Recycled waste for chemical plants

Abstract

The invention relates to the field of sustainability, in particular to the field of plastics sorting and recycling. The invention relates to methods, systems, apparatuses, and computer elements for monitoring and / or controlling at least one composition property of one or more recyclate(s).

Description

[0001] 230774

[0002] RECYCLED WASTE FOR CHEMICAL PLANTS

[0003] TECHNICAL FIELD

[0004] The invention relates to the field of sustainability, in particular to the field of plastics sorting and recycling. The invention relates to methods, systems, apparatuses, and computer elements for monitoring and / or controlling at least one composition property of one or more recyclate(s).

[0005] TECHNICAL BACKGROUND

[0006] Chemical products for plastic are used in diverse applications and end up in multiple supply chains to produce a diversity of products containing plastics. Recycling of plastic articles is challenging owing to the complexity of sorting the diverse set of waste articles. The refeed of plastics into chemical value chains is particularly difficult, since chemical plants such as steam crackers are world scale plants with narrow specifications. Chemical producers are hence hampered to recycle and refeed plastics in material value chains.

[0007] Recycling of plastic waste requires separation and a sorting of the plastic waste due to the big variety of polymer types, grades, blends and / or additives. Therefore, the quality of the recyclate produced from the plastic waste can vary impacting chemical production using such recyclate.

[0008] SUMMARY

[0009] In one aspect disclosed is a method for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for industrial production:

[0010] providing at least one target composition property associated with recyclates to be used as input material for one or more production plant(s);

[0011] providing one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s);

[0012] gathering based on the one or more waste identifier(s) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s);

[0013] determining, based on the target composition property and the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s), at least one subset of the one or more waste identifier(s) and a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s);230774

[0014] 2

[0015] providing the at least one subset of the one or more waste identifier(s) and optionally the total composition property for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for production.

[0016] In another aspect disclosed is an apparatus, e.g. connected to or as part of a decentral network node, associated with chemical production, for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for chemical production:

[0017] at least one input interface configured to provide at least one target composition property associated with recyclates to be used as input material for one or more production plant(s) and to provide one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) and to gather based on the one or more waste identifier(s) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s);

[0018] at least one processor configured to determine, based on the target composition property and the at least one composition property per one or more waste articles and / or one or more sorted waste frac- tion(s), at least one subset of the one or more waste identifier(s) and a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s);

[0019] at least one output interface configured to provide the at least one subset of the one or more waste identifier(s) and optionally the total composition property for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for production.

[0020] An apparatus, e.g. in connection with or as part of a decentral network node, associated with chemical production, comprising:

[0021] one or more processors and one or more computer-readable media having thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the apparatus to perform the following steps:

[0022] providing at least one target composition property associated with recyclates to be used as input material for one or more chemical production plant(s);

[0023] providing one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s);

[0024] gathering based on the one or more waste identifier(s) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s);

[0025] determining based on the target composition property, the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) at least one subset of the one or230774

[0026] 3

[0027] more waste identifier(s) and a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s);

[0028] providing the at least one subset of the one or more waste identifier(s) and optionally the total composition property for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for chemical production.

[0029] An apparatus, e.g. in connection with or as part of a decentral network node, associated with waste sorting, comprising:

[0030] one or more processors and one or more computer-readable media having thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the apparatus to perform the following steps:

[0031] providing one or more waste identifier(s) and at least one composition property associated with one or more waste articles;

[0032] receiving the at least one subset of the one or more waste identifier(s) generated according to the methods or by the apparatuses disclosed herein;

[0033] generating fraction control data for sorting waste articles based on the at least one subset of the one or more waste identifier(s);

[0034] providing fraction identifier(s) per fraction sorted based on fraction control data and assigning fraction identifier(s) to fraction data associated with sorted waste fractions.

[0035] An apparatus, e.g. in connection with or as part of a decentral network node, associated with waste recycling, comprising:

[0036] one or more processors and one or more computer-readable media having thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the apparatus to perform the following steps:

[0037] providing one or more waste identifier(s) and at least one composition property associated with one or more waste fractions;

[0038] receiving the at least one subset of the one or more waste identifier(s) generated according to the methods or by the apparatuses disclosed herein;

[0039] generating recyclate control data for monitoring and / or controlling input waste fractions to produce recyclate batch(es) based on the at least one subset of the one or more waste identifier(s); providing recyclate identifier(s) per recyclate batch recycled based on recyclate control data and assigning recyclate identifier(s) to recyclate data associated with recyclate batch(es).230774

[0040] 4

[0041] Use of the at least one subset of the one or more waste identifier(s) as determined according to the methods or by the apparatuses disclosed herein for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for production.

[0042] Any disclosure, embodiments and examples described herein relate to the methods, the systems, apparatuses, articles, waste fractions, uses and computer elements lined out above and below. Advantageously, the benefits provided by any of the embodiments and examples equally apply to all other embodiments and examples.

[0043] EMBODIMENTS

[0044] To improve the recycling of plastic and the reuse in material value chains, a data driven approach using data accessible through a decentral network for sorting and recycling is proposed. One challenge to realize a circular economy is to generate valuable waste fractions and recyclates that adhere to the requirements for refeeding into chemical plants. In particular the use of existing chemical infrastructure poses certain requirements to the composition of recyclates produced from (sorted) waste streams. The approach presented here allows through simple digital extension of existing infrastructure of sorting, recycling and chemical facilities for coordinating recyclate generation for chemical industry based on requirements of the chemical infrastructure.

[0045] In particular, by accessing the composition properties based on the decentral identifier per one or more waste articles and / or one or more sorted waste fraction(s) from one or more network node(s) of a decentral network and by determining based on the target composition property, the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) and at least one subset of the one or more waste identifier(s) a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s) allows the chemical producer to guide sorting and / or recycling according to the requirements of existing or retrofitted chemical production plants. Furthermore, by specifically defining the requirements of the use of the recyclate e.g. related to a waste fraction to be processed by a chemical recycling process to produce a hydrocarbon recyclate for a petrochemical process, by a chemical recycling process to produce a recyclate mixture including at least hydrogen and carbon monoxide for a hydrogen-based chemical process, by a chemical recycling process to produce a monomer and / or polymer recyclate for a monomer and / or a polymer production process, and / or by a solvent-based recycling process to produce a monomer and / or polymer recyclate e.g. for an article, a monomer and / or a polymer production process, the waste fraction can be tailored to the refeed230774

[0046] 5

[0047] of recyclate into chemical value chains. This way the recycling of materials can be improved by increasing the quantity of materials refeedable into material loops. As a result, the environmental impact of materials can be reduced.

[0048] In the following, embodiments of the present disclosure will be outlined by ways of examples. It is to be understood that the present disclosure is not limited to said embodiments and / or examples.

[0049] Monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for chemical production may include generating instruction configured to collect, sort, separate and / or recycle waste or waste fractions. The instructions may be configured to be executable by at least one sorting apparatus configured to sort waste and / or waste fractions, collecting apparatus configured to collect waste and / or waste fractions, separation apparatus configured to separate waste and / or waste fractions and / or recycling apparatus configured to recycle waste and / or waste fractions. In particular the waste or waste fractions may be collected, sorted and / or separated for a specific use, in particular to one or more of the following uses for waste fraction(s) to be processed:

[0050] by a chemical recycling process to produce a hydrocarbon recyclate for a petrochemical process, by a chemical recycling process to produce a recyclate mixture including at least hydrogen and carbon monoxide for a hydrogen-based chemical process,

[0051] by a chemical recycling process to produce a monomer and / or polymer recyclate for a polymer, component and / or article production process,

[0052] by a chemical recycling process to produce a monomer and / or polymer recyclate for a polymer, component and / or article production process, and / or

[0053] a mechanical recycling process to produce a monomer and / or polymer recyclate for monomer, polymer, component and / or article production process

[0054] At least one target composition property associated with recyclates to be used as input material for one or more chemical production plant(s) may be provided. The target composition property may be associated with one composition property or more composition properties of the recyclate to be used by at least one industrial production, such as chemical production process. The target composition property may specify constraints or boundaries for the one composition property or more composition properties of the recyclate to be used by at least one industrial production, such as chemical production process. The target composition property may be associated with substances or compounds to be excluded and / or contaminants or critical substances or compounds. The target composition property may may specify constraints or boundaries for contaminants or critical substances or compounds. The composition property may specify at least one230774

[0055] 6

[0056] or more critical substance(s) and their respective critical quantity, such as a threshold or range quantity, for the recyclates. Critical may refer to any characteristic or substance that may impede the processing of the recyclate, negatively affect the processing of the recyclate, e.g. by reducing yields, and / or the negatively impact the equipment the recyclate is processed by, e.g. through degradation. For example, such substances or contaminants may be monitored and / or controlled at the sorting and / or recycling stage reliably through the tracked composition data accessible via the decentral network. This way higher quality waste fractions, recyclate from such fractions such as pyrolysis oil and with that safe and reliable operation of the industrial production such as cracker operation may be achieved.

[0057] One or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) may include one or more decentral identifier(s) uniquely related to the one or more waste articles and / or one or more sorted waste fraction(s). The one or more waste identifier(s) may relate to one or more decentral identifier(s) signifying the digital twin of the physical entity of the one or more waste articles and / or one or more sorted waste fraction(s). The decentral identifier may be or include a digital identifier of or for the decentral network discoverable by decentral network participants or nodes. The decentral identifier may be or include a digital identifier provided to the decentral network and participant nodes of the decentral network. The decentral identifier may hence signify physical entities of the one or more waste articles and / or one or more sorted waste fraction(s) in the decentral network and participant nodes may be able to interpret the relation of the decentral identifier to the physical entities of the one or more waste articles and / or one or more sorted waste fraction(s).

[0058] The decentral identifier may comprise any unique identifier uniquely associated with the data owner and article. The decentral identifier may include one or more Universally Unique Identifier(s) (UUID) or a Digital Identifier(s) (DID). The decentral identifier may be issued by a central or decentral identity issuer. The decentral identifier may relate to authentication information. Via the decentral identifier associated with one or more waste articles or waste fractions and its unique association with the data owner and access to composition property data may be controlled by the data owner. This contrasts with central authority schemes, where identifiers are provided by such central authority and access to data is controlled by such central authority. Decentral in this context refers to the usage of the identifier as controlled by the data owner.

[0059] The decentral identifier may include one or more identifier(s) used in the decentral network and allowing for data exchange via the decentral network. Data exchange may include discovery of the decentral identifier for network nodes of the decentral network, authentication of network nodes of the decentral network and / or authorization of data transfers via a peer-to-peer communication between network nodes of the230774

[0060] 7

[0061] decentral network. The decentral identifier may be associated with participants of a material chain network, particularly a material loop, including chemical product producer, intermediate chemical product producer, intermediate part producer, component producer, component assembly producer, end product producer, end product user, end product collector, end product sorter and / or end product recycler. The decentral identifier may be associated with chemical product, intermediate chemical product, intermediate articles, articles, articles to be recycled, end-of-life articles, waste articles, waste fractions, recyclates of a material chain network, particularly a material loop.

[0062] The composition property per one or more waste articles and / or one or more waste fraction(s) may relate to the chemical composition and / or physical characteristic(s) of the one or more waste articles and / or one or more waste fraction(s). The composition property may include compound and / or substances contained in the one or more waste articles and / or one or more waste fraction(s). The physical characteristics may include application and / or operation properties of the one or more waste articles and / or one or more waste fraction(s) that may impact the processing, e.g. recycling, of the one or more waste articles and / or one or more waste fraction(s).

[0063] In one embodiment the target composition property specifies constraints or boundaries for the one or more composition properties associated with recyclate to be used by the industrial production.

[0064] In another embodiment the target composition property relates to one or more composition properties associated with recyclate as produced from one or more waste articles and / or one or more sorted waste frac-tion(s).

[0065] In another embodiment the target composition property relates to one or more composition properties associated with one or more waste articles and / or one or more sorted waste fraction(s), wherein the target composition property is provided by the operating apparatus associated with the industrial production for which the recyclate is to be used.

[0066] In another embodiment the one or more waste identifier(s) are provided by one or more nodes associated with a collecting, sorting and / or recycling stage configured to collect, sort and / or recycle one or more waste articles and / or one or more sorted waste fraction(s).

[0067] In another embodiment the one or more waste identifier(s) relate to at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s),230774

[0068] 8

[0069] In another embodiment the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) is accessible based on the one or more waste identifier(s).

[0070] In another embodiment the at least one composition property and the one or more waste identifier(s) per one or more waste articles and / or one or more sorted waste fraction(s) are stored by a distributed and / or decentral network storage associated with the owner of the one or more waste articles and / or one or more sorted waste fraction(s).

[0071] In another embodiment determining at least one subset of the one or more waste identifier(s) and a total composition property includes determining the total composition property from at least one composition property per waste identifier of the subset, wherein determining at least one subset of the one or more waste identifier(s) and a total composition property includes determining that the total composition property fulfills the target composition property.

[0072] In another embodiment determining at least one subset of the one or more waste identifier(s) and a total composition property includes determining the at least one subset of the one or more waste identifier(s) based on the composition property associated with one or more waste articles and / or one or more sorted waste fraction(s) as signified by the one or more waste identifier(s).

[0073] In another embodiment providing the at least one subset of the one or more waste identifier(s) includes providing the at least one subset to one or more nodes associated with collecting, sorting and / or recycling stages for generating control data for monitoring and / or controlling input waste articles and / or fractions based on the at least one subset of the one or more waste identifier(s).

[0074] BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In the following, the present disclosure is further described with reference to the enclosed figures.

[0076] Fig. 1 illustrates an example embodiment of a circular material loop including material participants connected through a decentral network with decentral network nodes associated with material participants.230774

[0077] 9

[0078] Fig. 2 illustrates the flow chart for an example of an intelligent sorting method that may be implemented in the sorting system with decentral network interface.

[0079] Figs. 3a, b illustrate example data structures used for the intelligent sorting method based on material composition data and / or article history data accessible by way of the decentral network interface.

[0080] Fig. 4 illustrates an example flow chart of a methods for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for production.

[0081] Fig. 5 illustrates an example of the waste sorting, recycling and production facility connected to operating apparatuses configured to access and share data via a decentral network.

[0082] Fig. 6 illustrates an example of a method or apparatus for providing material composition data by way of the decentral network.

[0083] Fig. 7 illustrates an example of the pre-defined classification configured to separate plastic articles by material composition, and recycling process.

[0084] Figs. 8a to 8c illustrate different computing environments, central, decentral and distributed.

[0085] DETAILED DESCRIPTION

[0086] The following embodiments are mere examples for implementing the methods, the apparatuses, the systems or applications disclosed herein and shall not be considered limiting.

[0087] Fig. 1 illustrates an example embodiment of a circular material loop 100 including material participants 101.1-6 connected through a decentral network 102 with decentral network nodes 103.1-6 associated with material participants 101.1-6.

[0088] The participant network shown in Fig. 1 may be a material chain network. The material chain network may include one or more linear material chain(s). The linear material chain(s) may include a material supply chain, in which the material is produced by a material producer 101.1 and used to produce an end product by an original equipment manufacturer 101.3 (OEM). The linear material chain(s) may include a material recycling chain, in which the produced end product is collected, sorted and recycled up to a recycling230774

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[0090] system operator 101.6 and the recyclate is used to produce new material by the material producer 101.1. The material chain may include one or more supply and / or recycling chain(s). The material chain may include one or more connected supply and / or recycling chain(s). One or more linear material chain(s) may be connected to the material loop 100.

[0091] The material chain network may include a material loop network 100 including the use of recycled materials) to produce new materials. One or more material loop(s) 100 may allow to use materials resulting from recycling of end-of-life products to produce new products, such as chemical products or materials, associated with one or more material chain(s). The material chain network, preferably the material loop 100, may include the production, use and / or recycling of physical materials and products. The product may be a material, a chemical product, an intermediate chemical product, a component, a component assembly, an end product, an end-of-life product, a product to be recycled, a recycled productor a recyclate.

[0092] Material or chemical product may refer to a chemical compound, a chemical ingredient, a chemical molecule, a chemical composition, a chemical mixture, a chemical formulation, an intermediate chemical product, or a chemical base material that may be used to produce discrete products. Chemical material or product flows may include non-discrete material flows that may be further processed to produce discrete products or components. Chemical material or product flows may include liquids, pellets, beats, powders or the like. The discrete product may refer to a component, a component assembly, an end product, an end-of-life product, a product to be recycled, or a recycled discrete product. The recyclate may refer to a mechanically or chemically recycled material. Recyclate or recycled material flows may include non-discrete material flows that may be further processed to produce new materials or chemical products. Recyclate or recycled material flows may include liquids, pellets, beats, powders or the like.

[0093] End product may refer to a product that is the result of a material supply chain. End product may refer to a product that is used by the end product user. End-of-life (EOL) product may refer to a product that has been used by end product user. End-of-life product may refer to a product that does no longer fulfill the requirements for its use. End-of-life product may refer to a product that is no longer required. End-of-life products may be products disposed in waste, such as plastic waste. A recycled product may refer to any product that has been produced using end-of-life product(s). A recycled product may refer to a new product that has been produced using end-of-life product(s).

[0094] The material loop 100 illustrated in Fig. 1 may include multiple participants 101.1-6 forming the material loop 100. The material loop 100 may include all stages of the material from production of the material via230774

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[0096] use of the material to re-use of the material. The material may hence flow in a closed loop from production of constituents, the end product via use to re-use. Re-use may include re-purposing of the end-of-life product, re-furbishing of the end-of-life product and / or recycling of the end-of-life product to refeed recyclate into material production.

[0097] The participant(s) 101.1-6 of the material loop may be associated with the production of any material or product and / or recycling of any material or product. The participant(s) of the material loop 100 may include the chemical product producer 103.1, the chemical product user 103.2, the original equipment manufacturer, OEM 103.3, the end product user 103.4, the EOL product collector and / or sorter 103.5, the recycling system operator 103.6 and combinations thereof. The participant(s) may include various participant(s) of the material chain or loop not shown in Fig. 1.

[0098] The participant(s) 101.1-6 of the material loop 100 may be connected through material flow(s) 104. The material flow 104 may correspond to the flow of product or material from one participant 101.1 -6 of the material loop to the downstream participant 101.1-6 of the material loop 100. The material flow 104 may refer to a continuous or a discontinuous flow of product or material. The flow of product or material may include any means of transportation suitable to transport the product from one participant 101.1-6 to another downstream participant 101.1-6. The means of transportation may include pipes, containers, barrels, packages or the like. The material flow 104 may be a one-sided flow, such as a directional material flow 104. The material flow 104 may flow from the upstream participant 101.1-6 to the downstream participant 101.1-6 of the material loop 100, such as the material flow 104 from the recycling system operator 101.6 to the chemical product producer 101.1. The material flow may include reverse material flow 104 from the downstream participant 101.1-6 to the upstream participant 101.1-6 of the material loop 100. For example, material may flow 104 from the chemical product producer 101.1 to the recycling system 101.6, e.g. when the recycled product or recyclate does not adhere to quality specifications and needs further treatment.

[0099] The material flow 106 may be associated with raw materials used to produce the material or chemical product, such as virgin raw material(s). Virgin raw material may be unused raw material that has not been subjected to any processing other than for its production. Instead of virgin raw material(s) the material flow 104 may include recycled material(s). Recycled material(s) may be made from waste material that can be recycled. The raw and recycled materials may be provided to the chemical product producer for producing materials), chemical product(s) and / or intermediate chemical product(s) (not shown).230774

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[0101] The material loop 100 illustrated in Fig. 1 is based on the example of plastic materials and their circular loop. Plastic materials may include a synthetic material made from a wide range of organic polymers such as polyethylene, polypropylene, polystyrene, polyethylene terephthalate, polyvinyl carbon, polyamide, polyurethane or the like. The material participants may include the monomer and / or polymer producer 101.1, the monomer and / or polymer user 101.2 such as the compounder, moulder or converter, the original equipment manufacturer 101.3 such as the polymer-containing product producer, the polymer-containing product user 101.4 such as the retailer or the consumer, the waste collector and / or sorter, the recycling system operator 101. 5 such as the recycler or refiner.

[0102] The monomers and / or polymers may be produced by the chemical producer. The monomers and / or polymers may be provided to a polymer user, such as a compounder, moulder and / or converter. The monomers and / or polymers may be compounded, moulded and / or converted. The compounded, moulded and / or converted polymer may be provided to a polymer-containing product producer (Original Equipment Manufacturer - OEM). The polymer-containing product or article may be produced using the compounded, moulded and / or converted polymer. The polymer-containing product or article may be provided to a polymer-containing product user. The polymer-containing product or article may be used by the user. At the end-of-life the polymer-containing product or article may be disposed by the user. The disposed polymer-containing product or article may be provided to the plastic waste collector and / or sorter. The disposed polymer-containing product or article may be collected in a plastic waste stream. The plastic waste stream may be sorted. The plastic waste stream may be provided to a sorter for sorting fractions of polymer-containing products or articles to be recycled. The sorted fractions of polymer-containing products or articles may be provided to a recycler for recycling the polymer-containing product fraction. The recycled fraction may be provided to the chemical producer for producing new monomers and / or polymers thus closing the material loop 100. The material flow 104 may close the loop between the material participants.

[0103] In addition to the connection through material flows 104, the material participants 101.1-6 of the circular material loop 100 may be connected through data flows 105 via the decentral network 102. The decentral network 102 may include one or more decentral network nodes 103.1-6 associated with material participants 101.1-6 of the material loop 100. In a decentralized or decentral network 102, the decentral network nodes 103.1-6, in contrast to a centralized network, do not exclusively rely on a central network node. In other words, no single entity is the sole authority of the network. The decentral network 102 may include decentral and central network nodes. The decentral network 102 may include central network nodes that may control and / or monitor the decentral network nodes 103.1-6. For example, central network node(s)may provide authentication information, which allows at least two decentral network nodes 103.1-6 to establish a peer-to-peer communication channel between respective decentral network nodes 103.1-6.

[0104] The network nodes 103.1-6 may be computing nodes. The computing node may be any device or system that includes at least one physical and tangible processor, and a physical and tangible memory capable of having thereon computer-executable instructions that are executed by a processor. Computing nodes are now increasingly taking a wide variety of forms. Computing nodes may, for example, be handheld devices, monitoring systems, control systems, laptop computers, desktop computers, mainframes and / or data centers. The memory may take any form and depends on the nature and form of the computing node. The decentral network nodes 103.1-6 may be connected via a wired and / or wireless connection such as one of Ethernet, USB, LAN, WLAN and the like. Wireless communication may use, for example, WLAN, Wi-Fi, cellular, and / or Bluetooth. The decentral network nodes 103.1-6 may be configured to perform peer-to-peer data transactions, illustrated by the arrows 105 indicating data flow.

[0105] The decentral network nodes 103.1-6 may be configured as data consuming and / or providing network nodes. The decentral network nodes 103.1-6 may be configured to provide data to other network node(s) of the decentral network 102 and / or to consume data from other nodes of the decentral network 102. For instance, the decentral network node 103.1,3 associated with the monomer and / or polymer producer 101.1 or the polymer containing product producer 101.3 may be configured to provide chemical product data associated with properties of the polymer to downstream participants such as the plastic waste collector or sorter 101.5 or the recycling operator 101.6. Further for instance, the decentral network node 103.5,6 associated with the plastic waste collector or sorter 101.5 or the recycling operator 101.6 may be configured to access data from the network node 103.1-5 associated with upstream participants such as the monomer and / or polymer producer 101.1 or the polymer containing product producer 101.3.

[0106] The decentral network node(s) 103.1-6 may comprise computer-executable instructions configured to provide, consume and / or process data, such as chemical product data associated with the monomer, polymer, polymer-containing productor article produced or processed within the circular loop 100. The network node(s) may run a data providing service configured to provide data to another decentral network node 103.1-6 of the decentral network 102. The decentral network node(s) 103.1-6 configured to provide data may be associated with a data owner or a data generating node associated with a material or product produced or processed within the circular loop 100. The decentral network node(s) 103.1-6 may be connected to one or more dedicated data storage(s) storing the data associated with material or product produced or processed in the circular loop 100 (see for example Fig. 8). The dedicated data storage(s) may be under14

[0107] control of the data owner or data generating node associated with the material or product produced or processed in the circular loop 100. The data owner may be the respective participant 101.1-6 of the circular loop 100, the data generating node 103.1-6 is associated with. The data generating node 103.1-6 may have access to the dedicated data storage(s). Access to data associated with material or product produced or processed within the circular loop 100 may hence be under control of the data owner the respective decentral network node 103.1-6 is associated with. This allows to retain full control over data associated with material or product produced or processed within the circular loop 100 by the data owner. At the same time this enables sharing of data associated with material or product produced or processed within the circular loop 100 under controlled conditions, for example by using appropriate protocols including authorization and authentication mechanisms or schemes to establish peer-to-peer communication.

[0108] The decentral network node 103.1-6 configured to consume data may comprise computer-executable instructions for accessing and / or processing data within the decentral network 102, such as data associated with material produced or processed within the circular loop 100 and provided by a decentral data providing network node 103.1-6. The decentral data consuming network node 103.1-6 may be controlled or owned by or associated with any upstream or downstream participant of the circular loop 100. For instance, the decentral data consuming network node 103.4 may be associated with polymer-containing product user 103.4 to allow access to monomer and / or polymer data associated with the supplied monomer and / or polymer of the monomer and / or polymer producer through the decentral data providing network node 103.1 associated with the monomer and / or polymer producer 101.1.

[0109] The decentral network 102 may include further decentral network nodes 103.1-6. The further decentral network nodes 103.1-6 may not be associated with further participants of the circular loop 100. The further nodes may be decentral infrastructure service nodes (not shown in Fig. 1). The decentral infrastructure service nodes may provide services for decentral participant nodes 103.1-6, such as verifying the identity of the decentral network participant nodes 103.1-6 prior to performing a data ex-change. The decentral network participant node(s) 103.1-6 may be associated with or include certificate(s), such as X.509 certifi-cate(s). The certificate(s) may be associated with an identity manager including e.g. a certificate issuing service and / or a dynamic provisioning service providing dynamic attribute tokens (e.g. OAuth Access Tokens). This way the decentral network node(s) 103.1-6 may be associated or connected to a unique identifier embedded in a X.509 certificate that identifies the respective decentral network node(s) 103.1-6. The information required to verify the certificate may be provided via an authentication registry associated with the certificate issuing service and / or a dynamic provisioning service. For instance, in the IDSA Reference Architecture Model, Version 3.0 of April 2019, a decentral data providing network node associated with the15

[0110] data owner, a Certification Authority (CA), a Dynamic Attribute Provisioning Service (DAPS) and a decentral data consuming network node associated with the data consumer are used to verify the identity prior to performing a data exchange (not shown).

[0111] The material or product produced by participant(s) 101.1-6 of the circular loop 100 may be associated with material or product data associated with properties of the material or product produced by participant(s) 101.1-6 of the circular loop 100. The material or product data may be provided for access by the decentral data providing network node 103.1-6 associated with the material or product producer. Access to the material or product data may be controlled by the decentral data providing network node 103.1-6. The material or product data may be accessed by decentral data consuming network node(s) 103.1-6 associated with further participants 101.1-6 of the material loop 100, such as any downstream participant 101.1-6.

[0112] The data flow 105 between decentral network nodes 103.1-6 may be directly or indirectly associated with the material flow 104, 106 between the participants 101.1-6 of the material loop 100. For instance, the data flow 105 may be directly associated with the material flow 104, 105, if data associated with a chemical product provided from the chemical product producer 103.1 to the chemical product user 103.2 is accessed by a decentral data consuming network node 103.1-6 associated with said chemical product user 101.2. For instance, the data flow 105 may be indirectly associated with the material flow 104, 106, if data associated with a chemical product produced by chemical product producer 103.1 is accessed by a decentral data consuming network node 103.1-6 associated with the recycling system operator 101.6.

[0113] Data transactions between decentral network nodes 103.1-6 may be based on a decentral identifier associated with the material or product data to be accessed. The decentral identifier may be associated with the physical entity of the material or product. The decentral identifier may be uniquely associated with the physical entity of the material or product. The decentral identifier may uniquely identify the material or product within the decentral network 102. The decentral identifier may be associated with further decentral identifiers), such as decentral identifier(s) of material(s) or product(s) used to produce the end product. This may allow to track the material(s) or product(s) used to produce a product, such as an end-product. The decentral identifier may be included in a material passport associated with the material or product as is described in more detail in the context of Fig 8.

[0114] Fig. 2 illustrates the flow chart for an example of an intelligent sorting method that may be implemented in the sorting system with decentral network interface.230774

[0115] 16

[0116] The waste articles may include an identification element associated with the decentral identifier per waste article. The identification element may be detected. The identification element may be an optical identification element such as a QR code or an electronic identification element such as an RFID tag. The reader may detect the identification element. The decentral identifier per waste article may be provided based on such detection. For example, a QR code may be detected by the optical reader. The reader may translate the QR-code to the decentral identifier. Alternatively, the reader may translate the QR-code into an identifier of the QR-code. The identifier may be provided to the decentral identifier management system of the decentral network. The decentral identifier management system may store identifier pairs of QR-code identifiers and decentral identifiers. The decentral identifier connected to the provided QR-code identifier may be provided. Similarly, an RFID tag identifier may be used. Further for example, the identification element may include a physical tracer material contained in the waste article. The identification element may be detected by a method detecting the tracer, such as X-ray detector configured to detect tracer molecules or metals. The tracer identification may be provided to the decentral identifier management system. Based on the tracer identification the decentral identifier may be provided by the decentral identifier management system.

[0117] If no identifier element is detected, control data may be generated to separate the waste article without ID element detection from the waste articles for which the identifier element is detected. The waste article without ID element detection may be fed to a sensor-based sorting system.

[0118] Based on the decentral identifier article property data associated with the waste article such as composition property, material composition and / or article history data may be gathered by accessing decentral network nodes 103.1-6 of the decentral network 102, that are associated with other participants 103.1-6 of the decentral network 102 such as illustrated in the context of Fig. 1.

[0119] The material composition data may be gathered from one or more decentral network node(s) 103.1-6 of the decentral network 102. For example, the monomer(s), polymer(s) and / or additive(s) present in the waste article may be provided by the decentral network node 103.3 associated with the polymer-containing product producer 101.3. Further for example, the monomer type, polymer type and / or additive type present in the waste article may be provided by the decentral network node 103.3 associated with the polymer-containing product producer 101.3. Further for example, the plastic material(s) present in the waste article may be provided by the decentral network node 103.3 associated with the polymer-containing product producer 101.3. Further for example, the monomer(s) and / or polymer(s) present in the waste article may be provided by the decentral network node 103.1 associated with the monomer and / or polymer producer 101.1. Further230774

[0120] 17

[0121] for example, the monomer(s), polymer(s) and / or additive(s) present in the waste article may be provided by the decentral network node 103.2 associated with the monomer and / or polymer user 101.1. To provide data associated with properties of the waste article from decentral network node(s) 103.1-4, the decentral identifier associated with the waste article may be linked to decentral identifiers associated with physical entities of the materials or products used to produce the waste article. The decentral identifier(s) associated with the monomer(s), polymer(s) and / or additive(s) used to produce the waste article may be linked to the decentral identifier associated with the waste product. The linking of the decentral identifiers along the material flow allows fortracking the composition and / or history of the polymer-containing product. The linking of identifiers may be resolved by the identifier management system of the decentral network 102 based on the decentral identifier associated with the waste article. Depending on the data requested by the decentral network node 103.5 associated with the plastic waste sorter and / or collector 101.5 the identifier management system may resolve linked identifiers and manage the process for accessing the respective data providing network node(s). The linking of identifiers may be provided on providing the decentral identifier associated with the waste article. For example, the identifier linking may be part of the article passport associated with the plastic-containing waste article. The article passport may include the decentral identifier associated with the waste article, the digital representation or link to the article property data and the decentral identifier(s) associated with the monomer(s), polymer(s) and / or additive(s) used to produce the waste article and linked to the decentral identifier associated with the waste product.

[0122] The article history data may be gathered from one or more decentral network node(s) 103.1-6 of the decentral network 102. For example, the origin, application and / or use of the waste article may be provided by the decentral network node 103.3 associated with the polymer-containing product producer 101.3. Further for example, the origin, application and / or use of the waste article may be provided by the decentral network node 103.4 associated with the polymer-containing product user 101.4. As described above for the material composition, the decentral identifier associated with the waste article may be linked to further decentral identifiers associated with stages of the waste article along the material flow 04.

[0123] Based on the material composition such as composition property and / or the article history data fraction control data may be generated. Waste articles may be sorted according to the fraction control data. For example, the at least one subset of the one or more waste identifier(s) may be provided by the chemical producer node. The at least one subset of the one or more waste identifier(s) may be generated based on on the target composition and / or classification instructions configured to match the material composition to a pre-determined fraction for such material composition. The pre-determined fraction may specify the material type(s), range(s) for material quantity per type, specific compounds contained in the material, the230774

[0124] 18

[0125] exclusion of specific compounds contained in the material, recycled material content, bio-based material content or combinations thereof. The pre-determined waste fraction may for example specify the material types to be included in the waste fraction depending on the recycling process and further use of the recy-clate. The pre-defined waste fraction may include at least one of four types of waste fractions. The type of waste fraction may be tailored to pyrolysis to produce hydrocarbon recyclate, for gasification to produce recyclate mixture containing hydrogen and carbon monoxide, for depolymerization to produce monomer recyclate, to dissolution to produce polymer recyclate or to mechanical recycling to produce polymer recyclate. A first waste fraction may specify a mixed plastic waste and polyolefin-rich fraction e.g. including PE, PS and / or PP, for pyrolysis as recycling process to produce hydrocarbon recyclate. A second waste fraction may specify a mixed plastic waste and polyolefin-depleted fraction e.g. including polymers containing oxygen or halogens such as PET, PVC or compounds containing brominated flame retardants, for gasification as recycling process to produce the recyclate mixture including at least hydrogen and carbon monoxide as recyclate. A third waste fraction may specify a uniform plastic waste fraction e.g. including PP, PE or PS, for depolymerization as recycling process to produce the monomer recyclate. A fourth waste fraction may specify a uniform plastic waste fraction e.g. including PP, PS or PA, for dissolution as recycling process to produce the polymer recyclate. Further waste fractions may specify uniform or mixes waste fractions for mechanical recycling.

[0126] The property data and / or decentral IDs per waste article per fraction may be gathered. The gathered decentral IDs and / or property data per fraction may be assigned to a fraction identifier, such as a decentral identifier per fraction. The gathered decentral identifiers and / or property data may be aggregated to fraction data. Fraction data may relate to a fraction composition and / or a fraction history. For example, the composition data per decentral identifier may be aggregated by composition, compounds contained in the waste fraction and / or their respective quantities, such as amounts. Further for example, the article history per decentral identifier may be aggregated to signify the origin, application, or use of the materials. This may include origin such as specific product manufacturers. This may include application types such as bottle, medical packaging or the like. This may include uses in food industry.

[0127] Based on the classification and / or the aggregated fraction data, the recycling process may be determined and / or assigned to the fraction identifier. The classification may include a recycling process specific classification. For example, the material composition per fraction may be specified to include a first class of plastics or compounds and to exclude a second class of plastics or compounds. The first class may include polyethylene (PE), polypropylene (PP) and / or polystyrene (PS). For pure PE, PP, PS streams mechanical recycling may be specified as recycling process. In addition, the number of recycling loops may be part of the230774

[0128] 19

[0129] pre-determined classification. For example, a threshold value for the number of recycling loops may be specified to collect pure PE, PP, PS streams that are not suitable for mechanical recycling and need to be assigned to chemical recycling processes.

[0130] The second class of plastics may exclude plastics not suitable for chemical recycling via pyrolysis and contaminants impeding the quality of the recyclate. Plastics not suitable for chemical recycling via pyrolysis may include polyvinylchloride (PVC) and / or polyethylene terephthalate (PET). The second class of compounds may exclude contaminants specifically for use of pyrolysis oil in stream crackers. Contaminants may include sulfur, halogens, oxygen, phosphorus, metals and inorganics such as aluminum, antinomy, barium, calcium chromium, copper, iron, potassium, sodium, lead, silicon, titanium, zinc, arsine, mercury, nickel, vanadium, or combinations thereof. The presence of these compounds in the sorted fraction and hence on pyrolysis oil produced from such fraction can have adverse effect on steam cracker operation. Thus, by excluding such substances or contaminants for recycling already at the sorting stage of plastic waste reliably through the tracked composition data accessible via the decentral network results in higher quality waste fractions, pyrolysis oil and when fed to a cracker in safe and reliable operation.

[0131] Per fraction a fraction ID and a recycling process ID specifying a recycling process, such as mechanical, chemical and / or thermal (incineration), may be assigned. The fraction ID may include a decentral identifier. The recycling process ID may include a decentral identifier. The decentral identifier(s) may be associated with the aggregated fraction data.

[0132] The fraction data may be provided for access to decentral network node(s) 103.1-4,6. The fraction data may be provided by providing the decentral identifier associated with the fraction to the decentral network 102. The fraction data may be provided by the decentral network node 103.5 associated with the plastic waste sorter and / or collector 101.5. The fraction data may be stored in a dedicated storage associated with the plastic waste sorter and / or collector 101.5. Access to the fraction data may be provided by providing a representation linking or pointing to the fraction data. The decentral I D(s) and the representation linking to or pointing to the aggregated fraction data stored in dedicated storage associated with the plastic waste collector and / or sorter 101.5 may be provided to the decentral network 102 for access by nodes associated with other participants of the decentral network 102. The fraction data may be provided by the decentral data providing service of the decentral network node 103.5 associated with the plastic waste sorter and / or collector 101.5. The fraction data may be accessed by the decentral data consuming service of the decentral network node 103.6 associated with the recycling system operator 101.6 or the monomer and / or polymer producer.Figs. 3 a,b illustrate example data structures used for the intelligent sorting method based on material composition data and / or article history data accessible byway of the decentral network interface.

[0133] Fig. 3a illustrates the data structure based on the material composition data. The material composition data may be retrieved based on the decentral identifier from nodes 103 associated with participants 101 of the decentral network 102. The material passport may be retrieved from the node(s) 103 associated with partic-ipant(s) 101 of the decentral network 101 that own the respective data. For example, the waste article data packages 1 , 2 and 3 may be retrieved from the decentral network 102. The waste article data packages 1 , 2 and 3 may specify the material composition per waste article. The pre-defined classification may be configured to sort PE containing articles with a level of contaminants below a threshold value, e.g. contaminant mass fraction below 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1% or 0.5%, into one waste fraction. The pre-defined classification may be configured to sort PE containing articles without contaminants such as nitrogen or chlorine, into a first waste fraction. The pre-defined classification may be configured to sort PET articles into a second waste fraction. This way the quality of the sorted waste fraction can be increased with respect to the re-use of the waste fraction.

[0134] Fig. 3b illustrates a data structure based on the article history.

[0135] The article history data may be retrieved based on the decentral identifier from decentral network nodes 103 associated with participants 101 of the decentral network 102. The material passport may be retrieved from the node(s) 103 associated with participant(s) 101 of the decentral network 102 that own the respective data. For example, the article data packages 1, 2 and 3 may be retrieved from the decentral network 102. The article data packages 1 , 2 and 3 may specify the material composition and the article history per waste article. The article history may specify the use, application, and origin of the waste article. In the example of Fig. 3b this may include the use in food industry, the manufacturer, the application in a closed loop PET bottle scheme and the loop count. The pre-defined classification may be configured to sort PE containing articles by material composition as explained for example in the context of Fig. 3a. In addition, the waste articles may be sorted by use. For example, food industry use may require the first waste fraction to be directed to a cleaning step for cleaning the articles from biological residues. The pre-defined classification may be configured to sort PET containing articles by material composition as explained for example in the context of Fig. 3a. In addition, the pre-defined classification may be configured to sort according to application PET bottles in the closed loop recycling scheme and the loop count. Closed loop PET bottles21

[0136] can be sorted to the waste fraction for mechanical recycling, if the loop count does not exceed a threshold value such as 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15.

[0137] For bottles exceeding the loop count threshold, the pre-defined classification may sort the PET bottles to the waste fraction for chemical recycling, since the material degradation requires chemical recycling to renew the loop count of the material. This way the waste articles can be sorted with more depth in sorting allowing for tailored processing. The quality of the sorted waste fraction can be increased with respect to the re-use of the waste fraction.

[0138] Fig. 4 illustrates an example flow chart of a methods for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for production.

[0139] The method for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for chemical production may be executed or executable in a decentral or distributed network as illustrated e.g. in Figs. 12a-b. The method for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for chemical production may be executed or executable by at least one node of a distributed and / or decentral network associated with one or more chemical production plants. The method for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for chemical production may provide the at least one subset of the one or more waste identifier(s) to control and / or monitor collection, sorting and / or recycling steps or stages preceding the chemical production step or stage. This way waste streams can be monitored and / or controlled to fulfill the requirements of chemical production.

[0140] At least one target composition property associated with recyclates to be used as input material for one or more chemical production plant(s) may be provided. The target composition property may be provided by the operator of the industrial production for which the recyclate is to be used. The target composition property may be associated with one composition property or more composition properties of the recyclate to be used by at least one industrial production, such as chemical production process. The target composition property may specify constraints or boundaries for the one composition property or more composition properties of the recyclate to be used by at least one industrial production, such as chemical production process. The target composition property may be associated with substances or compounds to be excluded and / or contaminants or critical substances or compounds. The target composition property may may specify constraints or boundaries for contaminants or critical substances or compounds. The composition property may specify at least one or more critical substance(s) and their respective critical quantity, such as a22

[0141] threshold or range quantity, for the recyclates. Critical may refer to any characteristic or substance that may impede the processing of the recyclate, negatively affect the processing of the recyclate, e.g. by reducing yields, and / or the negatively impact the equipment the recyclate is processed by, e.g. through degradation. For example, such substances or contaminants may be monitored and / or controlled at the sorting and / or recycling stage reliably through the tracked composition data accessible via the decentral network. This way higher quality waste fractions, recyclate from such fractions such as pyrolysis oil and with that safe and reliable operation of the industrial production such as cracker operation may be achieved.

[0142] One or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) may be provided. One or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) may include one or more decentral identifier(s) uniquely related to the one or more waste articles and / or one or more sorted waste fraction(s). The one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) may be uniquely linked or related to composition data including the composition property of the associated one or more waste articles and / or one or more sorted waste fraction(s). The one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) may allow for discovery and / or access to composition data in or via a distributed and / or decentral network as illustrated e.g. in the context of Figs. 12a-c. One or more waste identifier(s) may be provided by accessing one or more nodes of the decentral or distributed network such as the nodes associated with sorter or recycler or a distributed or decentral storage configured to offer data related to one or more waste articles and / or one or more sorted waste fraction(s).

[0143] Based on the one or more waste identifier(s) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) may be gathered. The at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) may be gathered by accessing one or more nodes of the decentral or distributed network. E.g. the node associated with sorter or recycler or a distributed or decentral storage configured to offer data related to one or more waste articles and / or one or more sorted waste fraction(s) may be requested to provide the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s).

[0144] Based on the target composition property, the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s), at least one subset of the one or more waste identifier(s) and a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s) may be determined. For generating the at least one23

[0145] subset of the one or more waste identifier(s) or the respective a total composition property associated with at least one waste mixture with total composition property fulfilling the target composition property different approaches and options may be used. The total composition property may be generated based on scoring approaches, optimization approaches, physiochemical modelling approaches, data-driven modelling approaches and / or hybrid approaches combining physiochemical and data-driven modeling.

[0146] The scoring approach may include determining a score per one or more waste articles and / or one or more sorted waste fraction(s). For the scoring, the properties required for the industrial production may be selected and optionally prioritized. The score per one or more waste articles and / or one or more sorted waste fraction(s) may include determining a score per property of the one or more waste articles and / or one or more sorted waste fraction(s) and the respective total composition property specified by the target waste mixture that measures the distance of the property of the one or more waste articles and / or one or more sorted waste fraction(s) to the respective total composition property specified by the target waste mixture. Based on the per property score an accumulated and optionally normalized score per waste identifier may be determined. The per property scores may further include a penalty depending on the relevance of the specific property for the industrial production, e.g. if the property is required or optional. Based on the penalized score the accumulated score may be determined. Based on the accumulated score the one or more waste articles and / or one or more sorted waste fraction(s) suitable for the industrial production may be selected for mixing. The scores may be normalized e.g. to a relative scale of percentage.

[0147] The optimization approach may include determining weighted quantities of one or more waste article(s) and / or one or more sorted waste fraction(s) depending on the composition properties per waste identifier depending on or under the constraints of the target composition property. Depending on or under the constraints of the target composition mixture may refer to the weighted sum of at least part of the composition properties of the one or more waste articles and / or one or more sorted waste fraction(s) complying at least in part with the target composition properties of the recyclate or the recycled input material for the at least one industrial production. Based on the weights, the one or more waste articles and / or one or more sorted waste fraction(s) suitable for the industrial production and the quantity of one or more waste articles and / or one or more sorted waste fraction(s) determined by the weight may be selected for mixing. In mathematical terms an objective function or cost function may be minimized under defined constraints. For example, based on the weights the waste article(s) and / or one or more sorted waste fraction(s) suitable for the industrial operation and the quantity of waste article(s) and / or one or more sorted waste fraction(s) determined by the weight may be selected for mixing. In mathematical terms an objective function or cost function may be minimized under defined constraints:24

[0148] Cost function

[0149]

[0150] >

[0151] with C; = 1 / tj , f 'fwj = 1, ' wjxij< ti Vi and 0 < Wj < Uj

[0152] Default value for tty =1

[0153] Output: vector Wj of weights

[0154] i=1 denote the composition properties

[0155] j=1 , .. , N_s denote the waste articles / fractions

[0156] x_ij : Matrix of properties for waste articles / fractions

[0157] tj: Vector of allowed properties in the waste mixture according to the target composition

[0158] Outputs:

[0159] w_j: fraction of waste articles / fractions for waste mixture

[0160] The physiochemical modelling approach may include determining the subset of waste identifiers by using a first principles calculation to determine based on the properties per one or more waste articles and / or one or more sorted waste fraction(s) the properties of the waste mixture. The data-driven approach may include determining the subset of waste identifiers by providing the properties per one or more waste articles and / or one or more sorted waste fraction(s) to a data-driven model parametrized based on historical data including mixture data, target mixture data and waste data, such as properties per one or more waste articles and / or one or more sorted waste fraction(s). Additionally or alternatively, hybrid approaches or multi-criterial approaches may be used to determine mixture data.

[0161] In addition to the properties per one or more waste articles and / or one or more sorted waste fraction(s), further parameters such as the available quantity per one or more waste articles and / or one or more sorted waste fraction(s) may be included in any of the approaches for generating mixture data as lined out herein.

[0162] Once the total composition property is determined to lie within the pre-defined range or thresholds of the target composition property, the at least one subset of the one or more waste identifier(s) and optionally the total composition property may be provided. The at least one subset of the one or more waste identifier(s)230774

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[0164] and optionally the total composition property may be provided for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for chemical production. Based on the one subset of the one or more waste identifier(s) the input to one or more sorting and / or recycling step(s) to produce one or more recyclates as input to chemical production plant(s) may be monitored and / or controlled.

[0165] Fig. 5 illustrates an example of the waste sorting, recycling and production facility connected to operating apparatuses configured to access and share data via a decentral network.

[0166] The industrial production may use recyclates as input materials for the industrial production, such as chemical production. The industrial production may be associated with an operating apparatus capable for executing the methods disclosed herein, e.g. in the context of Fig. 4. The operating apparatus may be configured to provide at least one target composition property associated with recyclates to be used as input material for one or more chemical production plant(s) as e.g. described in the context of Fig. 4.

[0167] The operating apparatus, e.g. associated with the industrial production, may be configured to gather and / or provide one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s). For example, the operating apparatus may be configured to retrieve one or more waste identifier(s) from one or more nodes associated with collecting, sorting and / or recycling facilities. Further for example, the operating apparatus may be configured to retrieve one or more waste identifier(s) from one or more nodes associated with distributed and / or decentral storage offering the one or more waste identifier(s) available by collecting, sorting and / or recycling facilities.

[0168] The collecting, sorting and / or recycling facilities may be associated with an operating apparatus capable for executing the methods disclosed herein, e.g. for providing one or more waste identifier(s). The operating apparatus, e.g. associated with the collecting and / or sorting facility, may be configured to provide one or more waste identifier(s) and at least one composition property associated with one or more waste articles. The operating apparatus, e.g. associated with the recycling facility, may be configured to provide one or more waste identifier(s) and at least one composition property associated with one or more waste fractions.

[0169] The operating apparatus, e.g. associated with the industrial production, may be configured to gather based on the one or more waste identifier(s) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s). The operating apparatus, e.g. associated with the industrial production, may be configured to gather based on the one or more waste identifier(s) at least one230774

[0170] 26

[0171] composition property the operating apparatus, e.g. associated with the collecting, sorting and / or recycling facility. The operating apparatus, e.g. associated with the industrial production, may be configured to retrieve at least one composition property from one or more nodes associated with distributed and / or decentral storage offering the one or more waste identifier(s) available by collecting, sorting and / or recycling facilities. The composition property per one or more waste articles and / or one or more sorted waste fraction(s) may relate to the material composition of the one or more waste articles and / or one or more sorted waste fraction(s). For example, the composition property may specify chemical compounds and / or substances contained in the one or more waste articles and / or one or more sorted waste fraction(s), combination of substances and / or compounds contained in the one or more waste articles and / or one or more sorted waste fraction(s), composite material(s) contained in the one or more waste articles and / or one or more sorted waste fraction(s), combination of composite materials contained in the one or more waste articles and / or one or more sorted waste fraction(s), foamed materials contained in the one or more waste articles and / or one or more sorted waste fraction(s), combination of foamed materials contained in the one or more waste articles and / or one or more sorted waste fraction(s) or combinations thereof. The composition property may further include contaminants for recycling in relation to one or more recycling process(es), degradation level, recyclate content, monomer content and / or polymer content, content of certain compounds or substances or any combinations thereof.

[0172] The operating apparatus, e.g. associated with the industrial production, may be configured to determine based on the target composition property, the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) and at least one subset of the one or more waste identifiers) a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s). The at least one subset of the one or more waste identifier(s) may be determined based on the related or linked at least one composition property associated with the respective one or more waste articles and / or one or more sorted waste fraction(s). The total composition property may be determined for one or more subsets of the one or more waste identi-fier(s) based on the at least one composition property per waste identifier(s). The total composition property may be determined for multiple subsets of the one or more waste identifier(s) based on the at least one composition property per waste identifier(s). The subsets of the one or more waste identifier(s) having total composition property fulfilling the target composition property may be selected. The subsets of the one or more waste identifier(s) may be determined by determining the total composition property lies within the constraints provided by the target composition property. The subset of the one or more waste identifier(s) may be generated by determining weighted quantities of waste articles and / or fractions depending on the one property or more properties per waste article and / or fraction and the target composition property. The230774

[0173] 27

[0174] composition property or the multiple properties of the waste articles or fractions may correspond at least in part to the property or the multiple properties of the waste mixture as specified by the target composition property.

[0175] The operating apparatus, e.g. associated with the industrial production, may be configured to provide the at least one subset of the one or more waste identifier(s) and optionally the total composition property for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for chemical production. In particular, the determined subset of the one or more waste identifier(s) may be provided to one or more nodes associated with collecting, sorting and / or recycling facilities. This way the monitoring and / or controlling of the at least one composition property is pushed to the steps preceding the production, such as the collecting, sorting or recycling of waste articles and / or fractions.

[0176] For example, the operating apparatus, e.g. associated with the collecting and / or sorting facility, may be configured to receive the at least one subset of the one or more waste identifier(s) e.g. from the operating apparatus associated with the industrial production. The operating apparatus, e.g. associated with the collecting and / or sorting facility, may be configured to generate fraction control data for sorting waste articles based on the at least one subset of the one or more waste identifier(s). The operating apparatus, e.g. associated with the collecting and / or sorting facility, may be configured to provide fraction ID per fraction sorted based on fraction control data and assign fraction ID to fraction data associated with sorted fractions. The operating apparatus, e.g. associated with the collecting and / or sorting facility, may be configured to provide the fraction ID and fraction data related to the fraction ID, such as fraction composition, to the operating apparatus, e.g. associated with the recycling facility, steps or stage.

[0177] Further for example, the operating apparatus, e.g. associated with the recycling facility, steps or stage, may be configured to receive the at least one subset of the one or more waste identifier(s) e.g. from the operating apparatus associated with the industrial production. The operating apparatus, e.g. associated with the recycling facility, steps or stage, may be configured to generate recyclate control data for monitoring and / or controlling input waste fractions based on the at least one subset of the one or more waste identifier(s). The operating apparatus, e.g. associated with the recycling facility, steps or stage, provide recyclate ID per recycled waste fractions based on recyclate control data and assign recyclate ID to recyclate data associated with recyclate. The operating apparatus, e.g. associated with the recycling facility, may be configured to provide the recyclate ID and recyclate data related to the recyclate ID, such as recyclate composition, to the operating apparatus, e.g. associated with the production steps or stage.230774

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[0179] Fig. 6 illustrates an example of a method or apparatus for providing material composition data and / or article history data by way of the decentral network.

[0180] The waste article 900 as provided by the article user or producer may be provided in association with a material passport. The article passport may relate to an article identifier. The article identifier may include one or more decentral identifier(s). The decentral identifier may be an identifier in the decentral network 102 allowing for data exchange via the decentral network 102. Data exchange may include discovery of the decentral identifier for decentral network node(s) 103 associated with participant(s) 101 of the decentral network 102, authentication of decentral network node(s) 103 associated with participant(s) 101 of the decentral network 102 and / or authorization of data transfers via a peer-to-peer communication between decentral network node(s) 103 associated with participant(s) 101 of the decentral network 102.

[0181] The article passport may include or be related to data related to the article such as article property data associated with the article properties like composition and / or article history data. The article passport may include a digital representation of the article data associated with the article 900. The article passport may further include or relate to authentication and / or authorization information linked to the article identifier. The authentication and / or authorization information may be provided for authentication and / or authorization of a data providing service and / or data consuming service implemented by decentral network node(s) 103.5, 103.3. The article identifier may include or relate to a decentral identifier, that is uniquely associated with the article. The decentral identifier may be connected to the digital representation of the of the article data associated with the article 104. The digital representation may include a representation for accessing the article data or parts thereof. The decentral identifier may include a Universally Unique I Dentifier (UUID) or a Digital I Dentifier (DID). The decentral identifier may include any unique identifier uniquely associated with a data owner and / or article.

[0182] The data owner may be the producer of the article. Via the decentral identifier and its unique association with the data owner and / or article access to the article data may be controlled by the data owner.

[0183] The article passport including the digital representation of article data may be stored in a decentral data base 910. The article data may be stored in a data base 902 associated with the data owner, such as the producer of the article 900.230774

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[0185] The article 904 may be physically delivered to the user using the article and disposing the article. The article 900 may be physically collected and / or sorted by the article collector and / or sorter. The article may be connected with a QR-code having encoded the article identifier. The user, collector or sorter of the article 904 may read the QR-code through a QR-code reader 906. The article identifier may be provided to a data base 910 associated with the producer producing the article 900. In other embodiments the producer producing the article 900 may retrieve the article identifier through the decentral data base 910.

[0186] The data owner in this example may be the article producer, any intermediate product producer producing an intermediate product for the article or any producer producing a product based on the article. The data owner may comprise any entity generating data. The data generating node may be coupled to the data owner or the entity owning or producing physical products from or for which data is generated. The data may be generated by a third-party entity on behalf of the entity owning physical articles from or for which data is generated.

[0187] The data consuming service implemented by node 103.5 may comprise computer-executable instructions for accessing and / or processing data, such as article data, associated with the data owner. The data providing service implemented by node 103.3 may comprise computer-executable instructions for providing and / or processing data, such as article data, associated with the data owner for accessing and / or processing by the data consuming service implementing node 103.5.

[0188] Based on the received article identifier a request to access the article data related to the article identifier may be triggered by the data consuming service implemented by node 103.5 as signified by arrow 912. The article identifier may be provided to the data providing service implemented by node 103.3 associated with or of the producer of the article 900. In addition, authentication and / or authorization information may be provided.

[0189] The request may be authenticated and / or authorized to access the article data related to the article identifier. Based on successful authorization and / or authentication access to the article data related to the article identifier may be granted.

[0190] For access the article identifier may be provided to the data providing service implemented by node 103.3 as signified by arrow 912. The data providing service implemented by node 103.3 may use the received article identifier to retrieve the article data associated with the article 900 from a dedicated storage 902 as signified by arrows 918 and 920. The article data associated with the article 904 provided to the data30

[0191] providing service implemented by node 103.5 may be provided to the data consuming service implemented by node 103.5 as signified by arrow 916. The article data associated with the article 904 may be stored in the dedicated storage or data base 908 associated with the user, collector or sorter of the article 904 as signified by arrow 922.

[0192] Through the article identifier or decentral identifier, the article data can be uniquely associated with the article 900, 904. Through the decentral network the article data may be transferred between the producer of the article and the user, collector or sorter of the article. This way the article data can be shared with unique association to the article and without central intermediary directly between the players of the decentral network 102.

[0193] This allows for controlled transparency of article data across the material loop 100.

[0194] Fig. 7 illustrates an example of the pre-defined classification configured to separate plastic articles by material composition, article history and recycling process.

[0195] The subset of article or fraction identifiers may be provided to the sorting system via an interface configured to retrieve data from node(s) 103 of a decentral network 102. The subset may be determined based on the pre-defined classification that may be configured to sort waste articles according to the composition property as provided by the subset of article or fraction identifiers. The pre-defined classification may be configured to sort the waste articles or fractions according to the subset of article or fraction identifiers into waste fraction(s) to used for recycling through specific recycling processes based on the target composition. The pre-defined classification may be additionally configured to assign the recycling process to the respective sorted waste fraction or recyclate. Recycling processes may include mechanical, chemical and / or solventbased recycling processes. The chemical recycling process types may include depolymerization, pyrolysis, gasification or the like. The solvent-based recycling process type may include dissolution. The different recycling process types may be applicable to different fraction compositions. For example, PET that is not usable for mechanical recycling owing to degradation as e.g. specified by loop counts, may be assigned depolymerization as recycling process type. The depolymerization process may be further defined with regard to the depolymerization process type such as polycondensation via hydrolysis, glycolysis, methanoly-sis or transesterification. Further for example, fractions including mixed waste with limited oxygen content such as PE, PP, PS, may be assigned pyrolysis as recycling process type. The pyrolysis process may be further defined with regard to pyrolysis type based on operating conditions such as temperature, pressure, residence time, catalyst or thermal profiles. Further for example, fractions including mixed waste and biomass with oxygen content may be assigned gasification as recycling process type. The gasification process31

[0196] may be further defined with regard to gasification type based on operating conditions such as temperature. Further for example, fractions including contaminated waste of e.g. PP, PS, LDPE, PA or multi-layer films may be as-signed dissolution as recycling process type. The dissolution process may be further de-fined with regard to dissolution type based on target polymer.

[0197] As illustrated in Fig. 7 the sorted fractions IDs may be assigned to recycling process IDs. The fraction ID may include or relate to the decentral identifier(s) of the fraction. The fraction ID and associated fraction data may be provided for access by decentral network node(s) 103 of the decentral network 102 by the decentral network node 103.3 associated with the sorter 101.3 sorting the waste. The recycling process ID in association with the fraction ID may also be provided for access by decentral network node(s) 103 of the decentral network 102 by the decentral network node 103.3 associated with the sort-er 101.3 sorting the plastic waste stream. The fraction ID and recycling process ID may be accessed by the decentral network node 103.5 of the recycling system operator 101.5. The recycling system operator 103.5 may based on the fraction ID retrieve the fraction data and / or recycling process ID from the decentral network node 103.4 associated with the recycling system operator. The recycling system operator 103.5 may store the fraction data and / or recycling process ID in a dedicated storage associated with the recycling system operator 103.5. Based on the fraction ID, fraction data and the recycling process ID the recycling process may be operated by the recycling system operator. The fraction data may be used to aggregate recyclate data. Re-cyclate IDs may be assigned to the recyclate produced from respective fractions. This way not only the sorting process but also the recycling process may be monitored and / or controlled.

[0198] Figs. 12a to 12c illustrate different computing environments, central, decentral and distributed. The methods, apparatuses, computer elements of this disclosure may be implemented in decentral or at least partially decentral computing environments. In particular, for data sharing or ex-change in ecosystems of multiple players different challenges exist. Data sovereignty may be viewed as a core challenge. It can be defined as a natural person’s or corporate entity’s capability of being entirely self-determined with regard to its data. To enable this particular capability related aspects, including requirements for secure and trusted data exchange in business ecosystems, may be implemented across the chemical value chain. In particular, chemical industry requires tailored solutions to deliver chemical products in a more sustainable way by using digital ecosystems.

[0199] Fig. 8a illustrates an example embodiment of a centralized computing system 1200 comprising a central computing node 1201 (filled circle in the middle) and several peripheral computing nodes 1201.1 to 1201.n (denoted as filled circles in the periphery). The term “computing system” is defined herein broadly as230774

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[0201] including one or more computing nodes, a system of nodes or combinations thereof. The term “computing node” is defined herein broadly and may refer to any de-vice or system that includes at least one physical and tangible processor, and a physical and tangible memory capable of having thereon computer-executable instructions that are executed by a processor. Computing nodes are now increasingly taking a wide variety of forms. Computing nodes may, for example, be handheld devices, production facilities, sensors, monitoring systems, control systems, appliances, laptop computers, desktop computers, mainframes, data centers, or even devices that have not conventionally been considered a computing node, such as wearables (e.g., glasses, watches or the like). The memory may take any form and depends on the nature and form of the computing node.

[0202] In this example, the peripheral computing nodes 1201.1 to 1201.n may be connected to one central computing system (or server). In another example, the peripheral computing nodes 1201.1 to 1201.n may be attached to the central computing node via e.g. a terminal server (not shown). The majority of functions may be carried out by, or obtained from the central computing node (also called remote centralized location). One peripheral computing node 1201.n has been expanded to provide an overview of the components present in the peripheral computing node. The central computing node 1201 may comprise the same components as described in relation to the peripheral computing node 1201.n.

[0203] Each computing node 1201, 1201.1 to 1201.n may include at least one hardware processor 1202 and memory 1204. The term “processor” may refer to an arbitrary logic circuitry configured to per-form basic operations of a computer or system, and / or, generally, to a device which is configured for performing calculations or logic operations. In particular, the processor, or computer processor may be configured for processing basic instructions that drive the computer or system. It may be a semi-conductor based processor, a quantum processor, or any other type of processor configures for processing instructions. As an example, the processor may comprise at least one arithmetic logic unit ("ALU"), at least one floating-point unit ("FPU)", such as a math coprocessor or a numeric coprocessor, a plurality of registers, specifically registers configured for supplying operands to the ALU and storing results of operations, and a memory, such as an L1 and L2 cache memory. In particular, the processor may be a multicore processor. Specifically, the processor may be or may comprise a Central Processing Unit ("CPU"). The processor may be a (“GPU”) graphics processing unit, (“TPU”) tensor processing unit, ("CISC") Complex Instruction Set Com-puting microprocessor, Reduced Instruction Set Computing ("RISC") microprocessor, Very Long Instruction Word ("VLIW") microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets. The processing means may also be one or more special-purpose processing devices such as an Application-Specific Integrated Circuit ("ASIC"), a Field Programmable Gate230774

[0204] 33

[0205] Array ("FPGA"), a Complex Programmable Logic De-vice ("CPLD"), a Digital Signal Processor ("DSP"), a network processor, or the like. The methods, systems and devices described herein may be implemented as software in a DSP, in a micro-controller, or in any other side-processor or as hardware circuit within an ASIC, CPLD, or FPGA. It is to be understood that the term processor may also refer to one or more processing devices, such as a distributed system of processing devices located across multiple computer systems (e.g., cloud computing), and is not limited to a single device unless otherwise specified.

[0206] The memory 1204 may refer to a physical system memory, which may be volatile, non-volatile, or a combination thereof. The memory may include non-volatile mass storage such as physical storage media. The memory may be a computer-readable storage media such as RAM, ROM, EEPROM, CD-ROM, or other optical disk storage, magnetic disk storage, or other magnetic storage devices, or any other physical and tangible storage medium which can be used to store de-sired program code means in the form of computer-executable instructions or data structures and which can be accessed by the computing system. Moreover, the memory may be a computer-readable media that carries computer- executable instructions (also called transmission media). Further, upon reaching various computing system components, program code means in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to storage media (or vice versa). For example, computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a net-work interface module (e.g., a “NIC”), and then eventually transferred to computing system RAM and / or to less volatile storage media at a computing system. Thus, it should be understood that storage media can be included in computing components that also (or even primarily) utilize transmission media.

[0207] The computing nodes 1201, 1201.1...1201. n may include multiple structures 106 often referred to as an “executable component or computer-executable instructions”. For instance, memory 104 of the computing nodes 1201, 1201.1...1201.n may be illustrated as including executable component 106. The term “executable component” may be the name for a structure that is well under-stood to one of ordinary skill in the art in the field of computing as being a structure that can be software, hardware, or a combination thereof or which can be implemented in software, hard-ware, or a combination. For instance, when implemented in software, one of ordinary skill in the art would understand that the structure of an executable component include software objects, routines, methods, and so forth, that is executed on the computing nodes 101, 1201.1...1201.n, whether such an executable component exists in the heap of a computing node 1201, 1201.1...1201.n, or whether the executable component exists on computer-readable storage me-dia. In such a case, one of ordinary skill in the art will recognize that the structure of the executable component exists on a computer-readable medium such that, when interpreted by one or more processors of a230774

[0208] 34

[0209] computing node 1201, 1201.1...1201.n (e.g., by a processor thread), the computing node 1201,

[0210] 1201.1...1201 n is caused to perform a function. Such a structure may be computer-readable directly by the processors (as is the case if the executable component were binary). Alternatively, the structure may be structured to be interpretable and / or compiled (whether in a single stage or in multiple stages) so as to generate such binary that is directly interpretable by the processors. Such an understanding of example structures of an executable component is well within the understanding of one of ordinary skill in the art of computing when using the term “executable component”. Examples of executable components implemented in hardware include hardcoded or hard-wired logic gates, that are implemented exclusively or near-exclusively in hardware, such as within a field- programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or any other specialized circuit. In this description, the terms “component”, “agent”, “manager”, “service”, “engine”, “module”, “virtual machine” or the like are used synonymous with the term “executable component.

[0211] The processor 1202 of each computing node 1201, 1201.1...1201.n direct the operation of each computing node 1201, 1201.1...1201. n in response to having executed computer- executable instructions that constitute an executable component. For example, such computer-executable instructions may be embodied on one or more computer-readable media that form a computer program product. The computer-executable instructions may be stored in the memory 1204 of each computing node 1201, 1201.1...1201.n. Computerexecutable instructions comprise, for example, instructions and data which, when executed at a processor 1201, cause a general purpose computing node 1201, 1201.1...1201. n, special purpose computing node 1201. 1201.1...1201.n, or special purpose processing device to perform a certain function or group of functions. Alternatively or in addition, the computer-executable instructions may configure the computing node 1201. 1201.1...1201. n to perform a certain function or group of functions. The computer executable instructions may be, for example, binaries or even instructions that undergo some translation (such as compilation) before direct execution by the processors, such as inter-mediate format instructions such as assembly language, or even source code.

[0212] Each computing node 1201, 1201.1...1201. n may contain communication channels 1208 that allow each computing node 1201.1...1201.n to communicate with the central computing node 101, for example, a network (depicted as solid line between peripheral computing nodes and the central computing node in Fig.

[0213] 8a). A “network” may be defined as one or more data links that enable the transport of electronic data between computing nodes 1201, 1201.1...1201.n and / or modules and / or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computing node 1201, 1201.1...1201.n, the230774

[0214] 35

[0215] computing node 1201, 1201.1...1201. n properly views the connection as a transmission medium. Transmission media can include a network and / or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose or special-purpose computing nodes 1201, 1201.1...1201. n. Combinations of the above may also be included within the scope of computer-readable media.

[0216] The computing node(s) 1201, 1201.1 to 1201.n may further comprise a user interface system 1210 for use in interfacing with a user. The user interface system 110 may include output mechanisms 1210A as well as input mechanisms 1210B. The principles described herein are not limited to the precise output mechanisms 1210A or input mechanisms 110B as such will depend on the nature of the device. However, output mechanisms 1210A might include, for instance, displays, speakers, displays, tactile output, holograms and so forth. Examples of input mechanisms 110B might include, for instance, microphones, touchscreens, holograms, cameras, keyboards, mouse or other pointer input, sensors of any type, and so forth.

[0217] Fig. 8b illustrates an example embodiment of a decentralized computing environment 100’ with several computing nodes 1201.1’ to 1201. n’ denoted as filled circles. In contrast to the centralized computing environment 100 illustrated in Fig. 8a, the computing nodes 12201.1’ to 101. n’ of the decentralized computing environment are not connected to a central computing node 1201 and are thus not under control of a central computing node. Instead, resources, both hardware and software, may be allocated to each individual computing node 1201. T...1201. n’ (local or remote computing system) and data may be distributed among various computing nodes 1201.1 ’...1201.n’ to perform the tasks. Thus, in a decentral system environment, program modules may be located in both local and remote memory storage devices. One computing node 101’ has been expanded to provide an overview of the components present in the computing node 101’. In this example, the computing node 101’ comprises the same components as described in relation to Fig. 8a.

[0218] Fig. 8c illustrates an example embodiment of a distributed computing environment 1203. In this description, “distributed computing” may refer to any computing that utilizes multiple computing resources. Such use may be realized through virtualization of physical computing resources. One example of distributed computing is cloud computing. “Cloud computing” may refer a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services). When distributed, cloud computing environments may be distributed internationally within an organization and / or across multiple organizations. In this example, the distributed cloud computing environment 1203 may contain the following computing resources: mobile device(s) 1214, applications 1216, databases 1218, data storage 1220 and server(s) 1222. The cloud computing environment 1203 may be deployed as230774

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[0220] public cloud 1224, private cloud 1226 or hybrid cloud 1228. A private cloud 1224 may be owned by an organization and only the members of the organization with proper access can use the private cloud 1226, rendering the data in the private cloud at least confidential. In contrast, data stored in a public cloud 1226 may be open to anyone over the internet. The hybrid cloud 128 may be a combination of both private and public clouds 1224, 1226 and may allow to keep some of the data confidential while other data may be publicly available.

[0221] The present disclosure has been described in conjunction with preferred embodiments and examples as well. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed subject-matter, from the studies of the drawings, this disclosure and the claims.

[0222] Notably, in particular, any steps presented can be performed in any order, i.e. the present disclosure is not limited to a specific order of these steps. Moreover, it is also not required that the different steps are performed at a certain place or at one node of a distributed system, i.e. each of the steps may be performed at different nodes using different equipment / data processing. The sequence of all method steps presented above is not mandatory, also alternative sequences may be possible. Nevertheless, the specific sequence of method steps shown as examples in the figures shall be considered as one possible sequence of method steps, e.g. for the respective embodiment described by the respective figure or an embodiment comprising at least some of the steps described by the respective figure.

[0223] Any steps presented herein can be performed in any order. The methods disclosed herein are not limited to a specific order of these steps. It is also not required that the different steps are per-formed at a certain place or in a certain computing node of a distributed system, i.e. each of the steps may be performed at different computing nodes using different equipment / data processing.

[0224] As used herein ..determining" also includes ..initiating or causing to determine", “generating" also includes ..initiating and / or causing to generate" and “providing” also includes “initiating or causing to determine, generate, select, send and / or receive”. “Initiating or causing to perform an action” includes any processing signal that triggers a computing node or device to perform the respective action.

[0225] In the claims as well as in the description the word “comprising” does not exclude other elements or steps and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be230774

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[0227] used in an advantageous implementation. In the claims as well as in the description the word “comprising” or “including” or similar wording does not exclude other elements or steps and shall not be construed limiting to the elements or steps lined out. The indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation or further elements may be included.

[0228] Providing in the scope of this disclosure may include any interface configured to provide data. This may include an application programming interface, a human-machine interface such as a display and / or a software module interface. Providing may include communication of data or submission of data to the interface, in particular display to a user or use of the data by the receiving node, entity or interface.

[0229] Various units, circuits, entities, nodes or other computing components may be described as “con-figured to” perform a task or tasks. Configured to shall recite structure meaning “having circuitry that” performs the task or tasks on operation. The units, circuits, entities, nodes or other computing components can be configured to perform the task even when the unit / circuit / component is not operating. The units, circuits, entities, nodes or other computing components that form the structure corresponding to “configured to” may include hardware circuits and / or memory storing program instructions executable to implement the operation. The units, circuits, entities, nodes or other computing components may be described as performing a task or tasks, for convenience in the description. Such descriptions shall be interpreted as including the phrase “configured to.” Any recitation of “configured to” is expressly intended not to invoke 35 U.S.C. § 112(f) interpretation.

[0230] In general, the methods, apparatuses, systems, computer elements, nodes or other computing components described herein may include memory, software components and hardware components. The memory can include volatile memory such as static or dynamic random-access memory and / or nonvolatile memory such as optical or magnetic disk storage, flash memory, programmable read-only memories, etc. The hardware components may include any combination of combinatorial logic circuitry, clocked storage devices such as flops, registers, latches, etc., finite state machines, memory such as static random-access memory or embedded dynamic random-access memory, custom designed circuitry, programmable logic arrays, etc.

[0231] Moreover, any of the methods, method steps, processes and actions described or illustrated herein may be implemented using executable instructions in a general-purpose or special-purpose processor and stored230774

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[0233] on. A processor may be a processor of any suitable type such as a processor configured for parallel processing of at least a hundred or a at least a thousand threads in parallel, e.g. a graphical processing unit (GPU). For instance, the processor comprises at least a hundred or a at least a thousand parallel processing cores. In particular, the processor may comprise at least one (preferably at least a thousand) compute unified device architecture (CUDA) core(s), which may allow for using a graphical processing unit as the processor, which may increase computational efficiency. For instance, the processor may comprise at least one (e.g. at least a hundred) streaming multiprocessor cores, which may allow for increasing the data throughput. As a further example, the processor may comprise one or more (e.g. at least a hundred) tensor core(s). A tensor core may be specifically adapted to perform matrix operations and may allow to accelerate large matrix operations. A tensor core may be configured to perform mixed-precision matrix multiply and accumulate calculations in a single operation. For instance, a tensor core may perform mixed-precision floating-point matrix arithmetic, specifically utilizing FP16 (half-precision) inputs to produce either full-precision (FP32) or half-precision (FP16) out-puts. In the case of FP16 output, a tensor core may provide a performance boost by storing the intermediate accumulation results in FP32 format, thereby maintaining the precision necessary for accurate results. For example, a processor may comprise several thousand tensor cores, each capable of performing 64 floating point FMA (Fused Multiply-Add) operations per clock cycle. With these capabilities, such a GPU may allow for hundreds of TFLOPs (Tera Floating-Point Operations per Second) of performance in mixed-precision computations. Furthermore, a tensor core may support a variety of numerical formats, including IEEE standard half-precision, single-precision, and double-precision floating-point formats, as well as a range of integer formats.

[0234] A processor may be a processor of any suitable type, and is preferably a processor configured for parallel processing of at least a hundred or at least a thousand threads in parallel, e.g. a graphical processing unit (GPU). For instance, the processor comprises at least a hundred or a at least a thousand parallel processing cores. In particular, the processor may comprise at least one (preferably at least a thousand) compute unified device architecture (CUDA) core(s), which may allow for using a graphical processing unit as the processor, which may increase computational efficiency. For instance, the processor may comprise at least one (e.g. at least a hundred) streaming multiprocessor cores, which may allow for increasing the data throughput. As a further example, the processor may comprise one or more (e.g. at least a hundred) tensor core(s) and / or (e.g. at least a hundred) tensor processing units (TPUs). A tensor core may be specifically adapted to perform matrix operations and may allow to accelerate large matrix operations. A tensor core may be configured to perform mixed-precision matrix multiply and accumulate calculations in a single operation. For instance, a tensor core may perform mixed-precision floating-point matrix arithmetic, specifically utilizing FP16 (half-precision) inputs to produce either full-precision (FP32) or half-precision (FP16) outputs.230774

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[0236] In the case of FP16 output, a tensor core may provide a performance boost by storing the intermediate accumulation results in FP32 format, thereby maintaining the precision necessary for accurate results. A tensor processing unit may be an application-specific integrated circuit (ASIC). It may comprise a matrix multiplication unit (MXU), which may be specifically adapted or configured for dense linear algebra operations. TPUs may be configured to handle large-scale matrix operations efficiently, which may provide high computational throughput for Al tasks. A TPU may be equipped with on-chip high-bandwidth memory (HBM), which may enhance the capability for the use of larger models and batch sizes. TPUs may be connected in groups called Pods, which may scale up workloads with minimal code changes. An MXU may be specifically configured for performing matrix multiplications. A TPU may comprise a tensor core.

[0237] For example, a processor may comprise several thousand tensor cores, each capable of performing 64 floating point FMA (Fused Multiply-Add) operations per clock cycle or (e.g. at least several hundred) tensor processing units (TPUs) being specifically configured for accelerating machine learning (ML) workloads, particularly for cloud-based applications. Additionally, Field-Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs) may provide flexibility and performance benefits for specific Al tasks. With these capabilities, such a GPU may allow for hundreds of TFLOPs (Tera Floating-Point Operations per Second) of performance in mixed-precision computations. Furthermore, a tensor core may support a variety of numerical formats, including IEEE standard half-precision, single-precision, and doubleprecision floating-point formats, as well as a range of integer formats.

[0238] A processor may be a central processing units (CPU) configured with an advanced architecture. A CPU may be configured for sequential processing and general-purpose computing. These CPUs may incorporate vector instruction sets, such as AVX-512, to accelerate mathematical computations that may e.g. enhance Al model training and inference. Furthermore, CPUs may integrate Al accelerators i.e. a CPU may be specifically configured for deep learning workloads.

[0239] The processor may be coupled to memory having a memory bandwidth of at least a hundred gigabytes per second, which may allow efficient handling of extensive data sets and may allow faster reading, processing, and writing compared to a general-purpose processor such as a computational processing unit.

[0240] The memory may be a high-capacity memory configured to manage the data-intensive nature of Al applications, providing necessary bandwidth and storage capacity for complex datasets. The memory may for instance be DDR4, DDR5, High Bandwidth Memory (HBM) and / or GDDR6X memory, which may improve data transfer rates and reduce latency. Such memory may enhance e.g. modeling and real-time sensor230774

[0241] 40

[0242] data for monitoring and control. Further, the memory may be operated with memory optimization techniques, such as caching and prefetching, which may enhance the execution speed of Al algorithms. Nonvolatile Memory (NVM) technologies, including NAND Flash and 3D XPoint, may provide persistent storage solutions with high-speed access, which may enhance rapid data storage and retrieval for Al applications.

[0243] Any disclosure and embodiments described herein relate to the methods, the systems, apparatuses, devices, chemicals, materials, computer program elements lined out above and vice versa. Advantageously, the benefits provided by any of the embodiments and examples equally apply to all other embodiments and examples and vice versa.

[0244] All terms and definitions used herein are understood broadly and have their general meaning.

Claims

1. 23077441CLAIMS1. A method for monitoring and / or controlling at least one composition property of one or more recy- clate(s) to be used as input material for industrial production:providing at least one target composition property associated with recyclates to be used as input material for one or more production plant(s);providing one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s);gathering based on the one or more waste identifier(s) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s);determining, based on the target composition property and the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s), at least one subset of the one or more waste identifier(s) and a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s);providing the at least one subset of the one or more waste identifier(s) and optionally the total composition property for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for production.

2. The method of any of claim 1 , wherein the target composition property specifies constraints or boundaries for the one or more composition properties associated with recyclate to be used by the industrial production.

3. The method of any of the preceding claims, wherein the target composition property relates to one or more composition properties associated with recyclate as produced from one or more waste articles and / or one or more sorted waste fraction(s).

4. The method of any of the preceding claims, wherein the target composition property relates to one or more composition properties associated with one or more waste articles and / or one or more sorted waste fraction(s), wherein the target composition property is provided by the operating apparatus associated with the industrial production for which the recyclate is to be used.230774425. The method of any of the preceding claims, wherein the one or more waste identifier(s) are provided by one or more nodes associated with a collecting, sorting and / or recycling stage configured to collect, sort and / or recycle one or more waste articles and / or one or more sorted waste fraction(s).

6. The method of any of the preceding claims, wherein the one or more waste identifier(s) relate to at least one composition property per one or more waste articles and / or one or more sorted waste fraction^),7. The method of any of the preceding claims, wherein the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s) is accessible based on the one or more waste identifier(s).

8. The method of any of the preceding claims, wherein the at least one composition property and the one or more waste identifier(s) per one or more waste articles and / or one or more sorted waste fraction^) are stored by a distributed and / or decentral network storage associated with the owner of the one or more waste articles and / or one or more sorted waste fraction(s).

9. The method of any of the preceding claims, wherein determining at least one subset of the one or more waste identifier(s) and a total composition property includes determining the total composition property from at least one composition property per waste identifier of the subset, wherein determining at least one subset of the one or more waste identifier(s) and a total composition property includes determining that the total composition property fulfills the target composition property.

10. The method of any of the preceding claims, wherein determining at least one subset of the one or more waste identifier(s) and a total composition property includes determining the at least one subset of the one or more waste identifier(s) based on the composition property associated with one or more waste articles and / or one or more sorted waste fraction(s) as signified by the one or more waste identifier(s).

11. The method of any of the preceding claims, wherein providing the at least one subset of the one or more waste identifier(s) includes providing the at least one subset to one or more nodes associated with collecting, sorting and / or recycling stages for generating control data for monitoring and / or controlling input waste articles and / or fractions based on the at least one subset of the one or more waste identifier(s).2307744312. An apparatus associated with chemical production for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for chemical production:at least one input interface configured to provide at least one target composition property associated with recyclates to be used as input material for one or more production plant(s) and to provide one or more waste identifier(s) associated with one or more waste articles and / or one or more sorted waste fraction(s) and to gather based on the one or more waste identifiers) at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s);at least one processor configured to determine, based on the target composition property and the at least one composition property per one or more waste articles and / or one or more sorted waste fraction(s), at least one subset of the one or more waste identifier(s) and a total composition property associated with at least one waste mixture comprising one or more waste articles and / or one or more sorted waste fraction(s);at least one output interface configured to provide the at least one subset of the one or more waste identifier(s) and optionally the total composition property for monitoring and / or controlling the at least one composition property of one or more recyclate(s) to be used as input material for production.

13. An apparatus associated with waste collecting and / or sorting, comprising:one or more processors and one or more computer-readable media having thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the apparatus to perform the following steps:providing one or more waste identifier(s) and at least one composition property associated with one or more waste articles;receiving the at least one subset of the one or more waste identifier(s) generated according to the methods of claims 1 to 11 or by the apparatus of claim 13;generating fraction control data for sorting waste articles based on the at least one subset of the one or more waste identifier(s);providing fraction identifier(s) per fraction sorted based on fraction control data and assigning fraction identifier(s) to fraction data associated with sorted waste fractions.

14. An apparatus associated with waste recycling, comprising:23077444one or more processors and one or more computer-readable media having thereon computer-executable instructions that are structured such that, when executed by the one or more processors, cause the apparatus to perform the following steps:providing one or more waste identifier(s) and at least one composition property associated with one or more waste fractions;receiving the at least one subset of the one or more waste identifier(s) generated according to the methods of claims 1 to 11 or by the apparatus of claim 13;generating recyclate control data for monitoring and / or controlling input waste fractions to produce recyclate batch(es) based on the at least one subset of the one or more waste identi- fier(s);providing recyclate identifier(s) per recyclate batch recycled based on recyclate control data and assigning recyclate identifier(s) to recyclate data associated with recyclate batch(es).

15. Use of the at least one subset of the one or more waste identifier(s) as determined according to the methods of claims 1 to 11 or by the apparatus of claim 13 for monitoring and / or controlling at least one composition property of one or more recyclate(s) to be used as input material for production.

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