type.

31. The method of claim 30, further comprising individually inspecting the other battery to identify the battery type.

32. The method of claim 1, wherein the battery is determined as a lead acid battery if the composition includes at least 0.5% lead.

33. The method of claim 1, wherein the battery is determined as a NiCd battery if the composition includes at least 0.5% cadmium.

34. A battery identification and sortation system comprising: a separator configured to spatially separate batteries of a stream of mixed batteries; a sensor configured to detect an electromagnetic signature from a battery of the stream of mixed batteries, wherein the electromagnetic signature is emitted in response to a non-destructive beam of neutrons bombarding the battery; and a sorting device configured to sort the battery to a predetermined location based on the electromagnetic signature.

35. The system of claim 34, wherein the sorting device comprises a deflector bar.

36. The system of claim 34, wherein the sensor comprises a radiometric sensor.

37. The system of claim 34, wherein the sensor comprises at least one of a prompt-gamma neutron activation analysis sensor, a pulsed fast thermal neutron activation sensor.

38. The system of claim 34, further comprising a computer system.

39. The system of claim 38, wherein the computer system configures at least one of the separator, the sensor, or the sorting device.

40. A sensor device comprising: an emitter configured to emit or produce a plurality of non-destructive neutrons; a director configured to direct the plurality of non-destructive neutrons at a battery; a receiver configured to measure an electromagnetic signature from the battery; and a processor configured to determine a composition of the battery based on the electromagnetic signature.

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