Determining the intrinsic viscosity and Huggins constant of an unknown sample

Abstract

The present disclosure describes a computer-implemented method, system, and computer program product for determining the intrinsic viscosity and Huggins constant of an unknown sample. In one embodiment, the method, system, and computer program product includes receiving specific viscosity values ​​over time from a viscometer corresponding to a series of aliquots of an unknown sample injected into an instrument chain, the instrument chain including the viscometer, calculating a total mass of each of the aliquots, calculating a first intermediate viscosity value for each of the aliquots, calculating a second intermediate viscosity value for each of the aliquots, and fitting the total mass, the first intermediate viscosity value, and the second intermediate viscosity value to a fitting to yield a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample.

Description

[Technical Field]

[0001] (Priority Claim) This application claims priority to U.S. Patent Application No. 18 / 098,107, filed January 17, 2023, which is a continuation-in-part of U.S. Patent Application No. 16 / 840,478, filed April 6, 2020. [Background technology]

[0002] The present disclosure relates to samples, and more particularly to determining the intrinsic viscosity and Huggins constant of an unknown sample. Summary of the Invention [Means for solving the problem]

[0003] This disclosure describes a computer-implemented method, system, and computer program product for determining the intrinsic viscosity and Huggins constant of an unknown sample. In exemplary embodiments, the computer-implemented method, system, and computer program product include: (1) detecting, by a computer system, concentration detector signal values ​​c over time from a concentration detector; meas (t) receiving, by a computer system, specific viscosity values ​​over time, η, from the viscometer, where the concentration detector signal values ​​correspond to concentration values ​​of a series of aliquots of the unknown sample injected into an instrument chain, the instrument chain including a concentration detector; and (2) receiving, by a computer system, specific viscosity values ​​over time, η, from the viscometer. sp (3) receiving, by a computer system, specific viscosity values ​​corresponding to the series of aliquots, the instrument chain further including a viscometer; and (4) determining by a computer system the total mass m of each of the aliquots. i is the received concentration detector signal value c corresponding to each of the aliquots. meas (4) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots as a first integral function of (t); sp The first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) i(5) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots; sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) i (6) performing a set of logical operations to calculate the total mass m of each of the aliquots by the computer system; i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K h and a third integral function to yield a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample. [Brief explanation of the drawings]

[0004] [Figure 1A] 1 depicts a flowchart in accordance with an example embodiment. [Figure 1B] 1 depicts a block diagram in accordance with an illustrative embodiment; [Figure 2] 1 depicts a flowchart in accordance with an example embodiment. [Figure 3] 1 depicts a graph according to one embodiment. [Figure 4A] 1 depicts a graph according to an embodiment. [Figure 4B] 1 depicts a graph according to an embodiment. [Figure 4C] 1 depicts data according to an embodiment. [Figure 5A] 1 depicts a graph according to an embodiment. [Figure 5B] 1 depicts a graph according to an embodiment. [Figure 5C] 1 depicts data according to an embodiment. [Figure 6A] 1 depicts a graph according to an embodiment. [Figure 6B]1 depicts a graph according to an embodiment. [Figure 6C] 1 depicts data according to an embodiment. [Figure 7] 1 depicts a graph according to one embodiment. [Figure 8] 1 illustrates a computer system in accordance with an exemplary embodiment. [Figure 9A] 1 depicts a flowchart in accordance with an example embodiment. [Figure 9B] 1 depicts a block diagram in accordance with an illustrative embodiment; [Figure 10A] 1 depicts a flowchart in accordance with an example embodiment. [Figure 10B] 1 depicts a block diagram in accordance with an illustrative embodiment; DETAILED DESCRIPTION OF THE INVENTION

[0005] This disclosure describes a computer-implemented method, system, and computer program product for determining the intrinsic viscosity and Huggins constant of an unknown sample. In exemplary embodiments, the computer-implemented method, system, and computer program product include: (1) detecting, by a computer system, concentration detector signal values ​​c over time from a concentration detector; meas (t) receiving, by a computer system, specific viscosity values ​​over time, η, from the viscometer, where the concentration detector signal values ​​correspond to concentration values ​​of a series of aliquots of the unknown sample injected into an instrument chain, the instrument chain including a concentration detector; and (2) receiving, by a computer system, specific viscosity values ​​over time, η, from the viscometer. sp (3) receiving, by a computer system, specific viscosity values ​​corresponding to the series of aliquots, the instrument chain further including a viscometer; and (4) determining by a computer system the total mass m of each of the aliquots. i is the received concentration detector signal value c corresponding to each of the aliquots. meas (4) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots as a first integral function of (t); spThe first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) i (5) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots; sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) i (6) performing a set of logical operations to calculate the total mass m of each of the aliquots by the computer system; i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K h and a third integral function to yield a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample.

[0006] In one embodiment, the concentration detector is one of a differential refractive index detector (dRI), an ultraviolet absorption detector, a visible absorption detector, an infrared absorption detector, a fluorescence detector, and an evaporative light scattering detector (ELSD). In a particular embodiment, the concentration detector is a differential refractive index detector (dRI). In one embodiment, the viscometer is a differential viscometer. In one embodiment, the instrument chain includes a heat transport measurement device. In one embodiment, the instrument chain includes a mass flow meter.

[0007] In one embodiment, a computer-implemented method, system, and computer program product allows for calculating the intrinsic viscosity and Huggins constant of an unknown sample via a concentration detector connected in series with a concentration detector. In one embodiment, a computer-implemented method, system, and computer program product allows for calculating the intrinsic viscosity and Huggins constant of a small amount of unknown sample via a concentration detector connected in series with a concentration detector.

[0008] definition particle Particles can be components of an aliquot of a liquid sample. Such particles can be molecules, nanoparticles, virus-like particles, liposomes, emulsions, bacteria, and colloids of various types and sizes. These particles can range in size from nanometers to microns.

[0009] Analysis of polymer or particle species in solution Analysis of macromolecular or particle species in solution can be accomplished by preparing the sample in an appropriate solvent and then injecting an aliquot thereof into a separation system such as a liquid chromatography (LC) column or field flow fractionation (FFF) channel, where different particle species contained within the sample are separated into their various components. Generally, once separated based on size, mass, or column affinity, the sample can be subjected to analysis by light scattering, refractive index, ultraviolet absorbance, electrophoretic mobility, and viscosity response.

[0010] Concentration Detector Refractive Index Detector A differential refractive index detector (dRI), or differential refractometer, or refractive index detector (RI or RID), is a detector that measures the refractive index of an analyte relative to a solvent. They are often used as detectors for high-performance liquid chromatography and size-exclusion chromatography. dRIs can detect substances with refractive indices different from those of the solvent, but because of their low sensitivity, they are considered general-purpose detectors. When light leaves one material and enters another, it bends or refracts. The refractive index of a material is a measure of how much light bends as it enters.

[0011] A differential refractive index detector contains a flow cell with two sections, one for the sample and one for the reference solvent. The dRI measures the refractive index of both components. When only the solvent passes through the sample components, the measured refractive index of both components is the same, but when the analyte passes through the flow cell, the two measured refractive indices are different. This difference appears as a peak in the chromatogram. Differential refractive index detectors are often used for the analysis of polymer samples in size exclusion chromatography. The dRI can output a concentration detector signal value that corresponds to the concentration value of the sample.

[0012] UV-visible spectroscopy Ultraviolet-visible spectroscopy or ultraviolet-visible spectrophotometry (UV-Vis or UV / Vis) refers to absorption or reflectance spectroscopy in the ultraviolet-visible spectral region. UV-visible detectors / UV-visible spectrophotometers use light in the visible and adjacent ranges; absorption or reflectance in the visible range directly affects the perceived color of the chemicals involved, and it is in this region of the electromagnetic spectrum that atoms and molecules undergo electronic transitions. Such absorption spectroscopy measures the transition from a ground state to an excited state. UV-visible detectors / UV-visible spectrophotometers measure the intensity of light (I) passing through a sample, which is then compared to the intensity of the light before passing through the sample (I o ) where the ratio I / I o is called transmittance and is usually expressed as a percentage (%T). A is the absorbance A, Based on transmittance as A = -log(%T / 100%).

[0013] The UV-Visible spectrophotometer can also be configured to measure reflectance, where the spectrophotometer measures the intensity of light reflected from a sample (I) and correlates it with the intensity of light reflected from a reference material (I o ) compared to the ratio I / I o is called reflectance and is usually expressed as a percentage (%R). The ultraviolet absorption detector can output a concentration detector signal value that corresponds to the concentration value of the sample.

[0014] viscometer A capillary bridge viscometer (VIS) is an instrument used to measure the specific viscosity of a solute in a suitable solvent. The specific viscosity is expressed as η sp =η / η o is defined as -1, where η is the viscosity of the sample and η o is the viscosity of the solvent. When a sample is introduced into the bridge viscometer, a pressure transducer generates a signal indicative of the pressure difference. This pressure difference, combined with the predetermined internal pressure of the system, is used to calculate the specific viscosity of the sample. Specific viscosity is useful for determining molecular parameters of polymers, including molar mass and hydrodynamic radius.

[0015] The differential transducer in a capillary bridge viscometer measures the differential pressure developed across the fluid arms. The instrument continuously measures the differential pressure value while flowing fluid through the system. When pure solvent flows through the system and the bridge is balanced, the measured differential pressure should be zero. Impurities in the solvent, undissolved air bubbles, electrical noise, or minute leaks in the piping can cause unwanted noise in the differential pressure measurement, which is ultimately used to determine specific viscosity.

[0016] Current Technology Current technology can calculate the intrinsic viscosity and Huggins constant of large amounts of unknown samples. However, such large amounts of sample may not be practical or cost-effective for certain applications, such as pharmaceutical formulation of antibody drugs. In the early stages of pharmaceutical formulation / drug discovery, proteins may be produced in small quantities and at relatively low concentrations (<10 mg / ml). When drugs are formulated for clinical use, proteins may have high concentrations (100-200 mg / ml).

[0017] It is necessary to calculate the intrinsic viscosity and Huggins constant of a small amount of unknown sample via a concentration detector connected in series with the concentration detector.

[0018] Referring to FIG. 1A, in an exemplary embodiment, a computer-implemented method, system, and computer program product includes a computer system for detecting concentration detector signal values ​​c over time from a concentration detector. meas and an operation 110 receiving, by a computer system, specific viscosity values ​​over time η from the viscometer, where the concentration detector signal values ​​correspond to concentration values ​​of a series of aliquots of an unknown sample injected into an instrument chain, the instrument chain including a concentration detector. sp (t), the specific viscosity values ​​corresponding to the series of aliquots, and the instrument chain further includes a viscometer, and the computer system calculates the total mass m of each of the aliquots. i is the received concentration detector signal value c corresponding to each of the aliquots. meas 1. Operate 114, which performs a set of logical operations to calculate the received specific viscosity values ​​η corresponding to each of the aliquots by the computer system as a first integral function of (t). sp The first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) i , and the received specific viscosity values ​​η corresponding to each of the aliquots are calculated by the computer system using an operation 116 that performs a set of logical operations to calculate sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) iand the total mass m of each of the aliquots by the computer system. i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K h and a third integral function to perform an operation 120 that results in a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample.

[0019] In an exemplary embodiment, the computer system is a standalone computer system such as computer system 800 shown in FIG. 8, a network of distributed computers in which at least some of the computers are computer systems such as computer system 800 shown in FIG. 8, or a cloud computing node server such as computer system 800 shown in FIG. 8. In one embodiment, the computer system is computer system 800 as shown in FIG. 8 that performs analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 100. In one embodiment, the computer system is computer system / server 812 as shown in FIG. 8 that performs analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 100. In one embodiment, the computer system is processing unit 816 as shown in FIG. 8 that performs analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 100. In one embodiment, the computer system is a processor of an analytical instrument that performs analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 100.

[0020] In one embodiment, the computer system is computer system 800 as shown in FIG. 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 110, 112, 114, 116, 118, and 120. In one embodiment, the computer system is computer system / server 812 as shown in FIG. 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 110, 112, 114, 116, 118, and 120. In one embodiment, the computer system is processing unit 816 as shown in FIG. 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 110, 112, 114, 116, 118, and 120. In one embodiment, the computer system is a processor of an analytical instrument that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 110, 112, 114, 116, 118, and 120.

[0021] 1B, in an exemplary embodiment, a computer-implemented method, system, and computer program product includes a receiver 130, a calculator 132, and a fitter 134. In one embodiment, the receiver 130 receives concentration detector signal values ​​140, c, over time from a concentration detector 150. meas(t), where concentration detector signal values ​​140 correspond to concentration values ​​of a series of aliquots 154 of an unknown sample injected into an instrument chain, the instrument chain including a concentration detector 150. In one embodiment, receiver 130 includes a computer system, such as computer system 800 as shown in FIG. 8 , that performs operation 110. In one embodiment, receiver 130 includes a computer system, such as computer system / server 812 as shown in FIG. 8 , that performs operation 110. In one embodiment, receiver 130 includes a computer system, such as processing unit 816 as shown in FIG. 8 , that performs operation 110. In one embodiment, receiver 130 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8 , such that the computer system performs operation 110. In one embodiment, receiver 130 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8 , such that the computer system performs operation 110. In one embodiment, receiver 130 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 110. In one embodiment, receiver 130 performs operation 110 as computer software executing on a processor of receiver 130.

[0022] In one embodiment, the receiver 130 receives specific viscosity values ​​142, η, over time from the viscometer 152. sp(t), where the specific viscosity values ​​142 correspond to the series of aliquots 154, and the instrument chain further includes a viscometer 152. In one embodiment, the receiver 130 includes a computer system, such as computer system 800 as shown in FIG. 8, that performs the operation 112. In one embodiment, the receiver 130 includes a computer system, such as computer system / server 812 as shown in FIG. 8, that performs the operation 112. In one embodiment, the receiver 130 includes a computer system, such as processing unit 816 as shown in FIG. 8, that performs the operation 112. In one embodiment, the receiver 130 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs the operation 112. In one embodiment, the receiver 130 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs the operation 112. In one embodiment, receiver 130 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 112. In one embodiment, receiver 130 performs operation 112 as computer software executing on a processor of receiver 130.

[0023] In one embodiment, the calculator 132 calculates the total mass 160, m i the received concentration detector signal values ​​140, c corresponding to each of the aliquots. meas(t) as a first integral function of (t). In one embodiment, calculator 132 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 114. In one embodiment, calculator 132 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 114. In one embodiment, calculator 132 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 114. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 114. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 114. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 114. In one embodiment, calculator 132 performs operations 114 as computer software running on a processor of calculator 132 .

[0024] In one embodiment, the calculator 132 calculates a first intermediate viscosity value 162, Iη, for each of the aliquots. i the received specific viscosity values ​​142, η, corresponding to each of the aliquots sp(t) as a second integral function of (t). In one embodiment, calculator 132 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 116. In one embodiment, calculator 132 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 116. In one embodiment, calculator 132 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 116. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 116. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 116. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 116. In one embodiment, calculator 132 performs operations 116 as computer software running on a processor of calculator 132 .

[0025] In one embodiment, the calculator 132 calculates a second intermediate viscosity value 164, Iη, for each of the aliquots. i the received specific viscosity values ​​142, η, corresponding to each of the aliquots sp(t) as a third integral function of (t). In one embodiment, calculator 132 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 118. In one embodiment, calculator 132 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 118. In one embodiment, calculator 132 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 118. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 118. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 118. In one embodiment, calculator 132 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 118. In one embodiment, calculator 132 performs operations 118 as computer software running on a processor of calculator 132 .

[0026] In one embodiment, the fitter 134 measures the total mass 160, m i , the first intermediate viscosity value 162 of each of the aliquots, Iη i , and a second intermediate viscosity value 164, I2η, for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K hand a third integral function to yield a calculated intrinsic viscosity of the unknown sample 166 and a calculated Huggins constant of the unknown sample 168. In one embodiment, fitter 134 includes a computer system, such as computer system 800 as shown in FIG. 8 , that performs operation 120. In one embodiment, fitter 134 includes a computer system, such as computer system / server 812 as shown in FIG. 8 , that performs operation 120. In one embodiment, fitter 134 includes a computer system, such as processing unit 816 as shown in FIG. 8 , that performs operation 120. In one embodiment, fitter 134 is implemented as computer software that runs on a computer system, such as computer system 800 as shown in FIG. 8 , such that the computer system performs operation 120. In one embodiment, fitter 134 is implemented as computer software that runs on a computer system, such as computer system / server 812 as shown in FIG. 8 , such that the computer system performs operation 120. In one embodiment, fitter 134 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 120. In one embodiment, fitter 134 performs operation 120 as computer software executing on a processor of fitter 134.

[0027] (Total mass calculation) In an exemplary embodiment, the first integral function is:

[0028]

number

[0029] Calculation of the first intermediate viscosity value In an exemplary embodiment, the second integral function is:

[0030]

number

[0031] Calculation of the second intermediate viscosity value In an exemplary embodiment, the third integral function is:

[0032]

number

[0033] Fitting the total mass, the first intermediate viscosity value, and the second intermediate viscosity value to a fitting function In an exemplary embodiment, the fitting comprises least squares fitting. In one embodiment, the least squares fitting comprises non-linear least squares fitting. In one embodiment, the fitting function is:

[0034]

number

[0035] Calculating Figure of Merit (FOM) In further embodiments, the computer-implemented method, system, and computer program product may include, by a computer system, calculating K for fitting. h The figure of merit FOM, which characterizes the contribution of the second intermediate viscosity value Iη of each of the aliquots, i , and the first intermediate viscosity value Iη of each of the aliquots i No, K h In a further embodiment, the computer-implemented method, system, and computer program product further comprises performing a set of logical operations to calculate, by the computer system, a ratio of K for fitting. h The figure of merit FOM, which characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots, i, and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h The device is further configured to perform an operation that performs a set of logical operations that calculates the ratio of

[0036] In an exemplary embodiment, the ratio function is: FOM=(K h I2η i ) / Iη i is.

[0037] The figure of merit FOM is the Huggins constant K for the data / fitting h is a dimensionless number that can characterize the contribution of K to the data / fitting. h The contribution of becomes small and the calculated Huggins constant K h This results in an inaccurate calculated value of the Huggins constant Kh, as indicated by the high standard error of the value of K. h is greater than or equal to 1, then the approximation used to derive the fitting function is not valid and results in an inaccurately calculated Huggins constant K h When the FOM is between 0.05 and 0.5, the calculated Huggins constant K h can be reliable.

[0038] In one embodiment, the computer system calculates the second intermediate viscosity value 164, I2η, of each of the aliquots. i , and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h As a function of the ratio of h 8 to perform a set of logical operations to calculate a figure of merit FOM that characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots. i , and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h As a function of the ratio ofh 8 to perform a set of logical operations to calculate a figure of merit FOM that characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots. i , and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h K for fitting as a function of the ratio of h The system may include a computer system, such as processing unit 816 as shown in FIG. 8, that performs a set of logical operations to calculate a figure of merit FOM that characterizes the contribution of

[0039] In one embodiment, the computer system is configured to: h The figure of merit FOM, which characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots, i , and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h In one embodiment, the computer system is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, to perform a set of logical operations to calculate K for the fitting as a function of the ratio of h The figure of merit FOM, which characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots, i , and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h In one embodiment, the computer system is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, to perform a set of logical operations to calculate K for fitting as a function of the ratio of h The figure of merit FOM, which characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots, i , and a first intermediate viscosity value 162, Iη, of each of the aliquotsi No, K h The present invention is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, to perform a set of logical operations that calculates the ratio of

[0040] In one embodiment, the computer system may include a K for fitting function as computer software executing on a processor of the computer system. h The figure of merit FOM, which characterizes the contribution of the second intermediate viscosity value 164, Iη, of each of the aliquots, i , and a first intermediate viscosity value 162, Iη, of each of the aliquots i No, K h , and performs a set of logical operations that computes the ratio of

[0041] Displaying the results In further embodiments, the computer-implemented method, system, and computer program product further comprises: (a) determining, by the computer system, a first intermediate viscosity value Iη of each of the aliquots; i The total mass of each of the aliquots m i (b) performing a set of logical operations to calculate a ratio of each of the aliquots to the total mass m of each of the aliquots; i In one embodiment, the computer-implemented method, system, and computer program product further comprises: computing the calculated ratio for each of the aliquots relative to the total mass m of each of the aliquots; i Generate a plot of intrinsic viscosity versus peak mass by plotting v / s v against the peak mass. The plot can allow for a simple linear fit as opposed to a two-dimensional fit.

[0042] Referring to FIG. 2 , the computer-implemented method, system, and computer program product may include: determining, by a computer system, a first intermediate viscosity value Iη of each of the aliquots; i The total mass of each of the aliquots m iand a computer system performs an operation 210 that performs a set of logical operations to calculate a ratio of each of the aliquots to the total mass m of each of the aliquots. i The system is further configured to perform an operation 212 to display a plot of

[0043] In further embodiments, the computer-implemented method, system, and computer program product may further comprise: a computer system for determining a first intermediate viscosity value 162, Iη, of each of the aliquots; i of which the total mass of each aliquot is 160 m i and performing a set of logical operations to calculate a ratio of each of the aliquots to the total mass of each of the aliquots 160, m i The device is further configured to perform a calculation to display a plot of

[0044] In one embodiment, the computer system calculates a first intermediate viscosity value 162, Iη, for each of the aliquots. i of which the total mass of each aliquot is 160 m i a set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i 8 to perform calculations to display a plot of the first intermediate viscosity value 162, Iη, of each of the aliquots. i of which the total mass of each aliquot is 160 m i a set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i 8 to perform calculations to display a plot of the first intermediate viscosity value 162, Iη, of each of the aliquots. i of which the total mass of each aliquot is 160 m ia set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i The present invention includes a computer system, such as a processing unit 816 as shown in FIG. 8, that performs the calculations to display the plot of

[0045] In one embodiment, the computer system calculates a first intermediate viscosity value 162, Iη, for each of the aliquots. i of which the total mass of each aliquot is 160 m i a set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i In one embodiment, the computer system is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, to perform operations to display a plot of the first intermediate viscosity value 162, Iη, of each of the aliquots. i of which the total mass of each aliquot is 160 m i a set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i 8 to perform operations to display a plot of the first intermediate viscosity value 162, Iη, of each of the aliquots. i of which the total mass of each aliquot is 160 m i a set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i The present invention is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, to perform operations to display a plot of

[0046] In one embodiment, the computer system, as computer software executing on a processor of the computer system, calculates the first intermediate viscosity value 162, Iη, of each of the aliquots. i of which the total mass of each aliquot is 160 m i a set of logical operations to calculate the ratio of each of the aliquots to the total mass of each of the aliquots, m i Perform the calculation to display the plot of

[0047] Viscometer-based systems In exemplary embodiments, the computer-implemented method, system, and computer program product include: (1) detecting, by a computer system, specific viscosity values ​​η over time from a viscometer; sp (2) receiving, by a computer system, specific viscosity values ​​corresponding to a series of aliquots of an unknown sample injected into an instrument chain, the instrument chain including a viscometer; and (3) determining by a computer system the total mass m of each of the aliquots. i the volume of each aliquot, v i and the concentration of each of the aliquots, c i (3) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots as a function of sp The first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) i (4) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots. sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) i (5) performing a set of logical operations to calculate the total mass m of each of the aliquots by the computer system; i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K hand a third integral function to yield a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample.

[0048] Referring to FIG. 9A, in an exemplary embodiment, a computer-implemented method and system includes a computer system for detecting specific viscosity values ​​η over time from a viscometer. sp Specific viscosity values ​​correspond to a series of aliquots of an unknown sample injected into an instrument chain, the instrument chain including a viscometer. In operation 910, the computer system calculates the specific viscosity (t) of each of the aliquots by calculating the total mass m i the volume of each aliquot, v i and the concentration of each of the aliquots, c i The received specific viscosity values ​​η corresponding to each of the aliquots are calculated by the computer system in operation 912, which performs a set of logical operations to calculate sp The first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) i , by the computer system, performing an operation 914, a set of logical operations to calculate the received specific viscosity values ​​η corresponding to each of the aliquots. sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) i and a computer system that performs a set of logical operations to calculate the total mass m of each of the aliquots. i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K h and a third integral function to perform an operation 918 that results in a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant for the unknown sample.

[0049] In one embodiment, the computer system is computer system 800 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 900. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 900. In one embodiment, the computer system is processing unit 816 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 900. In one embodiment, the computer system is a processor of an analytical instrument that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 900.

[0050] In one embodiment, the computer system is computer system 800 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 910, 912, 914, 916, and 918. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 910, 912, 914, 916, and 918. In one embodiment, the computer system is processing unit 816 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 910, 912, 914, 916, and 918. In one embodiment, the computer system is a processor of an analytical instrument that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 910, 912, 914, 916, and 918.

[0051] 9B, in an exemplary embodiment, the computer-implemented method, system, and computer program product includes a receiver 930, a calculator 932, and a fitter 934. In one embodiment, the receiver 930 receives specific viscosity values ​​942, η, over time, from a viscometer 952. sp9. The instrument chain includes a viscometer, and the specific viscosity values ​​942 correspond to a series of aliquots 954 of the unknown sample injected into the instrument chain, and the instrument chain includes a viscometer 952. In one embodiment, the receiver 930 includes a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 910. In one embodiment, the receiver 930 includes a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 910. In one embodiment, the receiver 930 includes a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 910. In one embodiment, the receiver 930 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 910. In one embodiment, the receiver 930 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 910. In one embodiment, receiver 930 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 910. In one embodiment, receiver 930 performs operation 910 as computer software executing on a processor of receiver 930.

[0052] In one embodiment, the calculator 932 calculates the total mass 960, m i , the volume of each of the aliquots is 944, v i , and the concentration of each of the aliquots 946, c i8, where the computer system 932 is configured to perform a set of logical operations that calculates as a function of . In one embodiment, calculator 932 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 912. In one embodiment, calculator 932 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 912. In one embodiment, calculator 932 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 912. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 912. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 912. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 912. In one embodiment, calculator 932 performs operations 912 as computer software running on a processor of calculator 932 .

[0053] In one embodiment, calculator 932 calculates the first intermediate viscosity value Iη of each of aliquots 962. i , the received specific viscosity values ​​942, η, corresponding to each of the aliquots. sp(t) as a second integral function of (t). In one embodiment, calculator 932 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 914. In one embodiment, calculator 932 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 914. In one embodiment, calculator 932 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 914. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 914. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 914. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 914. In one embodiment, calculator 932 performs operations 914 as computer software running on a processor of calculator 932 .

[0054] In one embodiment, the calculator 932 calculates the received specific viscosity values ​​942, η, corresponding to each of the aliquots. sp (t) as a third integral function of the second intermediate viscosity value Iη of each of the aliquots 964. i8, such that the computer system performs operation 916. In one embodiment, calculator 932 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 916. In one embodiment, calculator 932 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 916. In one embodiment, calculator 932 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 916. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 916. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 916. In one embodiment, calculator 932 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 916. In one embodiment, calculator 932 performs operations 916 as computer software running on a processor of calculator 932 .

[0055] In one embodiment, fitter 934 determines the total mass m of each of aliquots 960. i , the first intermediate viscosity value Iη of each of the aliquots 962 i , and a second intermediate viscosity value I2η of each of the aliquots 964 i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K hand a third integral function to yield a calculated intrinsic viscosity of the unknown sample 966 and a calculated Huggins constant of the unknown sample 968. In one embodiment, fitter 934 includes a computer system, such as computer system 800 as shown in FIG. 8 , that performs operation 918. In one embodiment, fitter 934 includes a computer system, such as computer system / server 812 as shown in FIG. 8 , that performs operation 918. In one embodiment, fitter 934 includes a computer system, such as processing unit 816 as shown in FIG. 8 , that performs operation 918. In one embodiment, fitter 934 is implemented as computer software that runs on a computer system, such as computer system 800 as shown in FIG. 8 , such that the computer system performs operation 918. In one embodiment, fitter 934 is implemented as computer software that runs on a computer system, such as computer system / server 812 as shown in FIG. 8 , such that the computer system performs operation 918. In one embodiment, fitter 934 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 918. In one embodiment, fitter 934 performs operation 918 as computer software executing on a processor of fitter 934.

[0056] In exemplary embodiments, the computer-implemented method, system, and computer program product include: (1) detecting, by a computer system, specific viscosity values ​​η over time from a viscometer; sp (t) where the specific viscosity values ​​correspond to a series of aliquots of an unknown sample injected into an instrument chain, the instrument chain including a viscometer; and (2) calculating by a computer system the received specific viscosity values ​​η corresponding to each of the aliquots. sp The first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) iand (3) performing a set of logical operations to calculate, by the computer system, the received specific viscosity values ​​η corresponding to each of the aliquots. sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) i (4) performing a set of logical operations to calculate the total mass m of each of the aliquots by the computer system; i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K h and a third integral function to yield a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample.

[0057] Referring to FIG. 10A, in an exemplary embodiment, a computer-implemented method and system includes a computer system for detecting specific viscosity values ​​η over time from a viscometer. sp (t), the specific viscosity values ​​corresponding to a series of aliquots of an unknown sample injected into an instrument chain, the instrument chain including a viscometer; and, by the computer system, calculating the received specific viscosity values ​​η corresponding to each of the aliquots. sp The first intermediate viscosity value Iη of each of the aliquots as a second integral function of (t) i , by the computer system, performing an operation 1012, a set of logical operations to calculate the received specific viscosity values ​​η corresponding to each of the aliquots. sp The second intermediate viscosity value Iη of each of the aliquots as a third integral function of (t) i and a computer system that performs a set of logical operations to calculate the total mass m of each of the aliquots. i , the first intermediate viscosity value Iη of each of the aliquots i , and a second intermediate viscosity value I2η for each of the aliquots iThe first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K h and a third integral function to perform an operation 1016, which results in a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant for the unknown sample.

[0058] In one embodiment, the computer system is computer system 800 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 1000. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 1000. In one embodiment, the computer system is processing unit 816 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 1000. In one embodiment, the computer system is a processor of an analytical instrument that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least the operations of method 1000.

[0059] In one embodiment, the computer system is computer system 800 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 1010, 1012, 1014, and 1016. In one embodiment, the computer system is computer system / server 812 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 1010, 1012, 1014, and 1016. In one embodiment, the computer system is processing unit 816 as shown in Figure 8 that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 1010, 1012, 1014, and 1016. In one embodiment, the computer system is a processor of an analytical instrument that performs the analysis of data collected by an analytical instrument script or computer software application that performs at least operations 1010, 1012, 1014, and 1016.

[0060] 10B, in an exemplary embodiment, the computer-implemented method, system, and computer program product includes a receiver 1030, a calculator 1032, and a fitter 1034. In one embodiment, the receiver 1030 receives specific viscosity values ​​1042, η, over time from a viscometer 1052. sp(t), where the instrument chain includes a viscometer, and the specific viscosity values ​​1042 correspond to a series of aliquots 1054 of the unknown sample injected into the instrument chain, where the instrument chain includes the viscometer 1052. In one embodiment, the receiver 1030 includes a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 1010. In one embodiment, the receiver 1030 includes a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 1010. In one embodiment, the receiver 1030 includes a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 1010. In one embodiment, the receiver 1030 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 1010. In one embodiment, the receiver 1030 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 1010. In one embodiment, receiver 1030 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 1010. In one embodiment, receiver 1030 performs operation 1010 as computer software executing on a processor of receiver 1030.

[0061] In one embodiment, the calculator 1032 calculates the received specific viscosity values ​​1042, η, corresponding to each of the aliquots. sp a first intermediate viscosity value 1062, Iη, of each of the aliquots as a second integral function of (t) i8 , where the computer system performs operation 1012. In one embodiment, calculator 1032 comprises a computer system, such as computer system 800 as shown in FIG. 8 , that performs operation 1012. In one embodiment, calculator 1032 comprises a computer system, such as computer system / server 812 as shown in FIG. 8 , that performs operation 1012. In one embodiment, calculator 1032 comprises a computer system, such as processing unit 816 as shown in FIG. 8 , that performs operation 1012. In one embodiment, calculator 1032 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8 , such that the computer system performs operation 1012. In one embodiment, calculator 1032 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8 , such that the computer system performs operation 1012. In one embodiment, calculator 1032 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8 , such that the computer system performs operation 1012. In one embodiment, calculator 1032 performs operation 1012 as computer software running on a processor of calculator 1032 .

[0062] In one embodiment, the calculator 1032 calculates the received specific viscosity values ​​1042, η, corresponding to each of the aliquots. sp The second intermediate viscosity value 1064, Iη, of each of the aliquots as a third integral function of (t) i8, such that the computer system performs operation 1014. In one embodiment, calculator 1032 comprises a computer system, such as computer system 800 as shown in FIG. 8, that performs operation 1014. In one embodiment, calculator 1032 comprises a computer system, such as computer system / server 812 as shown in FIG. 8, that performs operation 1014. In one embodiment, calculator 1032 comprises a computer system, such as processing unit 816 as shown in FIG. 8, that performs operation 1014. In one embodiment, calculator 1032 is implemented as computer software running on a computer system, such as computer system 800 as shown in FIG. 8, such that the computer system performs operation 1014. In one embodiment, calculator 1032 is implemented as computer software running on a computer system, such as computer system / server 812 as shown in FIG. 8, such that the computer system performs operation 1014. In one embodiment, calculator 1032 is implemented as computer software running on a computer system, such as processing unit 816 as shown in FIG. 8, such that the computer system performs operation 1014. In one embodiment, calculator 1032 performs operations 1014 as computer software running on a processor of calculator 1032 .

[0063] In one embodiment, the fitter 1034 measures the total mass 1060, m i , the first intermediate viscosity value 1062 of each of the aliquots, Iη i , and the second intermediate viscosity value 1064, I2η, of each of the aliquots i The first integral function, the floating intrinsic viscosity of the unknown sample [η], and the second integral function, the floating Huggins constant of the unknown sample K hand a third integral function to yield a calculated intrinsic viscosity of the unknown sample 1066 and a calculated Huggins constant of the unknown sample 1068. In one embodiment, fitter 1034 comprises a computer system, such as computer system 800 as shown in FIG. 8 , that performs operation 1016. In one embodiment, fitter 1034 comprises a computer system, such as computer system / server 812 as shown in FIG. 8 , that performs operation 1016. In one embodiment, operation 1034 comprises a computer system, such as processing unit 816 as shown in FIG. 8 , that performs operation 1016. In one embodiment, fitter 1034 is implemented as computer software that runs on a computer system, such as computer system 800 as shown in FIG. 8 , such that the computer system performs operation 1016. In one embodiment, fitter 1034 is implemented as computer software that runs on a computer system, such as computer system / server 812 as shown in FIG. 8 , such that the computer system performs operation 1016. In one embodiment, fitter 1034 is implemented as computer software executing on a computer system, such as processing unit 816 as shown in Figure 8, such that the computer system performs operation 1016. In one embodiment, fitter 1034 performs operation 1016 as computer software running on a processor of fitter 1034. [Example]

[0064] For example, computer-implemented methods, systems, and computer products can calculate the intrinsic viscosity and Huggins constant of a series of aliquots 154 of an unknown sample, which can be generated by injecting a single concentration of the unknown sample into an instrument chain at various injection volumes, as depicted in Figure 3. In particular, Figure 3 depicts a series of injections of various total masses.

[0065] For each injection, the calculator 132 calculates the total mass in the injection, 160, m i, first intermediate viscosity value 162, Iη i , and a second intermediate viscosity value 164, I2η i can be calculated over the injection of the unknown sample, as a triple (m i , Iη ) of the total mass 160, the first intermediate viscosity value 162, and the second intermediate viscosity value 164. i , I2η i ) The fitter 134 then fits the triple to a fitting function, resulting in a calculated intrinsic viscosity 166 and a calculated Huggins constant 168 for the unknown sample.

[0066] For example, FIG. 4A depicts the measured / received concentration detector signal values ​​140 (dRI) of a first set of seven injections of a first unknown sample (protein) having a first concentration range, FIG. 4B depicts the measured / received specific viscosity values ​​142 of the first set of seven injections, and FIG. 4C depicts the calculated triple (mI, Iη) of the first set of seven injections calculated by calculator 132 based on the first set of seven injections. i , I2η i ), describes the calculated intrinsic viscosity 166 and calculated Huggins constant 168 of the first unknown sample generated by the fitter 134, and the FOM of the first unknown sample.

[0067] For example, FIG. 5A depicts the measured / received concentration detector signal values ​​140 (dRI) of a second set of seven injections of a first unknown sample (protein) having a second concentration range, FIG. 5B depicts the measured / received specific viscosity values ​​142 of the second set of seven injections, and FIG. 5C depicts the calculated triple (mI, Iη) of the second set of seven injections calculated by calculator 132 based on the second set of seven injections. i , I2η i ), describes the calculated intrinsic viscosity 166 and calculated Huggins constant 168 of the first unknown sample generated by the fitter 134, and the FOM of the first unknown sample.

[0068] For example, FIG. 6A depicts the measured / received concentration detector signal values ​​140 (dRI) for a set of seven injections of a second unknown sample (protein), FIG. 6B depicts the measured / received specific viscosity values ​​142 for a set of seven injections of the second unknown sample, and FIG. 6C depicts the calculated triple (mI, Iη) for a set of seven injections of the second unknown sample calculated by calculator 132. i , I2η i ), the calculated intrinsic viscosity 166 and calculated Huggins constant 168 of the second unknown sample generated by the fitter 134, and the FOM of the second unknown sample.

[0069] FIG. 7 shows the calculated ratios of each of the seven aliquots / injections versus the total mass 160, m for each of the seven aliquots / injections as displayed by the computer-implemented method, system, and computer program product for an unknown sample. i 7 depicts a plot of. In particular, Figure 7 depicts three plots, two intersecting plots corresponding to a first unknown sample and a third plot corresponding to a second unknown sample. The two intersecting plots in Figure 7 demonstrate that the results of the computer-implemented method, system, and computer program product may be reproducible.

[0070] For example, the computer-implemented method, system, and computer product can calculate the intrinsic viscosity and Huggins constant of a series of aliquots 954 of an unknown sample, which can be generated by injecting various concentrations of the unknown sample into an instrument chain at a fixed injection volume. i is variable and c i If v is constant, a single vial can be used to contain the aliquots. i If is constant and the peak has a constant width, then c iis variable. Multiple vials can be used to accommodate aliquots, thereby helping to set integration limits / boundaries due to peaks having the same width. For example, samples can be prepared by any one of the following: (i) an autosampler as a sampler (injector) to generate multiple vials, (ii) a mixer with multiple syringes, or (iii) an autosampler as a mixer (e.g., vial 1 - sample, vial 2 - solvent, mixing the contents of vial 1 with the contents of vial 2, thereby programmatically creating multiple vials).

[0071] Computer Systems In an exemplary embodiment, the computer system is computer system 800 as shown in Figure 8. Computer system 800 is merely one example of a computer system and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the present invention. In any event, computer system 800 is implemented and / or capable of performing any of the functions / operations of the present invention.

[0072] Computer system 800 includes a computer system / server 812 that is capable of operating in conjunction with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and / or configurations that may be suitable for use with computer system / server 812 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices.

[0073] The computer system / server 812 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, and / or data structures that perform particular tasks or implement particular abstract data types. The computer system / server 812 may be practiced in a distributed cloud computing environment where tasks are performed by remote processing devices linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media, including memory storage devices.

[0074] 8, computer system / server 812 in computer system 800 is shown in the form of a general-purpose computing device. Components of computer system / server 812 may include, but are not limited to, one or more processors or processing units 816, a system memory 828, and a bus 818 that couples various system components including the system memory 828 to the processor 816.

[0075] Bus 818 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a high-speed graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example and not limitation, such architectures include an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0076] Computer system / server 812 typically includes a variety of computer system-readable media. Such media can be any available media that can be accessed by computer system / server 812 and includes both volatile and nonvolatile media, removable and non-removable media.

[0077] The system memory 828 may include computer system-readable media in the form of volatile memory, such as random access memory (RAM) 830 and / or cache memory 832. The computer system / server 812 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 834 may be provided for reading from and writing to a non-removable, non-volatile magnetic medium (not shown, typically referred to as a "hard drive"). Although not shown, a magnetic disk drive may be provided for reading from and writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive may be provided for reading from and writing to a removable, non-volatile optical disk, such as a CD-ROM, DVD-ROM, or other optical medium. In such cases, each may be connected to the bus 818 by one or more data media interfaces. As further depicted and described below, the memory 828 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions / operations of embodiments of the present invention.

[0078] A program / utility 840 having a set (at least one) of program modules 842 may be stored in memory 828, by way of example and not limitation. Exemplary program modules 842 may include an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data, or any combination thereof, may comprise an implementation of a network environment. The program modules 842 generally perform the functions and / or methods of embodiments of the present invention.

[0079] The computer system / server 812 may also communicate with one or more external devices 814, such as a keyboard, a pointing device, a display 824, one or more devices that allow a user to interact with the computer system / server 812, and / or any device (e.g., a network card, a modem, etc.) that allows the computer system / server 812 to communicate with one or more other computing devices. Such communication may occur via an input / output (I / O) interface 822. Additionally, the computer system / server 812 may communicate with one or more networks, such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet), via a network adapter 820. As depicted, the network adapter 820 communicates with other components of the computer system / server 812 via a bus 818. It should be understood that other hardware and / or software components, not shown, may be used with the computer system / server 812. Examples include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems.

[0080] computer program products The present invention may be a system, a method, and / or a computer program product, which may include one or more computer-readable storage media having computer-readable program instructions that cause a processor to perform aspects of the present invention.

[0081] A computer-readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction execution device. A computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically encoded devices such as punch cards or ridge structures in grooves with instructions recorded thereon, and any suitable combination of the foregoing. Computer-readable storage medium, as used herein, should not be construed as being a transitory signal per se, such as an electric wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse passing through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0082] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device.

[0083] The computer-readable program instructions for carrying out the operations of the present invention may be either assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or a connection may be made to an external computer (e.g., via the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to customize the electronic circuitry to perform aspects of the present invention.

[0084] Aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0085] These computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, executed by the processor of the computer or other programmable data processing apparatus, create means for performing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. These computer-readable program instructions may also be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer-readable storage medium on which the instructions are stored comprises a product containing instructions that implement aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0086] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to generate a computer-implemented process, such that the instructions executing on the computer, other programmable apparatus, or other device perform the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0087] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing specified logical functions. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, may be implemented by a dedicated hardware-based system that performs the specified functions or operations or executes a combination of dedicated hardware and computer instructions.

[0088] The description of various embodiments of the present disclosure has been presented for purposes of illustration and is not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terms used herein have been selected to explain the principles of the embodiments, practical applications or technical improvements to technology found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. 1. A computer-implemented method comprising: The computer system records the specific viscosity value η over time from the viscometer. ｓｐ (t), the specific viscosity values ​​correspond to a series of aliquots of an unknown sample injected into an instrument chain; receiving the instrument chain including the viscometer; The computer system determines the total mass m of each of the aliquots. ｉ the volume v of each of the aliquots ｉ and the respective concentrations c of the aliquots ｉ performing a set of logical operations that compute as a function of The computer system receives the specific viscosity values ​​η corresponding to each of the aliquots. ｓｐ (t) as a second integral function of the first intermediate viscosity value Iη of each of the aliquots. ｉ performing a set of logical operations to compute The computer system calculates the received specific viscosity values ​​η corresponding to each of the aliquots. ｓｐ (t) as a third integral function of the second intermediate viscosity value I2η of each of the aliquots. ｉ performing a set of logical operations to compute The computer system calculates the total mass m of each of the aliquots. ｉ , the first intermediate viscosity value Iη of each of the aliquots ｉ and the second intermediate viscosity value I2η of each of the aliquots ｉ the first integral function, the floating intrinsic viscosity [η] of the unknown sample, the second integral function, and the floating Huggins constant K of the unknown sample. ｈ and performing a set of logical operations to fit a fitting function comprising the third integral function to the calculated intrinsic viscosity of the unknown sample and the calculated Huggins constant of the unknown sample.

2. The method of claim 1 , wherein the viscometer is a differential viscometer.

3. The total mass m of each of the aliquots ｉ but, m ｉ =v ｉ ×c ｉ The method of claim 1, wherein

4. The second integral function is [Equation 1] The method of claim 1, wherein

5. The third integral function is [Equation 2] The method of claim 1, wherein

6. The method of claim 1 , wherein the fitting comprises a least-squares fitting.

7. The method of claim 6 , wherein the least-squares fitting comprises non-linear least-squares fitting.

8. The fitting function is [Equation 3] The method of claim 1, wherein

9. The computer system calculates the K for the fitting. ｈ A figure of merit FOM characterizing the contribution of each of the second intermediate viscosity values ​​I2η of the aliquots ｉ and the first intermediate viscosity value Iη of each of the aliquots ｉ No, K ｈ The method of claim 1 further comprising performing a set of logical operations to calculate as a ratio function of

10. The ratio function is FOM=(K ｈ I2η ｉ ) / Iη ｉ The method of claim 9, wherein

11. The computer system determines the first intermediate viscosity value Iη of each of the aliquots. ｉ the total mass m of each of the aliquots ｉ performing a set of logical operations to calculate a ratio to The computer system calculates the ratio of each of the aliquots to the total mass m of each of the aliquots. ｉ and displaying a plot of the

12. 1. A computer-implemented method comprising: The computer system records the specific viscosity value η over time from the viscometer. ｓｐ (t), the specific viscosity values ​​correspond to a series of aliquots of an unknown sample injected into an instrument chain; receiving the instrument chain including the viscometer; The computer system receives the specific viscosity values ​​η corresponding to each of the aliquots. ｓｐ (t) as a second integral function of the first intermediate viscosity value Iη of each of the aliquots. ｉ performing a set of logical operations to compute The computer system calculates the received specific viscosity values ​​η corresponding to each of the aliquots. ｓｐ (t) as a third integral function of the second intermediate viscosity value I2η of each of the aliquots. ｉ performing a set of logical operations to compute The computer system determines the total mass m of each of the aliquots. ｉ , the first intermediate viscosity value Iη of each of the aliquots ｉ and the second intermediate viscosity value I2η of each of the aliquots ｉ the first integral function, the floating intrinsic viscosity [η] of the unknown sample, the second integral function, and the floating Huggins constant K of the unknown sample. ｈ and performing a set of logical operations to fit a fitting function comprising the third integral function to the calculated intrinsic viscosity of the unknown sample and the calculated Huggins constant of the unknown sample.

13. The method of claim 12, wherein the viscometer is a differential viscometer.

14. The second integral function is [Equation 4] The method of claim 12, wherein

15. The third integral function is [Equation 5] The method of claim 12, wherein

16. The method of claim 12 , wherein the fitting comprises a least-squares fitting.

17. The method of claim 16 , wherein the least-squares fitting comprises non-linear least-squares fitting.

18. The fitting function is [Equation 6] The method of claim 12, wherein

19. The computer system calculates the K for the fitting. ｈ A figure of merit FOM characterizing the contribution of each of the second intermediate viscosity values ​​I2η of the aliquots ｉ and the first intermediate viscosity value Iη of each of the aliquots ｉ No, K ｈ 13. The method of claim 12, further comprising performing a set of logical operations to calculate as a ratio function of

20. The ratio function is FOM=(K ｈ I2η ｉ ) / Iη ｉ 20. The method of claim 19, wherein:

21. The computer system determines the first intermediate viscosity value Iη of each of the aliquots. ｉ the total mass m of each of the aliquots ｉ performing a set of logical operations to calculate a ratio to The computer system calculates the ratio of each of the aliquots to the total mass m of each of the aliquots. ｉ and displaying a plot of the

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