Method for determining biodegradability of preparation

Abstract

The present disclosure relates to a method for determining the biodegradability of a given formulation in a given biodegradation habitat.

Description

Technical Field

[0001] The present invention relates to a method, an apparatus, and a computer program product for determining biodegradability that can be used to verify the biodegradability of a formulation. Additionally, the present invention relates to a training method, a training apparatus, and a training computer program for training a data-driven biodegradation model that can be used by the method, the apparatus, and the computer program product to determine the biodegradability of a formulation. Furthermore, the present invention relates to a method and an apparatus for providing an interface for determining the biodegradability of a formulation. Background Art

[0002] Generally, formulations, i.e., products containing at least two chemical components, are widely used in industrial and / or everyday use products due to their wide range of application properties. The uses of formulations cover paints, personal care products, detergents, lubricants, packaging, films, and foams, among others. However, this wide range of applications results in a large amount of waste containing the formulations used. Disposing of non-degradable waste in an unspecified environment is a problem. In particular, the accumulation of chemicals due to chemicals that do not change their chemical structure to be fed back into the cycle is undesirable. Therefore, if non-biodegradable formulations are not properly collected in the expected waste stream, this may lead to an increase in chemical pollution in the environment. Thus, not only biodegradable formulations are needed, but knowledge about the biodegradability of formulations also needs to be considered at an early stage of the product design process. Therefore, it would be advantageous to provide a possibility to accurately predict the biodegradability of formulations in a computationally inexpensive manner. Summary of the Invention

[0003] An object of the present invention is to provide a method, an apparatus, and a computer program product that allow for accurately determining the biodegradability of a formulation, which are not only computationally inexpensive but can also be robustly applied to new formulations. Additionally, another object of the present invention is to provide a training method, a training apparatus, and a computer program product that allow for providing a biodegradation model that can be used in the method, the apparatus, and the computer program, and can be trained to provide good determination accuracy by using fewer computational resources.

[0004] In a first aspect of the present invention, there is provided a computer-implemented method for determining the biodegradability that can be used to verify the biodegradation of a formulation, the method comprising: i) providing a digital representation of the formulation, ii) providing a biodegradation habitat, wherein the biodegradation habitat indicates habitat descriptor values of habitat descriptors that affect the biodegradation of the formulation in the corresponding habitat, wherein the habitat descriptor indicates an environmental characteristic of the habitat, iii) providing a biodegradation model based on the provided biodegradation habitat, wherein the biodegradation model is adapted to determine the biodegradability of the formulation in the corresponding biodegradation habitat, wherein the biodegradation model is a data-driven model parameterized with respect to the biodegradation habitat such that the biodegradation model can determine the biodegradability of the formulation based on the digital representation of the formulation, and iv) determining the biodegradability of the formulation based on the provided biodegradation model and the digital representation of the formulation.

[0005] Since the biodegradation model is particularly adapted to determine the biodegradability of a formulation in a specifically provided biodegradation habitat, which is characterized by the corresponding habitat descriptor values that affect the biodegradability of the formulation in the corresponding habitat, the biodegradability of the formulation in the corresponding habitat can be determined very accurately. In addition, since the biodegradation model has been specifically trained for one or more specific biodegradation habitats, less training data is required for training, and the biodegradation model becomes more flexible in determining the biodegradability of new formulations that are not part of the training data set. Thus, the method allows for an accurate determination of biodegradability, which is not only computationally inexpensive but can also be flexibly applied to new formulations. Further, current test methods for testing the biodegradability of formulations are extremely time-consuming and may take months or years to obtain results, while the above method allows for results to be provided essentially immediately. Thus, not only can the technical requirements for biodegradability determination be reduced, but also the time required for designing new biodegradable products can be significantly shortened. Additionally, providing a simple possibility of accurately determining the biodegradability of a product already during the design process allows for the design of products such that plastic waste, particularly plastic waste in the form of microplastics, can be avoided. In particular, it can be ensured that the formulations used in the products will biodegrade in the corresponding intended environment, such as in a marine habitat.

[0006] Developing new chemical products according to application requirements is a prominent issue in the modern chemical industry. Recently, another requirement has also been put forward, which concerns the environmental impact of chemical products during their life cycle. An important aspect of the environmental impact is to prevent the accumulation of chemicals. The accumulation of non-degradable chemicals is an increasingly serious problem, which can be avoided if the formulation of the material is biodegradable. To evaluate biodegradation, a series of standardized tests are currently used. For biodegradability, there are multiple tests with specified conditions (e.g., ISO13432, ISO14852, ISO14855, ISO17556, and OECD301). Standardized tests usually strike a balance between time-efficient tests (as short as 14 days and as long as 24 months) and actual conditions. In practice, higher temperatures than real conditions are often used to speed up the test time. Companies developing new products such as packaging need to invest a large amount of resources in self-assessing product sustainability and certification. The overall biodegradability assessment, including laboratory space and equipment, becomes expensive and time-consuming. Therefore, it is necessary to determine the biodegradability of new formulations as early as possible in the development process. The proposed method for determining biodegradability as disclosed herein enables the development of new formulations in a faster and more efficient manner. At an early stage, even before formulating the preparation, the biodegradability can be determined. This allows determining whether the formulation is suitable for entering the market. This speeds up the time to market. This also allows reducing waste generation because there is no need to prepare the formulation to determine biodegradability. The proposed method provides a digital twin for measuring the biodegradability of the formulation.

[0007] In addition, standard measurements and tests of biodegradability are usually time-consuming, for example, including waiting times of several months or even years. Especially when developing new formulations for corresponding applications, these time-consuming tests will greatly limit the development process. In this context, the present invention allows immediate provision of the results of new formulations, greatly shortening the time to obtain the results.

[0008] In addition, due to the staggering number of possible formulations potentially applicable to a particular application, often not even fully explored, today's technology product engineers are given the technical task of finding formulations that are not only applicable to a particular application but also meet the corresponding target properties (especially target biodegradability). A large number of possible formulations must be prepared and tested, or vast datasets and libraries storing potential formulations must be browsed in order to find the corresponding formulations that may be suitable for the application. Even when designed using sophisticated experimental methods, a large number of possible formulations still have to be prepared and experimentally tested. In this context, the above method allows for helping users, such as technology product engineers, to find potentially suitable formulations automatically and more quickly. In particular, by using the above method, the user only has to prepare and test potentially suitable formulations for which it has been determined that they are likely to meet the corresponding target properties, especially target biodegradability. Thus, unnecessary formulation preparation and testing can be avoided. Therefore, the method allows the user to perform more quickly and efficiently the technical task of finding formulations suitable for a technical application.

[0009] The method refers to a computer-implemented method and can thus be executed by a general-purpose or special-purpose computer suitable for implementing the method, for example, by running a corresponding computer program. The method is suitable for determining, in particular predicting, the biodegradability of a pre-defined formulation.

[0010] A biodegradable preparation refers to a preparation that can be degraded through biological processes. In particular, a biodegradable preparation can refer to a preparation that can be assimilated by bacteria and / or fungi to produce environmentally friendly products, i.e., decomposed into non-polluting residues, such as by producing mineralized carbon and / or biomass. Generally speaking, the measured biodegradability can refer to any quantification of the biodegradability of the preparation. For example, the measured biodegradability can refer to only one value, such as the half-life of the preparation in the corresponding habitat, or can refer to more than one value, such as the degradation function of the preparation over time in a specific habitat. In particular, the degradation function can take into account the specific interactions of the biodegradability of the components of the preparation. For example, if the external components of the packaging are biodegradable after a certain time, then the internal components of the packaging start to biodegrade. Preferably, biodegradability refers to the value of the percentage of biodegradation after a predetermined time range. In addition, biodegradability can also refer to the biodegradability of each component of the preparation or the biodegradation of a combination of the components of the preparation. Generally speaking, biodegradability refers to a measure of the degradation (i.e., decomposition) of at least one component, preferably the entire preparation, of the preparation caused by biological processes (i.e., processes involving biological materials, especially microorganisms involved in the degradation process). Therefore, biodegradability does not refer to a pure chemical degradation process that does not include microbial activity. Biodegradability is an inherent property of the preparation. In this context, an inherent property of a preparation refers to a property of the preparation that is caused by the nature of the preparation (i.e., the structure, composition, etc. of the preparation) and thus reflects the nature of the preparation in a specific situation. In particular, biodegradability reflects the nature of the preparation when it is present in a specific biologically active environment. For example, preferably, the biodegradability of the preparation refers to any one of the mineralization characteristics, biotransformation characteristics, and / or decomposition after a specific time range of the preparation. Biodegradability can be particularly used to verify the biodegradation of a preparation, such as for a specific biodegradable environment, i.e., a biodegradable habitat, i.e., the degradation characteristics. For example, the biodegradability can be compared with the biodegradability required for a specific application, and thus it can be determined whether the corresponding preparation is suitable for the corresponding application.

[0011] Biodegradable formulations can be designed to degrade upon disposal through the action of living organisms. Biodegradability can relate to the environmental fate and / or behavior of the formulation. Biodegradability can relate to the extent to which the formulation can be decomposed by microorganisms such as bacteria, fungi or algae. Biodegradability can depend on the chemical structure composition, molecular weight, physical factors such as crosslink density, branching, crystallinity or solubility of the formulation components, and exposure conditions such as the habitat, e.g., soil, compost or aquatic systems. Regarding exposure conditions, the microorganisms, microbial populations, nutrient concentration, temperature, pH, pO2, ionic conditions or substrate properties such as toxicity affect biodegradability. Biodegradability can be measured based on the measured mass loss (mg / time), dissolved organic carbon (DOC, organic carbon concentration / time), oxygen consumption (e.g., by pressure measurement, e.g., Pa / time) or carbon dioxide production over time (e.g., by pressure measurement, e.g., Pa / time).

[0012] To quantify biodegradability in terms of the measured properties of a formulation, many measurement criteria have been developed. Different measurement methods have been defined to determine biodegradability under predefined laboratory conditions. For example, for wastewater, OECD Test No. 301: "Ready Biodegradability" (July 17, 1992) describes six methods for determining biodegradability. Additionally, for example, ASTM D5988-18 "standard test method for determining aerobic biodegradation of plastic materials in soil" describes measuring the change in carbon dioxide produced by microorganisms over time of exposure, thus measuring the degree of biodegradability relative to a reference material. Further, for example, ISO 17556:2019 "plastics—determination of the ultimate aerobic biodegradability of plastic materials in soil by monitoring the oxygen demand in a respirometer or the amount of carbon dioxide evolved" derives the optimal biodegradation rate of plastic materials in the test soil by controlling the amount of oxygen consumed or carbon dioxide produced.In addition, for example, ISO 14855-1:2012 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions - Method by analysis of evolved carbon dioxide - Part 1: General method" and ASTM D5338-15 "Standard test method for determining aerobic bio-degradation of plastic materials under controlled composting conditions, incorporating thermophilic temperatures" determine the ultimate aerobic biodegradability (the way in which microorganisms completely consume chemical or organic substances in the presence of oxygen) of plastics based on organic compounds under controlled composting conditions by measuring the percentage of carbon converted to carbon dioxide and the degree of disintegration of the plastic at the end of the test. ASTM D6400-21 "Standard specification for labeling of plastics designed to be aerobically composted in municipal or industrial facilities" additionally includes elemental analysis, plant germination (phytotoxicity), and sieve filtration of the resulting granules. ISO 17088:2021 "Plastics - Organic recycling - Specifications for compostable plastics" includes an assessment of the negative impacts on the composting process and facilities, as well as on the quality of the resulting compost, including the presence of high levels of regulated metals and other harmful components.

[0013] For aerobic biodegradation, ISO 18830:2016 "Plastics - Determination of aerobic biodegradation of non-floating plastic materials in a seawater / sandy sediment interface - Method by measuring the oxygen demand in closed respirometer" and ISO 19679:2020 "Plastics - Determination of aerobic biodegradation of non-floating plastic materials in a seawater / sediment interface - Method by analysis of evolved carbon dioxide" have been developed. The evaluation of biodegradation is measured by the oxygen demand or the amount of CO2 released.Other standards include, for example, ISO 14853:2016 "Plastics - Determination of the ultimate anaerobic biodegradation of plastic materials in an aqueous system - Method by measurement of biogas production", ISO 23977-1:2020 "Plastics - Determination of the aerobic biodegradation of plastic materials exposed to seawater - Part 1: Method by analysis of evolved carbon dioxide", and ISO 23977-2:2020 "Plastics - Determination of the aerobic biodegradation of plastic materials exposed to seawater - Part 2: Method by measuring the oxygen demand in closed respirometer".

[0014] The quantitative biodegradation properties of the formulation can depend on the measurement method and conditions used, the measurement environment, and the measured values associated with the degradation process, such as mass loss over time, DOC, oxygen consumption, or carbon dioxide production. The measurement method and the measured characteristics can be provided as metadata for each measurement point related to biodegradability.

[0015] Generally speaking, the formulation can be any formulation. The formulation contains at least two components that can refer to any chemical entity. For example, the components can be small molecules, polymers, etc. However, these components themselves can also be more complex chemical products. In a preferred example, the formulation defines the packaging of the product.

[0016] In a first step, the method includes providing a digital representation of a formulation. In particular, providing can refer to receiving the digital representation from a user's input using, for example, a corresponding input unit. Additionally, providing can also refer to accessing a storage unit in which the digital representation has been stored. The digital representation of the formulation can be any representation that provides information allowing the definition of the formulation and / or the derivation of corresponding characterization parameters (e.g., physicochemical properties of the formulation components). Preferably, the digital representation includes an indication of a characterization parameter that relates to the chemical structures of at least two components of the formulation and a measure of the amounts of at least two components in the formulation used to define the formulation. The measure of the amount can be mass, volume, etc. Additionally, the digital representation can include derivatives of the chemical structures of at least two components as characterization parameters, such as the quantitative ratio of at least two components. More preferably, the digital representation of the formulation can indicate the components, the amounts of the components, and the morphology of the formulation as characterization parameters. The morphology of the formulation can be suitable for describing a mixture of at least two components. The morphology can be described by a morphology descriptor. Additionally, the morphology can include geometric measures for describing the result of the mixing of at least two components of the formulation. The result of the mixing of at least two components can be indicated by at least one phase present in the formulation and, if there are at least two phases, the relationship between the at least two phases. The relationship between the at least two phases can indicate the types of phases present in the formulation and the arrangement of the at least two phases relative to each other. Additionally, the digital representation can indicate the arrangement of two components in the formulation as a characterization parameter. The arrangement can indicate the shape of at least one phase that is at least partially incorporated into another phase, the size of the incorporated component / structure (e.g., the size of a capsule), the frequency / density of the incorporated component / structure, etc. In one example, the formulation can contain two phases, namely a hydrophilic phase having component A and a hydrophobic phase having component B. These phases can be mixed only partially, for example, with the help of a mixer or by stirring / shaking the formulation. A portion of component A can be incorporated as spherical droplets into the phase of component B. Thus, the relationship between the at least two phases can indicate the size and frequency of the droplets in the phase having component B. The morphology can be described by a descriptor. The morphology can be described by at least one phase present in the formulation. The at least one phase present in the formulation can be described by its size, the shape associated with the phase, the aggregated phase, the components present in the phase, the measure of the amount associated with the components present in the phase, etc.

[0017] Additionally or alternatively, the numerical representation may indicate components, the amounts of components, and processing conditions as characterizing parameters. The processing conditions may be described by a mixing description. The mixing description may be described by mixing descriptors. The mixing description may be indicated by the order of addition of at least two components and the mixing conditions. The mixing conditions may include details regarding agitation, temperature, pressure, atmosphere, etc. The mixing description significantly affects the physicochemical properties of the formulation and thus affects biodegradation. For example, adding component C to components A and B while agitating may be different from adding component B to components A and C while agitating because A and B may establish different intermolecular interactions than A and C. Different intermolecular interactions may lead to different arrangements of the components, resulting in different formulations.

[0018] Additionally or alternatively, the numerical representation may also indicate storage conditions as characterizing parameters. The storage conditions may refer to the temperature, pressure, atmosphere, and time intervals associated with storing the formulation.

[0019] The morphology or conditions of the treatment are advantageous for determining the preparation specifications because, in an example with a solution containing capsules, once the microorganisms arrive, the surface of the capsule may degrade first, followed by the degradation of the inlay of the capsule. Since, in this case, the morphology resulting from the treatment conditions is crucial when determining the parts of the formulation to be degraded. Thus, the biodegradability may be determined based on the order of acquisition of at least two components in the formulation. Thus, the numerical representation may indicate the order of acquisition of at least two components in the formulation. Additionally, the relationship between at least two phases may indicate the order of acquisition of at least two components in the formulation.

[0020] Additionally or alternatively, the numerical representation of the formulation may indicate the cooperative effect associated with at least two components as a characterizing parameter. The cooperative effect may be synergistic or antagonistic. The cooperative effect becomes apparent when comparing the biodegradability of individual components with the biodegradability of a mixture of components. In the case of more than two components, the cooperative effect becomes even more apparent when comparing the biodegradability associated with at least two components selected from more than two components with the biodegradability associated with a formulation of more than two components. By doing so, a more accurate and realistic description of the formulation is achieved.

[0021] Preferably, the digital representation includes physicochemical properties of the formulation and / or at least one component of the formulation as characterization parameters. In particular, the physicochemical properties of the formulation can be quantified by physicochemical parameters. Preferably, the digital representation indicates and / or includes physicochemical parameters. For example, if the formulation contains a polymer, the physicochemical parameter preferably refers to a polymer descriptor. In particular, the physicochemical parameter indicates a parameter that quantifies the physicochemical properties of the formulation and / or the formulation components. In this context, the term "physicochemical property" refers to the physical and / or chemical properties of the formulation and / or the formulation components. However, a digital representation can also be provided such that it allows, for example, the derivation of physicochemical properties in the form of polymer descriptors by providing a representation of the polymer that is part of the formulation. The physicochemical properties can, for example, already be stored for the formulation and / or the components of the formulation, or can be determined, for example, by corresponding calculations. Preferably, the digital representation refers to or includes at least one of the formulation's formula, structural formula, trade name, IUPAC name, chemical identifier, and CAS number.

[0022] Preferably, the physicochemical parameter refers to at least one of a composition descriptor, a count descriptor, a list of structural fragments, a fingerprint, a graphical invariant, a 3D descriptor, and / or a higher-dimensional descriptor, which indicates a parameter that quantifies the physicochemical properties of the formulation and / or the formulation components. In a preferred embodiment, the descriptor refers to a 3D descriptor, particularly a quantum chemical descriptor. Furthermore, the inventors have found that, in particular, the molar mass very accurately describes the biodegradation of the formulation and / or the formulation components. Therefore, it is particularly preferred that the physicochemical parameter includes the molar mass of the formulation and / or the formulation components. Possible physicochemical parameters are defined in more detail below.

[0023] The composition descriptor can refer to any one of electric potential, average molecular weight, polydispersity, charge, spin, boiling point, melting point, enthalpy of fusion, dissociation constant, Hansen parameter, proton, polar and dispersive contributions, Abraham parameter, retention index, TPSA, receptor binding constant, Michaelis constant, inhibitor constant, mutagenicity, LD50, bioconcentration, toxicity, biodegradation profile, and viscosity.

[0024] The count descriptor can refer to any one of the sum of atomic electronegativities, the sum of atomic polarizabilities, the amount of a component, the ratio of the amounts of components, the number of atoms and non-H atoms, the number of H, B, C, N, O, P, S, Hal, and heavy atoms, the number of H-donor and H-acceptor atoms, the number of bonds, the number of non-H or multiple bonds, the number of double bonds, triple bonds, and aromatic bonds, the number of functional groups, the ratio of functional groups, the sum of bond orders, the aromatic ratio, the number of rings or circuits, the number of unpaired electrons, the number of rotatable bonds, the rotatable bond fraction, and the number of conformational isomers.

[0025] Descriptors related to the list of structural fragment descriptors can refer to at least one of a list of molecular fractions, a list of functional groups, a list of bonds, and a list of atoms. The fingerprint descriptors preferably include at least one of MACCS keys, preferably in bit format or total format, Morgan and other circular fingerprints, preferably in bit format or total format, topological torsion, atom pairs, infrared and related spectra, fingerprint counts, PubChem fingerprints, substructure fingerprints, and Klekota-Roth fingerprints. The graph invariant / topological index descriptors preferably include at least one of topological structure indices and topological chemical indices.

[0026] In a preferred embodiment, the physicochemical parameters are 3D descriptors, including at least one of the volume of the total atomic sum, the average volume per atom, the total atomic sum area, the average area per atom, the area of all atoms, the average area per atom, the solvent accessible surface, the dispersion energy, the dielectric energy, H-donors, H-acceptors, polar and non-polar surface areas, atom-resolved H-donors, H-acceptors, polar and non-polar surface areas, shape, sphericity, dipole and higher electric moments, polarizability, dielectric energy, protons, polar and non-polar surface areas, orbital energies and orbital gaps, ionization energy, electron affinity, hardness, electronegativity, electrophilicity, excitation energy and intensity, infrared and ultraviolet absorption bands, reactivity measurements, redox potential, bond critical points, partial charges, charge surface area, atomic orbital contributions, bond order, atomic radius. In particular, preferably, the physicochemical parameters refer to 3D descriptors, including at least one of the sum of the volumes of all atoms, the average volume per atom, the sum of the areas of all atoms, the average area per atom, the solvent accessible surface, the dispersion energy, the dielectric energy, H-donors, H-acceptors, polar and / or non-polar surface areas, atom-resolved H-donors, H-acceptors, polar and / or non-polar surface areas, shape, sphericity, cone angle, polarizability, dielectric energy, protons, polar and / or non-polar surface areas, excitation energy and intensity, infrared and / or ultraviolet absorption bands, reactivity measurements, particle charge and / or charge surface area. The higher-dimensional descriptors preferably used can include at least one of conformational partition functions, solubility, vapor pressure, activity coefficient, diffusion coefficient, partition coefficient, interfacial activity, rotational constant, moment of inertia, radius of gyration, compositional drift of polymers, density, viscosity, conformationally weighted volume and area, conformationally weighted H-donors, H-acceptors, protons, polar and / or non-polar surface areas, charge distribution, conformational dipole moment, and molecular refraction. Higher-dimensional descriptors are preferably used, which include at least one of solubility, vapor pressure, and activity coefficient, interfacial activity, conformationally weighted H-donors, H-acceptors, protons, polar and non-polar surface areas, and charge distribution.

[0027] In one embodiment, the physicochemical parameters are determined based on the components of the formulation. For example, numerical representations indicate the components of the formulation, and the method further includes classifying the components of the formulation into predetermined group categories, such as solvents, surfactants, pigments, etc. These categories can be pre-determined by the corresponding expert users or can be learned during the training of the biodegradation model. The physicochemical parameters can then be determined based on the group categories. In particular, the physicochemical parameters of the group categories can be derived based on the values of the physicochemical parameters of the components belonging to the group categories. For example, the weight % weighted average, maximum or minimum value, median, total amount, etc. can be determined as the physicochemical parameters for each group category. If more than one physicochemical parameter is provided for the components in a group category, this operation can be performed for each component. Predetermined rules for the corresponding categories can determine how the corresponding physicochemical parameters are derived from the physicochemical parameters of the components in the category. Then, the physicochemical parameters determined for each category are the physicochemical parameters used in the biodegradation model.

[0028] The method further includes providing a biodegradation habitat, where the biodegradation habitat indicates the habitat descriptor values of the habitat descriptors that affect the biodegradation of the formulation in the corresponding habitat. In particular, providing can refer to receiving the biodegradation habitat from user input using, for example, the corresponding input unit. Additionally, providing can also refer to accessing a storage unit on which the biodegradation habitat has been stored. Furthermore, providing can also refer to the presetting of the biodegradation habitat. For example, if the method is used in a very specific environment that is only sensitive to a specific biodegradation habitat, the corresponding biodegradation habitat can be preset and thus does not have to be provided as a specific input. Additionally, the providing can also include, for example, directly receiving the habitat descriptor values of the habitat descriptors from other sources via a network connection and providing the received habitat descriptor values as the biodegradation habitat. The provided biodegradation habitat can refer to a general habitat, such as a wastewater habitat, where the corresponding habitat descriptor values of the habitat descriptors of the habitat have been stored in an accessible corresponding storage device. However, the provided biodegradation habitat can also directly include the corresponding habitat descriptor values of the biodegradation habitat to provide further clarification of the biodegradation habitat (such as the deep sea floor). Additionally, providing the biodegradation habitat can include providing a digital representation of the biodegradation habitat, where the digital representation can then indicate the corresponding habitat descriptor values of the habitat descriptors that affect the biodegradation of the formulation in the corresponding habitat. Furthermore, in a preferred embodiment, the habitat is derived from the digital representation of the formulation. For example, the biodegradation habitat can be indicated by the phases present in the formulation and the aggregated phases of the formulation. Additionally, in one embodiment, different habitats can be provided or derived for different components of the formulation. For example, if for a specific application, it is expected that different components will experience different habitats during the use of the formulation.

[0029] Generally, a habitat descriptor indicates the environmental characteristics of a habitat. In particular, the environmental characteristics of a biodegradable habitat can affect the biological activity in the corresponding habitat. For example, it can affect the presence, growth, or absence of specific microorganisms. Therefore, the environmental characteristics defined by the habitat descriptor also indirectly affect the biodegradation of a formulation in the corresponding habitat. For example, if a formulation and / or a component of the formulation can be biodegraded by specific microorganisms that require a specific salt concentration, the formulation and / or the component of the formulation will be rapidly biodegraded in a habitat that provides such a salt concentration, such as a marine habitat, but will biodegrade much more slowly in a habitat that does not have a suitable salt concentration, such as wastewater.

[0030] Preferably, the biodegradable habitat refers to any one of a marine habitat, a wastewater habitat, a limnetic habitat, an anaerobic habitat, a composting habitat, or a soil habitat. In a preferred embodiment, the biodegradable habitat refers to a marine habitat, and the habitat descriptor refers to at least one of salt concentration, sedimentation type, oxygen level, location, sample depth, water temperature, nutrient concentration, pH value, environmental type, and microbial community. In another preferred embodiment, the biodegradable habitat refers to a limnetic habitat, and the habitat descriptor refers to at least one of salt concentration, sedimentation type, oxygen level, location, sample depth, water temperature, nutrient concentration, pH value, environmental type, and microbial community. In another preferred embodiment, the biodegradable habitat refers to wastewater, and the habitat descriptor refers to at least one of water temperature, microbial community, sludge concentration, nutrient concentration, pH value, test duration, and enzyme environment. In another preferred embodiment, the biodegradable habitat refers to soil, and the habitat descriptor refers to at least one of temperature, sand content, pH value, water content, nutrient concentration, microbial community, and enzyme environment. In another preferred embodiment, the biodegradable habitat refers to compost, and the habitat descriptor refers to at least one of temperature, compost activity, pH value, water content, humidity, degree of compost maturity, compost composition, compost source, nutrient concentration, microbial community, and enzyme environment. Generally, the habitat can also refer to the habitat of a standard test for measuring the biodegradability of a formulation. For example, the standard tests defined by ISO13432, ISO14852, ISO14855, ISO17556, and OECD 301 also define the specific habitats where biodegradation occurs. Therefore, the provision of a biodegradable habitat can also include providing, for example, selecting one of the standard tests via user input, where the habitat descriptor then refers to the specific characteristics of the test, i.e., the test environment and thus the specific characteristics of the test habitat. In addition, the habitat can also be defined by referring to the biodegradation of a formulation or other reference chemicals. In this case, the habitat can be provided by providing the reference and its biodegradation. In this case, the reference and its biodegradation indicate the habitat descriptor.

[0031] The method further includes providing a biodegradation model based on the provided biodegradation habitat. In particular, preferably, providing the biodegradation model means selecting a biodegradation model based on the provided biodegradation habitat. For example, multiple biodegradation models may be stored on a biodegradation storage device, where each biodegradation model has been trained for a particular biodegradation habitat, specifically for different values or value ranges of the habitat descriptors of the biodegradation habitat. Based on the provided biodegradation habitat indicating the habitat descriptor values, an appropriate corresponding biodegradation model can be selected from the multiple biodegradation models. For example, if the indicated habitat descriptor values fall within the range of the habitat descriptor values for which the biodegradation model has been trained, the biodegradation model is appropriate. For example, a corresponding lookup table may be provided that allows for easy comparison between the indicated habitat descriptor values and the descriptor value ranges for which the biodegradation models stored on the storage device have been trained, such that an appropriate biodegradation model can be directly selected. However, in another embodiment, providing the biodegradation model based on the provided biodegradation habitat may also mean that the user selects the biodegradation model. For example, preselected biodegradation models that refer to the provided biodegradation habitat may be provided to the user, and then the user is allowed to select the corresponding biodegradation model that should be used. Additionally, for example, if different habitats are provided for different components of the formulation, more than one biodegradation model may also be provided. Different biodegradation models may also be provided for different components or combinations of components. Generally, the biodegradation models that may be stored are those that have been parameterized based on the corresponding training dataset parameters of one or more habitats. Since the training dataset used to parameterize the biodegradation model is historical data, as described in more detail below, the biodegradation model can be trained and thus generated at any time before determining the specific biodegradation of a particular formulation, and then stored in the corresponding database after training. However, the trained and thus generated biodegradation model can of course also be executed when a specific biodegradation model is needed, for example for a specific habitat.

[0032] In one embodiment, the biodegradation model is parameterized based on a training dataset that includes the measured biodegradation in the corresponding habitat associated with the corresponding formulation in the training dataset. The measured biodegradation can be measured for the corresponding habitat using a predetermined biodegradation test method (e.g., any of the above test methods). Thus, the biodegradation model represents the measured biodegradability of the training formulation.

[0033] Then, the provided biodegradation model is adapted to measure the biodegradability of the formulation in the corresponding biodegradation habitat. In particular, the biodegradation model is a data-driven model parameterized with respect to the biodegradation habitat, such that the biodegradation model can measure the biodegradability of the formulation based on a digital representation of the formulation. Preferably, the biodegradation model is trained to measure biodegradation based on the characterization parameters of the formulation, preferably based on the components of the formulation and the amounts of the components derivable from the digital representation. Additionally, at least one of the morphology, processing conditions, and storage conditions derivable from the digital representation can also be used as a characterization parameter and as an input to the biodegradation model to measure biodegradation. For the components of the formulation, the components themselves can be used as an input to the biodegradation model. However, the parameters derivable from the components can also be used as input characterization parameters, i.e., as characterization parameters input into the biodegradation model. For example, at least one of the chemical structure and physicochemical parameters of the component can be used as an input characterization parameter. Additionally, the amount of the component provided as an input characterization parameter can refer to any one of the mass, volume, and ratio of the corresponding component. For morphology, the input characterization parameter can refer to a morphology descriptor, as described above, for example. The processing conditions can refer to at least one of the mixing conditions. The storage conditions can refer to at least one of the temperature, pressure, atmosphere, and time interval associated with storing the formulation. The term "such that" is here interpreted as parameterization adaptation and thus enables the biodegradation model to provide the biodegradability of the habitat when the physicochemical parameters of the formulation are provided as input. For example, the biodegradation model correlates the physicochemical parameters of the formulation, which are the historical digital representation of the preparation specifications and the historical digital representation of the habitat, with the biodegradability. This allows, based on the target biodegradability, the digital representation of the preparation specifications to be measured. The term "data-driven" is used here to emphasize that the model is mainly based on the corresponding data input and not on, for example, intuition, personal experience, or knowledge. Preferably, the biodegradation model refers to a machine learning-based model, which is based on known machine learning algorithms such as neural networks, regression models, classification algorithms, etc. It has been found that for most applications in this context, in particular, regression models based on linear regression, random forest, boosting trees, lasso, ridge regression, and MARS algorithms are suitable, while for classification models, in particular, random forest, logistic regression, and SVM algorithms are suitable. Generally, the biodegradation model is parameterized during the training process, where, as described above, the digital representation of the formulation or one or more characterization parameters derivable from the digital representation are used together with the corresponding biodegradability of a specific biodegradation habitat. Based on such a training dataset specific to the biodegradation habitat, for example, for a specific range and / or value of the habitat descriptor values, the corresponding parameters of the data-driven model can be determined using known training methods, such that the biodegradation model can also measure the biodegradability of formulations that are not part of the training dataset.

[0034] In addition, in a preferred embodiment, the biodegradation model may also be adapted to further determine the biodegradation of the formulation based on the habitat descriptor values as inputs. In particular, the biodegradation model can be trained by using a training data set that includes the formulations and / or derivable characterization parameters as described above and the associated biodegradability of the specific habitat as described above, so as to obtain a biodegradation model that indirectly takes into account the specific habitat. However, the training data set may optionally also include the specific habitat descriptor values of the corresponding habitat. In this case, the biodegradation model can be trained such that, in addition to the formulations and / or derivable characterization parameters as described above, the habitat descriptor values can also be provided as inputs, where the biodegradation model then further determines the biodegradability based on the habitat descriptor values. The advantage of doing so is that the biodegradability can be determined more accurately, especially in cases where the biodegradation strongly depends on the specific habitat descriptor values of the habitat. For example, in a marine habitat, the temperature or salt concentration may vary greatly in different regions of the world, and for some formulations, this may also result in different biodegradabilities. Therefore, for such cases, it may be advantageous to directly provide the habitat descriptor values as inputs to the biodegradation model. However, it is also possible not to provide the habitat descriptor values as inputs to the biodegradation model, but to train two different biodegradation models and indirectly consider different regions as different habitats.

[0035] Furthermore, the method includes determining the biodegradability of the formulation based on the provided biodegradation model and the digital representation of the formulation. In particular, as described above, the digital representation of the formulation, i.e., the components of the provided formulation and the amounts of the components, can be provided as input characterization parameters to the biodegradation model. However, as described above, further characterization parameters can also be provided by or derived from the digital representation of the formulation and used as inputs. The biodegradation model then provides the determined biodegradability as an output. If the characterization parameters are to be derived from the digital representation of the formulation, the determination of the biodegradability may also include deriving these characterization parameters, for example, as described above. Such determined characterization parameters can then be provided as inputs to the biodegradation model. Then the determined biodegradability can be provided to, for example, an output unit or a computing unit for further processing. Preferably, providing the biodegradability causes further processing using the determined biodegradability. In this case, this provision can be omitted as a separate step and replaced by the processing of the determined biodegradability.

[0036] Determining biodegradability using a biodegradation model can be regarded as a virtual measurement of biodegradability. In particular, the biodegradation model is based on measurement data, for example, the measured biodegradability of a formulation used to train the biodegradation model. Thus, the biodegradation model includes the information provided by these previous measurements. Additionally, physicochemical parameters can also refer to the measured properties of a formulation in some cases. Therefore, the determined biodegradability of a new formulation determined using the biodegradation model can also be regarded as being at least partially based on the measurement results.

[0037] Preferably, the processing of biodegradability includes determining a control signal for controlling a production process based on the determined estimated biodegradability. The production process can refer to the production process of a formulation or can refer to the biodegradation process of a product in which the formulation is utilized. For example, if the determined biodegradability indicates that the formulation will biodegrade in a particular environment (i.e., habitat) in a suitably rapid manner, the generation of the control signal can include generating a control signal for controlling a waste management facility to provide such a habitat, for example, by providing a corresponding temperature. In a preferred embodiment, the control signal indicates the machine-executable preparation specifications of the formulation, particularly when the determined biodegradability of the formulation indicates that it is within a predetermined range around the provided target biodegradability. Generally, the target preparation specifications can indicate the chemical structure of at least two components and a measure of the amounts of at least two components in the formulation. Additionally or alternatively, the target preparation specifications can indicate the morphology. Additionally or alternatively, the target preparation specifications can indicate the processing conditions. Additionally or alternatively, the target preparation specifications can indicate the storage conditions.

[0038] In addition, the process of dealing with biodegradability can also involve the step of selecting one or more preparations based on separately determined biodegradabilities. For example, if the biodegradabilities of a plurality of potential preparations have been determined, the selection may include comparing the biodegradabilities of the different preparations with a predetermined selection criterion and then selecting the preparations whose determined biodegradabilities meet these criteria. In particular, in one embodiment, the method includes receiving a target biodegradability of a preparation, comparing the received target biodegradability with the determined biodegradability, and providing a control signal based on this comparison. The control signal can refer to any signal that allows further control of a technical system. For example, the control signal can be adapted to control an interface for providing the result of this comparison thereon. In a preferred embodiment, the comparison refers to the verification of the target biodegradability, where if the determined biodegradability falls within a predetermined range around the target biodegradability, the verification gives a positive result. In this case, the control signal can be adapted to simply control the user interface to provide an indication of a positive or negative verification result. However, preferably, the control signal refers to the formulation of one or more preparations that meet the specified target biodegradability, i.e., the preparation specification, i.e., the verification of these preparations gives a positive result. The formulation, i.e., the preparation specification, is generally defined as the instructions on how the preparation can be made. In particular, the formulation includes the components and the corresponding amounts of the components. Preferably, the control signal includes the formulation in a form that directly allows automatic control of the corresponding industrial system or labor equipment for producing the preparation. In particular, when the comparison result refers to the determined biodegradability being within a predetermined range around the target biodegradability, preferably the control signal indicates the machine-executable preparation specification of the preparation.

[0039] In a preferred embodiment, the method further includes providing the preparation specification as a digital representation of the preparation and determining the preparation and / or a characterization parameter of the preparation, such as in the form of a chemical structure, based on the preparation specification. In particular, the preparation specification, i.e., the formulation, includes information about the preparation process of the preparation, such as information about the components, the amounts, and the process of preparing the corresponding components to form the preparation. The method then includes determining the preparation and / or one or more characterization parameters, such as the chemical structure, based on the preparation specification.

[0040] By providing a variety of preparation specifications, the user can optimize the mixture of components according to biodegradability. Preferably, in this embodiment, a target biodegradability is further provided, and for each formulation associated with various preparation specifications, the biodegradability is measured as described above. Then, the measured biodegradability is compared with the target biodegradability, and the preparation specification that meets the target biodegradability is determined as the target preparation specification. In addition, optimization can also be carried out by providing the preparation specification as a starting point, and then modifying the preparation specification if the measured biodegradability does not meet the target biodegradability. For example, the components can be modified or changed. In addition, not only can the components be optimized, but also the interactions between the components crucial to the formulation can be optimized. The components of the formulation are generally widely known materials, and their new combinations provide the known effects of the formulation. Therefore, in many cases, optimizing the sole components does not provide the changes required to meet the target biodegradability. Therefore, it can be determined whether the target biodegradability can be achieved by changing the "formulation" of the formulation, rather than designing new components for the formulation by the methods disclosed herein. By doing so, the resources for preparing new materials are saved, and standard chemicals can be combined more effectively.

[0041] In one embodiment, the method further includes providing a biodegradation test method, wherein the provided biodegradation test method indicates a standardized biodegradation test method for experimentally determining the biodegradation of chemicals, and a biodegradation model is further provided based on the provided biodegradation test method. Generally, there are a variety of standardized biodegradation test methods for testing the biodegradation of chemicals. For example, such test methods can be found in DIN or ISO standards. Further providing the biodegradation test method and providing a biodegradation model that has been trained based on the provided biodegradation test method allows for the determination of biodegradability that can be easily compared with, for example, the biodegradability measured separately using the corresponding test methods. In particular, for this embodiment, it is preferred that the biodegradation model be trained based on a dataset in which the test method based on which the biodegradation is determined is clearly specified, such that the biodegradation model can be specifically trained for one or more test methods.

[0042] In a preferred embodiment, a numerical representation indicates the components of the formulation, and the biodegradability of each component is determined individually, wherein the overall biodegradability of the formulation is determined based on the biodegradability of the measured components. Preferably, the overall biodegradability is set to the biodegradability of the component formulation with the lowest biodegradability. However, the overall biodegradability can also be determined based on other predefined rules, for example, as the average of the biodegradabilities of all components. Additionally, the numerical representation can further indicate the amount of the components in the formulation. In this case, the overall biodegradability can be further determined based on the amount, for example, as a weighted average, where the weights are determined by the amount. Generally, for these embodiments, the biodegradation of each component can be determined as described above. For example, the same biodegradation model can be used for each component, and the corresponding characterization parameters of the components can be provided as inputs to the corresponding biodegradation models. However, for different components, different biodegradation models can also be used, for example, biodegradation models specifically trained for the corresponding components.

[0043] In one embodiment, it is further provided that the target application of the formulation relates to the intended application of the formulation, wherein the biodegradation habitat is provided based on the target application. The target application of the formulation can refer to, for example, the intended application context of the formulation, such as if the formulation is expected to be used as a coating, in personal care products, in detergents, in lubricants, in agriculture, or in product packaging. Such target applications indicate specific biodegradation habitats. For example, for the packaging of a product, it may be interesting if the formulation biodegrades in compost. In another example, if the target application involves using the formulation in personal care products, it is likely that the formulation will be found in the aquatic environment sooner or later. Thus, the corresponding target application can indicate the corresponding biodegradation habitat. In this context, a predefined list can be provided on a storage device, on which the corresponding target applications and the corresponding biodegradation habitats are stored. Then the target application of the formulation can be provided, for example, by presenting a list of target applications to the user and allowing the user to select the corresponding target application, wherein the corresponding target application is associated with one or more biodegradation habitats. Then the biodegradability of the target application and each of its associated biodegradation habitats can be determined, or the user can again select the corresponding biodegradation habitats associated with the target application. Additionally or alternatively, information indicating the end-of-life treatment of the formulation can be provided. For example, the end-of-life treatment can indicate whether the formulation is expected to biodegrade in a specific environment, or whether a specific treatment should be carried out, such as in a bioreactor. Thus, as described above, the information on the end-of-life treatment can also be used to determine the biodegradation habitat of the formulation.

[0044] In one embodiment, further information indicating the accessible surface area of the formulation in its intended form is provided, wherein the biodegradation model is further trained to determine biodegradability based on the accessible surface area, and wherein the method further comprises determining biodegradability based on the accessible surface area. For example, the information may indicate whether the intended product is provided in a solid, powder, foam, granular or any other form. Preferably, the information indicates the surface area per mass of the product or the geometry of the smallest independent part of the product. Generally speaking, although the biodegradability of a formulation is an inherent property of the formulation, the exact time of biodegradability of a product containing the formulation can also depend on, for example, the surface area accessible to the microbial components of the habitat responsible for biodegradation. Therefore, further determining biodegradability based on the surface area of the product containing the formulation allows for an improvement in the accuracy of predicting the biodegradability of the final product.

[0045] In one embodiment, the habitat descriptor values of the habitat descriptor are stored in association with the corresponding geographical locations, wherein providing the biodegradation habitat refers to the geographical location providing the habitat, and retrieving these habitat descriptor values of the geographical location from the storage device. For example, the geographical location may refer to coordinates or other area identifiers. For example, the geographical location may refer to the name of a city, country, country region, sea area, geographical feature, etc. Based on such geographical locations, the corresponding habitat descriptors, such as the average value, minimum value and maximum value of the habitat descriptor, can be stored. Therefore, by providing the geographical location, the corresponding habitat descriptor values of the geographical location can be provided. This has the advantage that the user does not have to know the exact habitat or the exact habitat descriptor value of the area. Therefore, the user can simply provide the location where the intended formulation may biodegrade in that area.

[0046] In one embodiment, the characterization parameters of the formulation and / or formulation components indicated by the digital representation of the formulation may refer to at least one of formulation parameters, composition descriptors, count descriptors, lists of structural fragments, fingerprints, graphical invariants, 3D descriptors and / or higher-dimensional descriptors indicating the chemical properties of the formulation and / or formulation components from the preparation process. The digital representation and the corresponding associations with such parameters calculated previously or further information about the formulation may already be stored and associated with the corresponding digital representation. For example, if the digital representation refers to a trade name or a known identifier, the corresponding composition, structural properties, morphology, parameters or physicochemical parameters corresponding to the trade name or identifier may already be stored on, for example, the storage device of the trade name owner.

[0047] In another aspect, an interface method for providing an interface is proposed, where the interface method includes: i) receiving a digital representation and a habitat as inputs via a user interface and providing the received digital representation and habitat to a processor that executes the method as described above, and ii) providing, via the user interface, the biodegradability of the determined formulation as a result, where the result is received from a processor that executes the method as described above.

[0048] In yet another aspect, a computer-implemented training method is proposed, which is used to train a data-driven biodegradation model to parameterize the biodegradation model. The training method includes i) providing training data associated with a predetermined biodegradation habitat, where the training data includes a) digital representations of a plurality of training formulations, and b) the biodegradability of the corresponding biodegradation habitat associated with each training formulation; ii) providing a data-driven trainable biodegradation model; iii) training the provided data-driven biodegradation model based on the provided training data such that the trained biodegradation model is adapted to determine the biodegradation of a formulation based on the digital representation of the formulation, and iv) providing the trained biodegradation model.

[0049] In another aspect, a device for determining the biodegradability of a predetermined formulation is proposed, where the device includes: i) a digital representation providing unit for providing a digital representation of the formulation; ii) a habitat providing unit for providing a biodegradation habitat, where the biodegradation habitat indicates a habitat descriptor value of a habitat descriptor that affects the biodegradation of the formulation in the corresponding habitat, and the habitat descriptor indicates the environmental characteristics of the habitat; iii) a model providing unit for providing a biodegradation model based on the provided biodegradation habitat, where the biodegradation model is adapted to determine the biodegradability of the formulation in the corresponding biodegradation habitat, and the biodegradation model is a data-driven model parameterized with respect to the biodegradation habitat such that the biodegradation model determines the biodegradation of the formulation based on the digital representation, and iv) a determination unit for determining the biodegradability of the formulation based on the selected biodegradation model and the digital representation of the formulation.

[0050] In yet another aspect, an interface device for providing an interface is proposed, where the interface device includes: i) an input interface unit for receiving a digital representation and a habitat as inputs via a user interface and providing the received digital representation and habitat to the device as described above, and ii) a result interface for providing, via the user interface, the biodegradability of the determined formulation as a result, where the result is received from the device as described above.

[0051] On the other hand, a training device for training a data-driven biodegradation model to parameterize the biodegradation model is proposed, wherein the training device includes i) a training data providing unit for providing training data associated with a predetermined biodegradation habitat, wherein the training data includes a) digital representations of a plurality of training formulations, and b) biodegradability of the corresponding biodegradation habitat associated with each training formulation, ii) a trainable model providing unit for providing a data-driven trainable biodegradation model, iii) a training unit for training the provided data-driven biodegradation model based on the provided training data such that the trained biodegradation model is adapted to determine the biodegradation of a formulation based on the digital representation of the formulation, and iii) a trained model providing unit for providing the trained biodegradation model.

[0052] In yet another aspect of the present invention, the use of the method as described above is proposed, wherein the method is used to determine the biodegradability of any of the following pre-specified formulations: i) formulations containing polyesters, especially for covering films and packaging applications, such as aromatic aliphatic copolyesters, ii) formulations containing polyalkoxylates, especially for household and personal care applications, iii) formulations containing polyurethane dispersions, iv) formulations for fragrance applications, v) formulations for paper coatings for packaging applications based on multilayer blends, and vi) formulations containing polyurethanes for adhesives.

[0053] In another aspect of the present invention, a system is proposed, wherein the system includes i) a control signal, which includes preparation specifications of a formulation, which indicate one or more components of the formulation, wherein the control signal is generated according to the method described above, and ii) one or more components indicated by the preparation specifications in the control signal.

[0054] In yet another aspect of the present invention, the use of the control signal generated according to the method described above for controlling a production process, especially a production process including the production of a formulation, is proposed.

[0055] In another aspect of the present invention, a control signal is proposed, wherein the control signal is generated according to the method described above. Preferably, the control signal includes machine-executable preparation specifications for producing a target formulation.

[0056] On the other hand, a computer program product for determining the biodegradability of a pre-specified formulation is proposed, wherein the computer program product includes program code means for causing the device as described above to execute the method as described above.

[0057] On the other hand, a computer program product for training a biodegradation model is proposed, wherein the computer program product includes program code means for causing the training device as described above to execute the training method as described above.

[0058] It should be understood that the methods, devices, and computer program products as described above have similar and / or identical preferred embodiments, particularly the preferred embodiments defined in the dependent claims. In addition, the training methods, training devices, and training computer program products as described above also have similar and / or identical preferred embodiments, particularly the preferred embodiments defined in the dependent claims.

[0059] It should be understood that the preferred embodiments of the present invention may also be any combination of the dependent claims or the above-described embodiments with corresponding dependent claims.

[0060] These and other aspects of the present invention will be apparent and elucidated with reference to the embodiments described hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In the following drawings:

[0062] Figure 1 An embodiment of a system including a device for determining the biodegradability of a formulation is schematically and exemplarily shown,

[0063] Figure 2 A flowchart of a method for determining the biodegradability of a formulation is schematically and exemplarily shown,

[0064] Figure 3 A flowchart of a method for training a biodegradation model to determine the biodegradability of a formulation is schematically and exemplarily shown,

[0065] Figure 4 A flowchart of an embodiment of a method for determining the biodegradability of a formulation is schematically and exemplarily shown,

[0066] Figures 5 to 7 A block diagram of the system architecture of a system and device for determining the biodegradability of a formulation is schematically and exemplarily shown. DETAILED DESCRIPTION

[0067] Figure 1 An embodiment of system 100 is schematically and exemplarily shown, which system includes a device 110 for determining the biodegradability of a formulation based on a digital representation of the formulation and a provided biodegradation habitat. Additionally, system 100 includes: a training device 130 for training the biodegradation model used in device 110; a database 140 on which the determination results of the biodegradability of the formulation can be stored; and a production system 120 for producing products, particularly products including the formulation, which products can be controlled using the determined biodegradability.

[0068] Device 110 includes a digital representation providing unit 111, a habitat providing unit 112, a model providing unit 113, a determination unit 114, and an optional output and / or control unit 115, which may be adapted to output the determined biodegradability and / or provide a control signal for controlling the production process of the production system 120 based on the determined biodegradability.

[0069] The digital representation providing unit 111 is adapted to provide a digital representation of the preparation, which at least indicates the components of the preparation and the amounts of the components. The digital representation providing unit 111 may refer to, for example, an input unit to which the user can input the corresponding digital representation. In addition, the digital representation providing unit 111 may refer to a user interface that allows the user to interact with the device 110 and / or the database 140 or a part of the user interface. However, the digital representation providing unit 111 may also refer to a storage unit on which the digital representation of the preparation is stored or is communicatively coupled thereto. Generally, the digital representation may directly include the preparation, which indicates the components and amounts. However, instead of directly providing the preparation, the preparation specifications may also be provided. In this case, preferably, the digital representation providing unit 111 is also adapted to determine the preparation and optionally further characterization parameters of the preparation according to the preparation specifications. In particular, the digital representation providing unit 111 may be adapted to determine the preparation and / or the characterization parameters, for example, by accessing a database on which a plurality of the most relevant preparations and the corresponding characterization parameters are stored. Then, the digital representation providing unit 111 is adapted to provide, for example, to the determination unit 114, a digital representation including the preparation.

[0070] The habitat providing unit 112 is adapted to provide a biodegradation habitat. The habitat providing unit 112 may refer to, for example, an input unit to which the user can input the corresponding biodegradation habitat. For example, a user interface may be provided that allows the user to select from a plurality of predetermined biodegradation habitats. In a preferred embodiment, the habitat providing unit may be communicatively coupled to a user interface or a reference user interface that allows, for example, indicating a geographical location by marking a position on a map, by indicating coordinates, or by providing the name of a region (e.g., a political region or a geological region), where the habitat providing unit may then be adapted to provide a biodegradation habitat based on the geographical location. For example, if the geographical location indicates a specific sea area, such as the North Sea or the Atlantic Ocean, the habitat providing unit may be adapted to determine a marine habitat as the biodegradation habitat.

[0071] Generally speaking, biodegradation habitat descriptors affect the habitat descriptor values of the habitat descriptors that affect the biodegradation of the formulation in the corresponding habitat. In particular, the habitat descriptors indicate the environmental characteristics of the habitat. For example, for a marine habitat, the salt concentration can strongly affect the biodegradation of the formulation in the marine habitat. Generally speaking, since the biodegradation is measured, the chemical effect of the habitat descriptor on the formulation is not important for this application. Therefore, the effect of the habitat descriptor on the habitat biology, especially on the habitat microbial population, indirectly affects biodegradation.

[0072] The model providing unit 113 is adapted to provide a biodegradation model based on the provided biodegradation habitat. In particular, preferably, the model providing unit 113 is adapted to select a biodegradation model from a plurality of biodegradation models already stored in the database. For example, the biodegradation model can be trained with respect to training data corresponding to one or more specific biodegradation habitats. These specific biodegradation habitats can be defined with respect to habitat descriptor values or value ranges, which define for which biodegradation habitat the corresponding biodegradation model is applicable. For example, a lookup table can be provided that allows the model providing unit to select which biodegradation model is appropriate based on the biodegradation habitat, for example, based on the habitat descriptor values of the biodegradation habitat. However, the model providing unit 113 can also include or refer to an input unit, and the biodegradation model can be received in the input unit, for example, through a user selection or user input indicating which biodegradation model should be used.

[0073] The biodegradation model is a parameterized data-driven model such that the biodegradation model can measure the biodegradability of the formulation based on a digital representation, for example, based on the components of the formulation and the amounts of the components. In a preferred embodiment, the data-driven model refers to a machine learning model, for example, using an algorithm based on a regression model or an algorithm based on a classifier model. The algorithm based on the regression model can be based on any one of a neural network algorithm, a linear regression algorithm, a LASSO algorithm, a ridge regression algorithm, a MARS algorithm, a random forest algorithm, and a boosting tree algorithm. The algorithm based on the classifier model can be based on any one of a random forest algorithm, a logistic regression algorithm, and an SVM algorithm. The inventors have found that for most applications, in particular, algorithms based on linear regression, random forest, and MARS are suitable.

[0074] For example, the training device 130 can be used to train a biodegradation model. In particular, the training device 130 includes a training data providing unit 131 for providing training data to train a data-driven biodegradation model. The training data includes a) digital representations of a variety of training formulations, and b) biodegradability associated with each training formulation in one or more different habitats. Preferably, in the training data, the biodegradability provided for each training formulation refers to the biodegradability measured according to the same measurement method. Generally speaking, the training data can be designed to cover a predetermined habitat space of the biodegradation model to be trained, where the habitat space is defined by the value range of the corresponding habitat descriptors for which the biodegradation model will be trained. For example, the training data can be designed to cover a predetermined type of formulation in a predetermined habitat. Known methods for designing and optimizing the training data for the predetermined habitat space can be used so that the habitat space is well covered by the training data and random outliers are avoided.

[0075] In addition, the training device 130 includes a model providing unit 132, which is adapted to provide a data-driven trainable biodegradation model, for example, a biodegradation model including parameters that can be set during the training process for training the biodegradation model. For example, the trainable biodegradation model may already be stored on a storage unit, and the model providing unit 132 can access the storage unit to provide the model. In addition, the training device 130 includes a training unit 133 for training the provided data-driven biodegradation model based on the provided training data. In particular, training can refer to changing the parameters of the biodegradation model based on the corresponding training data until the biodegradation model is suitable for measuring the biodegradability of a formulation based on the digital representation. Generally speaking, any known training algorithm for training data-driven, especially machine learning-based models, can be used. Preferably, during the training of the biodegradation model, the characterization parameters of the formulation that have the greatest impact on biodegradability in the corresponding habitat are also determined, and then the model is trained based on these most influential characterization parameters. To determine these most influential characterization parameters, for example, clustering analysis or PCA analysis tools can be used. In particular, the characterization parameters can be used to determine the application space of the training data, where the application space is then defined by the characterization parameters of the formulation and the habitat descriptors covered by the data. Then, the determination of the most influential characterization parameters and / or habitat descriptors can be performed as a dimensionality reduction of the application space. An algorithm for optimizing the training data in the application space can then be applied, for example, covering the application space with as little training data as possible.

[0076] Thus, the training device 130 includes a trained model providing unit 134, which is adapted to provide the trained biodegradation model to, for example, a storage unit on which the trained biodegradation models for different habitats and / or different types of formulations are respectively stored. However, the trained model providing unit 134 may also be adapted to directly provide the trained biodegradation model to, for example, the biodegradation model providing unit 113 of the device 110.

[0077] In all cases, the biodegradation model providing unit 113 is then adapted to provide a suitable trained biodegradation model to the property determination unit 114. Then, the determination unit 114 can utilize the biodegradation model and the provided digital representation to determine biodegradability. In particular, the determination unit 114 may be adapted to use the characterization parameters indicated by the digital representation as inputs to the biodegradation model, which, as described above, has been trained to then provide a determination of its trained biodegradability as an output. The output unit, such as a display, can then be adapted to output the determined biodegradability. However, the output unit may additionally or alternatively be adapted to provide the determined biodegradability to the database 140 for storing the formulations associated with the determined biodegradability for future use. In particular, if the biodegradabilities of different formulations have been determined and, for example, stored on the storage unit, i.e., the database 140, the output unit may be adapted to select the corresponding formulations based on a predetermined criterion regarding biodegradability. Then, the output unit may be adapted to provide and / or output the selected formulations and their biodegradabilities. This is particularly suitable in cases where a user is looking for formulations with a specific biodegradability in one or more habitats from among a plurality of candidate formulations.

[0078] Optionally, the device 110 may include a control unit 115, which is adapted to provide a control signal based on the determined biodegradability to control the production process of the production system 120. In particular, preferably, the control unit 115 is adapted to receive the target biodegradability of the formulation, compare the received target biodegradability with the determined biodegradability, and provide a control signal based on this comparison, preferably, a control signal indicating the use or production of the formulation with the determined biodegradability. In addition, when the result of the comparison indicates that the determined biodegradability is within a predetermined range around the target biodegradability, the control signal may indicate the machine-executable preparation specifications of the formulation with the determined biodegradability. However, the control unit 115 may also be adapted to control the production process of another product based on the determined biodegradability, for example, to provide a control signal indicating the machine-executable preparation specifications of another product that utilizes or contains the corresponding formulation. In addition, the control unit 115 may provide a control signal for controlling the habitat for the biodegradable formulation, for example, in a waste management facility. For example, the target biodegradability that meets specific habitat descriptors may be satisfied, and the control unit 115 may then be adapted to provide a control signal for controlling the facility to meet these habitat descriptor values.

[0079] Figure 2 A flowchart of a method for determining the biodegradability of a formulation is schematically and exemplarily shown. The method 200 includes a first step 210 of providing a digital representation of the formulation. In particular, providing the digital representation in this step may be implemented according to the principles described above with respect to the digital representation providing unit 111. Additionally, in step 220, a biodegradation habitat is provided that provides habitat descriptor values indicating the habitats that affect the biodegradation of the formulation in the corresponding habitats. Similarly for this step 220, the principles described, for example, with respect to the habitat providing unit 112 may be applied. Additionally, in step 230, a biodegradation model is provided that is adapted to determine the biodegradability of the formulation based on the digital representation. As already discussed in more detail above, providing the biodegradation model may also refer to selecting the biodegradation model based on the provided biodegradation habitat. In addition, the biodegradation model is a data-driven model parameterized with respect to the biodegradation habitat parameters such that the biodegradation model can determine the biodegradability of the formulation based on the digital representation. Generally, steps 210, 220, and 230 can be performed in any order, or even simultaneously. In the subsequent step 240, the biodegradability is determined based on the provided digital representation of the formulation and the biodegradation model. In an optional step 250, the biodegradability may then be provided to, for example, a user interface such that the determined biodegradability of the formulation can be displayed on a display. However, in step 250, the method may additionally or alternatively include generating control signals that allow controlling the production process of a product (such as a formulation or a product containing the formulation), as already described in more detail above.

[0080] Figure 3 A flowchart is schematically and exemplarily shown for a method of training a data-driven biodegradation model, which model is used, for example, in the method 200 discussed with respect to Figure 2 the method 200. Generally, the method 300 can be performed, for example, by corresponding units of the training device 130 as described with respect to Figure 1 The method 300 includes a step 310 of providing training data for training a data-driven biodegradation model. The training data includes a) digital representations of a plurality of training formulations, and b) biodegradability associated with each of the training formulations in a corresponding biodegradation habitat, e.g., for a particular habitat descriptor value. In particular, the training data can be provided according to the principles described by the training data providing unit 131 as described above with respect to Figure 1 The method further includes a step 320 of providing a data-driven trainable biodegradation model, e.g., a machine learning-based biodegradation model such as a neural network. Generally, step 310 and step 320 can be performed in any order or even simultaneously. The method 300 then further includes a step 330 of training the provided data-driven biodegradation model based on the provided training data, e.g., by varying parameters in the data-driven trainable biodegradation model such that the trained biodegradation model is adapted to predict the biodegradability of a formulation based on the digital representation of the formulation. In step 340, then, the trained biodegradation model can be provided, e.g., by storing the trained biodegradation model on a storage device or by directly providing the trained biodegradation model to the device 130 as described with respect to Figure 1 described.

[0081] In the following, more detailed preferred examples of the above method and corresponding device will be described. An exemplary embodiment of the method can consist of a plurality of steps described below. Figure 4A schematic and exemplary flowchart of an exemplary embodiment of the method is provided. In this exemplary embodiment, the method begins with a request for a digital representation of a new formulation, for example, via a user interface. Additionally, a target application for the new formulation can also be requested, for example, via the user interface. The target application can relate to, for example, how the new formulation, for which a digital representation is provided, should be utilized in a product, or what kind of waste treatment is anticipated for the formulation. Furthermore, as a supplement or alternative to the target application, a biodegradation habitat can also be requested. However, the corresponding target application can also indicate the corresponding biodegradation habitat, for example. For example, a list can be presented to the user via the user interface, from which the user can select the corresponding target application. Based on the corresponding selection, in addition, a selection of a biodegradation habitat associated with the target application can also be provided for the user to select. Based on the target application, particularly based on the biodegradation habitat indicated by the target application, a corresponding biodegradation model, i.e., the biodegradation model, can be selected. Optionally, additional pre-selection conditions indicated by the selected biodegradation model can be required. For example, the biodegradation model can be adapted to utilize additional descriptors, such as optional habitat descriptors, application constraints, etc., and these additional descriptors can be requested if necessary, and these additional descriptors can allow the biodegradation model to determine biodegradation with higher accuracy or specifically for these constraints. Additionally, characteristic parameter values can be derived from the provided digital representation, where the characteristic parameters can also depend on the provided target application. Then, using the selected biodegradation model and the derived characteristic parameter values allows for the provision of the corresponding determined biodegradability, i.e., the corresponding target biodegradability.

[0082] Figure 5A block diagram showing an exemplary system architecture of an automated laboratory system 1000 for preparing a preparation, the automated laboratory system having a laboratory equipment control device 1102, a network 1150, and a preparation specification (i.e., formulation) module 1100 / 1110 and a client device 1108. The automated laboratory system includes a laboratory equipment control device layer 1152 as part of the laboratory equipment control device 1102, a preparation specification module layer 1154 associated with the preparation specification module, and a remote control or client layer 1156 associated with the client device 1108. The laboratory equipment control device layer can be divided into several hierarchical layers: hardware, middleware, and interface layer. The hardware layer relates to hardware resources such as sensors and actuators, especially for controlling the preparation of the preparation. The middleware relates to any known middleware for laboratory or factory preparation operations. An example is LABS / QM, which provides different abstractions for hardware, network, and operating systems, such as low-level device control and messaging. The communication layer relates to a communication protocol, which can be REST, and can be implemented through different transport protocols (i.e., UDP, TCP, telemetry), which allow message exchange between the laboratory equipment control device and the laboratory equipment device. Such a software architecture allows the control and monitoring of laboratory equipment without interacting with the hardware.

[0083] The preparation specification module layer 1154 may include: a mass storage layer, a computing layer, and an interface layer. The storage layer is configured to provide a mass storage device for a data-driven biodegradation model to provide a formulation of the preparation, i.e., a preparation specification, based on biodegradability, as described in detail above. In particular, as described above, the functions performed by the device can be provided as program code components stored on the mass storage device. In addition, the preparation specifications of multiple preparations can be stored in the mass storage device. Such data can be stored in a structured database such as an SQL database, or in a distributed file system such as HDFS, a NoSQL database such as HBase, MongoDB. The computing layer may include an application layer that allows customization of the functions provided by standard cloud services to perform computational processes based on target characteristics. Such functions may include determining a digital representation of a target preparation based on the target biodegradability and biodegradation model, generating a preparation specification from the digital representation of the target preparation, and providing the preparation specification as control data to the laboratory equipment control device.

[0084] The interface layer can implement web services, a network interface as UDP or TCP, or a Websocket interface. To communicate with the laboratory equipment control device, a REST API is implemented.

[0085] The client layer 1156 provides an interface for end users. For end users, the client layer 1156 can run a client-side web application that provides an interface to the preparation specification module layer 1154 or the laboratory equipment control device layer 1152. A UI can be provided to the user for selecting a target biodegradability and a biodegradable habitat of the target biodegradability, and the target biodegradability can also include a range of biodegradability values. In other examples, a UI can be provided to the user for selecting more than one target biodegradability and corresponding values. The application can be configured for the user to remotely monitor and control the laboratory equipment control device and operations. In other examples, the client device layer and the preparation specification module layer can be integrated into one device. The alternatives described herein are for illustrative purposes only and should not be considered limiting.

[0086] Figure 6 A block diagram of an exemplary system architecture of a system and device for generating a biodegradation model to determine biodegradability, network 2150, and model generation modules 2100 / 2110 is shown. The model generation modules can be considered as or include a training model device, a preparation specification module 1100 / 1110, and a client device 2108. The system for generating a biodegradation model includes a model generation module layer 2154 as part of the model generation module, and a client layer 2156 associated with the client device 2108.

[0087] The model generation module layer 2154 may include: a mass storage layer, a computing layer, and an interface layer. The storage layer is configured to provide a mass storage device for the data-driven biodegradation model as described above. Additionally, the mass storage device is configured to store the preparation specifications of the formulation and the measured biodegradability of one or more habitats. Such data may be stored in a structured database, such as an SQL database, or in a distributed file system, such as HDFS, a NoSQL database, such as HBase, MongoDB. The computing layer may include an application layer that allows customization of the functions provided by standard cloud services to perform the computational processes for generating a biodegradation model for measuring the biodegradability of the formulation. Such functions may include: receiving, for at least two previously measured formulations, their corresponding digital representations associated with the preparation specifications, measurement data of the biodegradability of each of the at least two previously measured formulations in at least one habitat; receiving at the model generation module the digital representation of at least one unmeasured formulation; training the model based on the above training principle on the digital representations of at least two previously measured formulations, the measurement data of the biodegradability of each of the at least two previously measured formulations in at least one habitat, and preferably a similarity metric between the digital representations associated with the preparation specifications of each of the at least two previously measured formulations and the corresponding digital representation associated with the preparation specification of at least one unmeasured formulation; and providing, via an output interface, a biodegradation model for biodegradability. The model generation module layer may be configured to deploy the generated model and the preparation specification database to the preparation specification module layer. This may include storing the generated model and the preparation specification database in the mass storage device associated with the preparation specification module.

[0088] The model generation module layer may also be configured to determine, based on the preparation specifications, the digital representation of the formulation associated with the preparation specifications. The digital representation may include a set of characterization parameters and characterization parameter values associated with the preparation specifications of each measured formulation. In the case where the model is generated based on the digital representation derived from the formulation, the relationship between the preparation specifications and the physicochemical parameters may be stored in the mass storage device associated with the model generation module. In such a case, deploying the model includes providing the relationship.

[0089] The interface layer can implement web services, a network interface as UDP or TCP, or a Websocket interface. To communicate with the client device, a REST API is implemented in this example. The client layer 2156 provides access to a mass storage device that contains the preparation specifications of the preparation and the biodegradability of at least one of at least two preparations. The client layer also provides an interface for the end user. For the end user, the client layer 2156 can run a client-side web application that provides an interface to the model generation module layer 2154 or the mass storage device associated with the client layer. A UI for selecting the test method and / or habitat for which biodegradability should be determined can be provided to the user. A UI for selecting the preparation specification data can also be provided to the user. The user interface can also provide an option to upload the selected data to the model generation module layer and optionally an option to initiate model generation.

[0090] Figure 7 An exemplary system 700 for producing a chemical product based on the preparation specifications generated according to the present invention is shown. In this example, the system includes a user interface 710 and a processor 720 associated with a control unit 740. The user interface 710 and the processor 720 can be associated with or implemented according to the above principles, and in particular can be adapted to execute a computer-implemented method to determine the target preparation and / or preparation specifications based on the biodegradability determined as described above. The control unit 740 is configured, for example, to receive control data generated according to the present invention as described above, in particular to receive control data generated based on the preparation specifications of a preparation containing the target biodegradability. In this example, the control data is provided by a database 730, however, in other examples, the control data can also be provided by a server or any other computing unit for distributing data. Containers 750, 752 each contain components of the chemical product, such as components of the preparation, catalysts, etc. Generally, there are more than two containers, however, in this example, for illustrative purposes, only two containers are shown. Valves 760, 762 are associated with containers 750, 752. According to the preparation specifications, valves 750 and 752 can be controlled to incorporate appropriate amounts of each component into the reactor 770. The motor 800 of the mixer 780 can also be controlled by the control unit according to the preparation specifications. The optional heater 790 can also be controlled according to the preparation specifications. Finally, the outlet valve 810 in fluid communication with the reactor can be controlled by the control unit to provide the chemical product to a container or a test system 820.

[0091] In the following, a more detailed example of a biodegradation model is described. In this example, the biodegradation model is trained based on a training data set including one hundred or more data points, for example, trained according to specific criteria such as OECD 301a-f. These data points include corresponding formulations, including composition and biodegradation. The composition of the formulation can be defined using the ID and amount of the chemical components of the formulation. To train or apply the biodegradation model, the chemical components of the formulation can then be classified into predefined or learned group classifications. For example, these classifications can include solvents, surfactants, pigments, etc. For each component of the classification, predefined descriptors can be provided, for example, stored on a corresponding database or exported, as described in more detail above. The descriptors can be partition coefficient, functional group count, pKa value, molar mass distribution, glass transition temperature, etc. In addition, the biodegradability according to specific criteria (e.g., OECD 301a-f) of individual components can be used as a descriptor. Calculated descriptors such as calculated polarity, partition coefficient, critical micelle concentration, solubility, etc. can also be used. In addition, if the chemical structure of the component is known, molecular fingerprints such as Morgan fingerprints can also be used as descriptors. The descriptors of the corresponding classifications can be normalized within the group classification, for example, using z-score normalization. In addition, if water is a component used in the formulation, this component can be removed from the list of components, and the remaining components can be normalized to 100 wt%. Then, for each descriptor, the descriptor values of all components can be derived from the group classification of the given formulation, for example, as an average descriptor value or a minimum or maximum descriptor value. For example, average can mean using the weight fraction of the individual components without water in the formulation as a weighting factor. In the case of Morgan count fingerprints, the weight%-weighted fingerprints of the individual components of the group classification can be summed. The total amount of the weight fractions within each group classification can also be used as a descriptor. In addition, in addition to the descriptors, the calculated properties of the formulation can be additionally used as inputs to the biodegradation model, such as viscosity, solids content, etc. Based on these input parameters of the formulation, a random forest algorithm as a biodegradation model can be trained to determine the amount of biodegradation in the habitat, for example, according to specific criteria such as OECD 301a-f. The biodegradation model can be parameterized based on the corresponding training data set. In addition, a corresponding test data set can be used to test and validate the trained biodegradation model. The data of the training data set and the test data set can be obtained by measuring the biodegradation of the corresponding formulation in the corresponding habitat in a comparable manner, for example, according to the standard OECD 301a-f. In addition, existing databases, publicly available data sets or literature can also be utilized.An example of the biodegradation data of a published polymer blend can be found, for example, in "Blends of PBAT with plasticized starch for packaging applications: mechanical properties, rheological behavior can biodegradability" by M. Dammak et al., Industrial Crops & Products, 144, 112061 (2020).

[0092] Generally speaking, for example, the present invention relates to a method for determining the biodegradability of a new formulation. For example, in a first step, a digital representation of the formulation can be provided. The digital representation can be a formula, a structural formula, a trade name, a CAS number, etc. In an optional step, the target application of the new formulation can be provided. In a second step, a habitat can be selected. In this context, the term "habitat" is the biological environment in which the biodegradability should be evaluated. Depending on the habitat, other parameters can also be relevant and then these parameters are provided. In one embodiment, the habitat can be selected based on the target application. For example, for personal care products such as shampoos, it is usually desired that they decompose in wastewater. Therefore, for this example, the automatic selection will select wastewater as the habitat.

[0093] Generally, biodegradation models can be based on habitat descriptors that are dominant in the habitat. Therefore, different biodegradation models can be selected based on the input habitat. Thus, in a preferred workflow, the biodegradation model is selected based on the habitat. When selecting the inputs for the model, the model can indicate that further inputs are required, such as further formulation characterization parameters, etc., and then further inputs can be requested. This can be done by providing a list of the required parameters that should be provided. The formulation characterization parameter values are derived from the digital representation of the formulation, which form the inputs to the model. Based on the habitat descriptors and the characterization parameters, a measure of biodegradability can be determined and provided. In an optional step, a representation of biodegradability can be selected. In this case, the output is based on this selection. Potential representations of biodegradability can be one or more of mineralization (referring to whether the formulation is completely mineralized or the time required to reach mineralization), biotransformation (referring to a change in the chemical structure resulting in the loss of specific properties of the formulation, such as toxicity or the time required to reach that property), and half-life (referring to the time required for the formulation to decompose by 50%). The main habitats are the ocean, wastewater, and soil. For the ocean, the following parameters can affect biodegradation: salt concentration, sediment, water temperature, bacterial culture, etc. In some examples, the ocean habitat descriptors can be stored in a database together with the geographical location. In this case, the geographical location can be input, and the parameter values related to that geographical location can be retrieved from the database. For wastewater, the following parameters can affect biodegradation: temperature, number of bacteria, type of bacteria, enzyme concentration, enzymes. For soil, the following parameters can affect biodegradation: temperature, number of bacteria, type of bacteria, enzyme concentration, enzymes.

[0094] By studying the drawings, the disclosure, and the appended claims, those skilled in the art will be able to understand and realize other variations of the disclosed embodiments when practicing the claimed invention.

[0095] For the processes and methods disclosed herein, the operations performed in the processes and methods can be implemented in a different order. In addition, the operations outlined are provided only as examples, and some of these operations can be optional, combined into fewer steps and operations, supplemented with further operations, or extended to additional operations without departing from the essence of the disclosed embodiments.

[0096] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality.

[0097] A single unit or device can perform the functions of several items recited in the claims. The fact that certain measures are recited only in mutually different dependent claims does not mean that a combination of these measures cannot be used advantageously.

[0098] Processes performed by one or several units or devices, such as providing a formulation and biodegradation model, determining biodegradability, providing biodegradability, etc., can be performed by any other number of units or devices. These processes can be implemented as program code components of a computer program and / or dedicated hardware.

[0099] A computer program product can be stored / distributed on a suitable medium (such as an optical storage medium or a solid state medium), supplied together with or as part of other hardware, but can also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0100] Any unit described herein can be a processing unit as part of a classical computing system. The processing unit can include a general-purpose processor and can also include a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or any other specialized circuit. Any memory can be a physical system memory, which can be volatile, non-volatile, or some combination of both. The term "memory" can include any computer-readable storage medium, such as a non-volatile mass storage device. If the computing system is distributed, then the processing and / or memory capabilities can also be distributed. The computing system can include a plurality of structures as "executable components". The term "executable component" is a term for a structure that is well understood in the computing field to be a structure that can be software, hardware, or a combination thereof. For example, when implemented in software, those of ordinary skill in the art will understand that the structure of an executable component can include software objects, routines, methods, etc. that can be executed on a computing system. This can include executable components in the heap of a computing system or on a computer-readable storage medium. The structure of an executable component can exist on a computer-readable medium such that when interpreted by one or more processors (e.g., by a processor thread) of the computing system, it causes the computing system to perform a function. Such a structure can be directly computer-readable by a processor, for example, as in the case where the executable component is binary, or it can be structured such that it can be interpreted and / or compiled, for example, either in a single stage or in multiple stages, to produce such binary that can be directly interpreted by a processor. In other instances, the structure can be hard-coded or hard-wired logic gates that are implemented exclusively or nearly exclusively in hardware, such as within a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or any other specialized circuit. Thus, the term "executable component" is a term for a structure that is well understood by those of ordinary skill in the computing field, whether implemented in software, hardware, or a combination. Any implementation described herein is described with reference to actions performed by one or more processing units of a computing system. If such actions are implemented in software, then one or more processors, in response to having executed computer-executable instructions that constitute an executable component, direct the operation of the computing system. The computing system can also include a communication channel that allows the computing system to communicate with other computing systems, for example, via a network. A "network" is defined as one or more data links that enable the transfer of electronic data between computing systems and / or modules and / or other electronic devices. When information is passed or provided to a computing system via a network or another communication connection (e.g., hardwired, wireless, or a combination of hardwired and wireless), the computing system appropriately treats that connection as a transmission medium. The transmission medium can include a network and / or a data link that can be used to carry the desired program code components in the form of computer-executable instructions or data structures and that can be accessed by a general-purpose or specialized computing system or combination.While not all computing systems require a user interface, in some embodiments, a computing system includes a user interface system for interacting with a user. The user interface serves as an input or output mechanism for the user, for example, via a display.

[0101] Those skilled in the art will understand that at least portions of the present invention may be practiced in a network computing environment having many types of computing system configurations, including personal computers, desktop computers, laptop computers, messaging processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, pagers, routers, switches, data centers, wearable devices (such as glasses), and the like. The present invention may also be practiced in a distributed system environment where local and remote computing systems that are linked, for example, by a hardwired data link, a wireless data link, or a combination of hardwired and wireless data links, both perform tasks through the network. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

[0102] Those skilled in the art will also understand that at least a portion of the present invention may be practiced in a cloud computing environment. The cloud computing environment may be distributed, although this is not required. When distributed, the cloud computing environment may be distributed internationally within an organization and / or have components owned by multiple organizations. In this specification and the following claims, "cloud computing" is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage devices, applications, and services). The definition of "cloud computing" is not limited to any of the numerous other advantages that may be obtained from such a model at the time of deployment. The computing systems in the figures include various components or functional blocks that may implement the various embodiments disclosed herein as explained. The various components or functional blocks may be implemented on a local computing system or on a distributed computing system that includes elements residing in the cloud or that implements aspects of cloud computing. The various components or functional blocks may be implemented as software, hardware, or a combination of software and hardware. The computing systems shown in the figures may include more or fewer components than those shown in the figures, and some of the components may be combined when the environment permits.

[0103] Any reference numerals in the claims should not be construed as limiting the scope.

[0104] The present invention relates to a method for determining the biodegradability of a formulation. A digital representation of the formulation is provided that indicates the physicochemical characteristics of the formulation. Additionally, a habitat is provided that indicates habitat descriptor values that affect the biodegradation of the formulation. The habitat descriptor indicates the environmental characteristics of the habitat. A biodegradation model is provided based on the habitat, wherein the biodegradation model is adapted to determine the biodegradability of the formulation in the corresponding habitat, and wherein the biodegradation model is a data-driven model parameterized with respect to the habitat such that the biodegradation model can determine the biodegradability of the formulation based on the physicochemical characteristics. Then, the biodegradability of the formulation is determined based on the provided biodegradation model and the digital representation of the formulation.

Claims

1. A computer-implemented method for determining biodegradability that can be used to verify the biodegradation of a formulation, wherein the method (200) comprises: providing (210) a digital representation of the formulation, providing (220) a biodegradation habitat, wherein the biodegradation habitat indicates habitat descriptor values of habitat descriptors that affect the biodegradation of the formulation in the corresponding habitat, and wherein the habitat descriptors indicate environmental characteristics of the habitat, providing (230) a biodegradation model based on the provided biodegradation habitat, wherein the biodegradation model is adapted to determine the biodegradability of the formulation in the corresponding biodegradation habitat, and wherein the biodegradation model is a data-driven model parameterized with respect to the biodegradation habitat such that the biodegradation model can determine the biodegradability of the formulation based on the digital representation of the formulation, and determining (240) the biodegradability of the formulation based on the provided biodegradation model and the digital representation of the formulation.

2. The method according to claim 1, wherein the method further comprises providing a biodegradation test method, wherein the provided biodegradation test method indicates a standardized biodegradation test method for experimentally determining the biodegradation of a chemical, and wherein the biodegradation model is further provided based on the provided biodegradation test method.

3. The method according to any one of the preceding claims, wherein the biodegradation habitat refers to any one of a marine habitat, a wastewater habitat, a lake habitat, a composting habitat, an anaerobic habitat, or a soil habitat.

4. The method according to claim 3, wherein the biodegradation habitat refers to a marine habitat, and wherein the habitat descriptor refers to at least one of salt concentration, sedimentation type, oxygen level, location, sample depth, water temperature, nutrient concentration, pH value, environmental type, and microbial community.

5. The method according to claim 3, wherein the biodegradation habitat refers to wastewater, and the habitat descriptor refers to at least one of water temperature, microbial community, sludge concentration, nutrient concentration, pH value, test duration, and enzyme environment.

6. The method according to claim 3, wherein the biodegradation habitat refers to soil, and the habitat descriptor refers to at least one of temperature, sand content, pH value, water content, nutrient concentration, microbial community, and enzyme environment.

7. The method according to claim 3, wherein the biodegradation habitat refers to compost, and the habitat descriptor refers to at least one of temperature, compost activity, pH value, water content, humidity, compost maturity, compost composition, compost source, nutrient concentration, microbial community, and enzyme environment.

8. The method according to any one of the preceding claims, wherein the habitat descriptor values of the habitat descriptors are stored in association with the corresponding geographical location, and wherein providing the biodegradation habitat refers to providing the geographical location of the habitat and retrieving the habitat descriptor values of the geographical location from a storage device.

9. An interface method for providing an interface, wherein the interface method comprises: Receiving a digital representation and a habitat as inputs via a user interface, and providing the received digital representation and habitat to a processor that executes the method according to any one of claims 1 to 8, and Providing, via the user interface, the biodegradability of the measured preparation to the user as a result, where the result is received from the processor that executes the method according to any one of claims 1 to 8.

10. A computer-implemented training method for training a data-driven biodegradation model to parameterize the biodegradation model, where the training method (300) includes:[[]] Providing (310) training data associated with a predetermined biodegradation habitat, where the training data includes a) digital representations of a plurality of training preparations, and b) the biodegradability of the corresponding biodegradation habitat associated with each training preparation, Providing (320) a data-driven trainable biodegradation model, Training (330) the provided data-driven biodegradation model based on the provided training data such that the trained biodegradation model is adapted to determine the biodegradation of a preparation based on the digital representation of the preparation, and Providing (340) the trained biodegradation model.

11. A device for determining the biodegradability that can be used to verify the biodegradation of a predetermined preparation, where the device (110) includes:[[]] A digital representation providing unit (111) for providing a digital representation of the preparation, A habitat providing unit (112) for providing a biodegradation habitat, where the biodegradation habitat indicates a habitat descriptor value of a habitat descriptor that affects the biodegradation of the preparation in the corresponding habitat, and where the habitat descriptor indicates the environmental characteristics of the habitat, A model providing unit (113) for providing a biodegradation model based on the provided biodegradation habitat, where the biodegradation model is adapted to determine the biodegradability of a preparation in the corresponding biodegradation habitat, and where the biodegradation model is a data-driven model parameterized with respect to the biodegradation habitat such that the biodegradation model determines the biodegradation of a preparation based on the digital representation, and A determination unit (114) for determining the biodegradability of the preparation based on the selected biodegradation model and the digital representation of the preparation.

12. An interface device for providing an interface, where the interface device includes:[[]] An input interface unit for receiving a digital representation and a habitat as inputs via a user interface and providing the received digital representation and the habitat to the device according to claim 11, and A result interface for providing, via the user interface, the biodegradability of the measured preparation to the user as a result, where the result is received from the device according to claim 11.

13. A training device for training a data-driven biodegradation model to parameterize the biodegradation model, where the training device (120) includes:[[]] A training data providing unit (121) for providing training data associated with a predetermined biodegradable habitat, wherein the training data includes a) digital representations of a plurality of training agents, and b) biodegradability of the corresponding biodegradable habitat associated with each training agent. A trainable model providing unit (122) for providing a data-driven trainable biodegradation model. A training unit (123) for training the provided data-driven biodegradation model based on the provided training data, such that the trained biodegradation model is adapted to determine the biodegradation of an agent based on the digital representation of the agent, and A trained model providing unit (124) for providing the trained biodegradation model.

14. A computer program product for determining the biodegradability of a predetermined agent, wherein the computer program product includes program code means for causing the apparatus according to claim 11 to perform the method according to any one of claims 1 to 8.

15. A computer program product for training a biodegradation model, wherein the computer program product includes program code means for causing the apparatus according to claim 13 to perform the method according to claim 10.

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