Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing retrosynthesis using a neural network. One of the methods includes generating a prediction of a set of a plurality of predicted reactants that are combinable to generate a target compound, the generating comprising processing, for each of a plurality of candidate sets of reactants, a network input characterizing the candidate set using a neural network, determining, for each candidate set of the plurality of candidate sets, a score using the generated probabilities; and selecting a particular candidate set of one or more reactants using the determined scores.

A computer system and computational method for determining optimal solid-state methods for synthesis of an inorganic material that results in an output of recommended synthetic methods that can be implemented based on the recommendation. The method involves inputting a target inorganic material, querying structural data and thermodynamic data for the target inorganic material and reactant inorganic materials that can be used for its synthesis, enumerating possible synthetic reactions to construct a synthesis reaction database with a viable subset of the possible synthetic methods. The program generates a nucleation barrier metric and a competition metric that are combined to provide a recommendation of the synthetic procedures to the target inorganic material.

A computer system and computational method for determining optimal solid-state methods for synthesis of an inorganic material that results in an output of recommended synthetic methods that can be implemented based on the recommendation. The method involves inputting a target inorganic material, querying structural data and thermodynamic data for the target inorganic material and reactant inorganic materials that can be used for its synthesis, enumerating possible synthetic reactions to construct a synthesis reaction database with a viable subset of the possible synthetic methods. The program generates a nucleation barrier metric and a competition metric that are combined to provide a recommendation of the synthetic procedures to the target inorganic material.

A method and apparatus for monitoring and evaluation of a production of a functional material, wherein an assessment of steps taken by users based on a data basis results in reporting to the user of the extent to which predetermined properties of a functional material produced are attained in the event of variances in the steps taken.

A method and system for predicting performance of strains in processes, the strains being capable of fermentation of biomass for production of at least bio-ethanol, the method including the steps of: receiving a first process data set related to a performance of a first strain in a first process for producing bio-ethanol at a first site, receiving a second process data set related to a performance of a second strain in the first process for producing bio-ethanol at the first site, receiving a third process data set related to a performance of the first strain in a second process for producing bio-ethanol at a second site, the second site being different from the first site, and wherein the first, second and third process data sets each include one or more process profiles and/or process responses, determining a first correlation between the first process data set and the second process data set, and determining a second correlation between the first process data and the third process data, and reconstructing a fourth process data set related to a performance of the second strain in the second process for producing bio-ethanol at the second site by missing data imputation, wherein the fourth process data set is estimated based on the first correlation and the second correlation.

Platforms for enzymatic assays for biomarkers, including systems, methods, and measuring devices by which a biomarker, such as creatinine, is measured using a small amount of biological fluid, such as blood, plasma, or serum. The measuring device or biosensor can be a test strip including a layered active component assembly positioned between two outer layers which enables multi-step enzymatic reactions operating in kinetic and/or endpoint (in which the reaction is allowed to near completion), and generally includes multiple layers with primary enzyme(s), coupling enzyme(s), and reagents to produce an optical signal correlated to the concentration of a biomarker in the sample. The test strip can be read using a portable optical reader coupled to a smart phone or tablet.

Platforms for enzymatic assays for biomarkers, including systems, methods, and measuring devices by which a biomarker, such as creatinine, is measured using a small amount of biological fluid, such as blood, plasma, or serum. The measuring device or biosensor can be a test strip including a layered active component assembly positioned between two outer layers which enables multi-step enzymatic reactions operating in kinetic and/or endpoint (in which the reaction is allowed to near completion), and generally includes multiple layers with primary enzyme(s), coupling enzyme(s), and reagents to produce an optical signal correlated to the concentration of a biomarker in the sample. The test strip can be read using a portable optical reader coupled to a smart phone or tablet.

A computer-implemented method of designing a molecule and determining a route to synthesise the molecule is provided. The method comprises: receiving one or more desired properties of the molecule; generating one or more candidate molecules using a first machine learning technique that uses the one or more desired properties of the molecule as an input; and for at least one candidate molecule, computing one or more routes to synthesise the candidate molecule using a second machine learning technique.

A computer-implemented method of designing a molecule and determining a route to synthesise the molecule is provided. The method comprises: receiving one or more desired properties of the molecule; generating one or more candidate molecules using a first machine learning technique that uses the one or more desired properties of the molecule as an input; and for at least one candidate molecule, computing one or more routes to synthesise the candidate molecule using a second machine learning technique.

A method for predicting a yield of calcium in a calcium treatment process based on deep neural network as provided relates to a calcium treatment process of molten steel refining in the field of iron and steel metallurgy, and includes steps of: obtaining production and operation data information of each of charges and thereby constructing a dataset; training and testing a deep neural network based on constructed dataset to establish a prediction model; and based on the prediction model, predicting and calculating current yield of calcium by taking actual production and operation data information of each charge as input. The method can predict the yield of calcium in the calcium treatment process, is favorable for accurately controlling a calcium content of steel, can stably control the calcium treatment process, improve the calcium treatment effect, improve the product quality, and ensure the production stability.