Reactivity mapping methods are provided. A method may include: analyzing each of a group of inorganic particles to generate data about physical and/or chemical properties of the inorganic particles; and generating correlations between the properties of inorganic particles based on the data.

The present invention provides a method for forming a history of natural gas accumulation by using carbon isotopes by a pyrolysis experiment. The method includes: obtaining activation energy distribution and a frequency factor of light carbon methane; carrying out carbon isotope kinetics simulation of natural gas in a study area by using a spreadsheet function of Excel to obtain activation energy, a mass fraction and a frequency factor of heavy carbon methane; establishing a burial history and a thermal history of the study area based on geological data; and combining the activation energy distribution and frequency factor of the heavy carbon methane with the burial history and thermal history of the study area, and establishing an instantaneous curve, a cumulative curve and a stage cumulative curve of natural gas under geological conditions on a geologic time scale.

Methods, systems, and apparatus for generating a recipe for a concrete mixture, comprising: obtaining an optical characterization of a set of particles; determining, based on the optical characterization, physical characteristics of the set of particles; generating a multispherical approximation of the set of particles; selecting, based on the physical characteristics of the set of particles and from a database of performance rules, performance rules applicable to the set of particles; predicting performance of a proposed recipe for a concrete mixture formed from the set of particles by: determining a wet flowability rating of the proposed recipe based on the selected performance rules; and determining a dry packing rating of the proposed recipe based on the multispherical approximation; iteratively altering the proposed recipe and predicting performance of the altered proposed recipe until the predicted performance satisfies performance criteria to obtain a final recipe; and outputting the final recipe.

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.

According to at least one exemplary embodiment, a system, method, and apparatus for predicting physical properties by indirect measurement is disclosed. The system, method, and apparatus provide for measurement of physical properties of petroleum products by calculating predictions of the properties based on diverse inputs. These predictions may be updated in real time and may be used to modify various processes in midstream and downstream petroleum operations. Various use cases for the system, method, and apparatus for predicting physical properties by indirect measurement are disclosed.

A method and a system for material design utilizing machine learning are provided, where the underlying joint distribution p(S,P) of structure (S)-property (P) relationships is explicitly learned simultaneously and is utilized to directly generate samples (S,P) in a single step utilizing generative techniques, without any additional processing steps. The subspace of structures that meet or exceed the target for property P is then identified utilizing conditional generation of the distribution (e.g., p(P)), or through randomly generating a large number of samples (S,P) and filtering (e.g., selecting) those that meet target property criteria.

An information processing system according to an embodiment is configured to: acquire numerical representations and combination ratios for a plurality of component objects; acquire numerical representations for a plurality of reference objects; calculate a plurality of component feature vectors and a plurality of reference feature vectors by inputting the numerical representations of each of the plurality of component objects and the plurality of reference objects into a first machine learning model; calculate a probability vector for each of the plurality of component objects by inputting those feature vectors into a second machine learning model; and calculate a composite feature vector for a composite object obtained by combining the plurality of component objects, based on a plurality of probability vectors and a plurality of combination ratios.

The information processing apparatus, the information processing method, and the program include at least one processor configured to acquire, in at least one piece of processing of the process, at least one piece of information of chemical information or physical information of an object to be processed and a processed object at two points at which elapses of processing times between before the processing and after the processing are different from each other, acquire a calculation value of a difference between numerical values at the two points that are obtained from the information, and set the difference as an explanatory variable, set the quality of the product as an objective variable, and predict the quality of the product based on the calculation value by using a trained model obtained by performing machine learning based on a known data set of the explanatory variable and the objective variable.