A system can include one or more processors configured to access at least one parameter of a material, generate a plurality of structures of the material using the at least one parameter, determine a state of each structure of the plurality of structures using the at least one parameter, determine a difference between the state of each structure of the plurality of structures and a ground state value, evaluate a convergence condition responsive to determining the difference between the state of each structure of the plurality of structures and the ground state value, and output at least one structure of the plurality of structures responsive to the convergence condition being satisfied.

A system can include one or more processors configured to access at least one parameter of a material, generate a plurality of structures of the material using the at least one parameter, determine a state of each structure of the plurality of structures using the at least one parameter, determine a difference between the state of each structure of the plurality of structures and a ground state value, evaluate a convergence condition responsive to determining the difference between the state of each structure of the plurality of structures and the ground state value, and output at least one structure of the plurality of structures responsive to the convergence condition being satisfied.

An inferring device includes one or more memories and one or more processors. The one or more processors are configured to generate information on a tree including information on a node and information on an edge from a latent representation by using a trained inference model; and generate a graph from the information on the tree. The information on the tree includes connection information on the nodes.

A data processing system configured for computer visualization of drugs for drug interaction information retrieval is disclosed. For each of multiple different substances and using a camera within the mobile or other computing device, imagery of at least one external characteristic of a physical body of the substance is acquired. An identity of each of the multiple different substances is determined based upon the at least one external characteristic from the acquired imagery. Drug interaction data is retrieved for each of the multiple different substances using the determined identities. Drug interaction data for at least one of the multiple different substances is correlated with at least one other of the multiple different substances. At least one generic substance and/or cost information of at least one of the multiple different substances is identified. The correlated drug interaction data, the at least one generic substance, and/or the cost information are displayed.

A system and method for molecular design and simulation is disclosed. In one aspect, a system for simulating a molecular structure includes a processor configured to simulate the molecular structure, a head-mounted display (HMD) configured to display the molecular structure, and at least one handheld input device. The input device may be configured to: receive input from a user, the input being indicative of movement of the handheld input device in 6 degrees-of-freedom (DoF), and selectively map, based on additional user input and at least one property of the molecular structure, one of the DoF to one of a plurality of defined techniques for altering the molecular structure. The processor may be configured to modify the molecular structure based on the received input as mapped to the selected defined technique.

A property display method includes obtaining variables and pieces of option data, determining compositions of compounds by selecting one of the pieces of option data for each of the variables, obtaining predicted property values corresponding to the compositions, obtaining experimental property values corresponding to the compositions, generating a map indicating the predicted property values at positions corresponding to the compositions, generating a first image in which the experimental property values are superimposed upon the map, outputting the first image to a display unit, obtaining a piece of compound identification information corresponding to a selected one of the experimental property values on the map, obtaining a piece of compound information data relating to the experimental property value, generating a second image including a compound data image indicating the compound information data and the first image, and outputting the second image to the display unit.

A property display method includes obtaining variables and pieces of option data, determining compositions of compounds by selecting one of the pieces of option data for each of the variables, obtaining predicted property values corresponding to the compositions, obtaining experimental property values corresponding to the compositions, generating a map indicating the predicted property values at positions corresponding to the compositions, generating a first image in which the experimental property values are superimposed upon the map, outputting the first image to a display unit, obtaining a piece of compound identification information corresponding to a selected one of the experimental property values on the map, obtaining a piece of compound information data relating to the experimental property value, generating a second image including a compound data image indicating the compound information data and the first image, and outputting the second image to the display unit.

In an example, a method includes receiving, at a computing device, information from a scanning electron microscope (SEM) device. The SEM device includes an energy-dispersive X-ray spectroscopy (EDS) detector, and the information including SEM/EDS data for multiple locations of a sample. The method also includes generating a compositional three-dimensional (3D) surface plot based on the SEM/EDS data. The compositional 3D surface plot includes quantitative atomic composition data for each location of the multiple locations of the sample.

Computer-implemented methods may include accessing a multi-dimensional embedding space that supports relating embeddings of molecules to predicted values of a given property of the molecules. The method may also include identifying one or more points of interest within the embedding space based on the predicted values. Each of the one or more points of interest may include a set of coordinate values within the multi-dimensional embedding space and may be associated with a corresponding predicted value of the given property. The method may further include generating, for each of the one or more points of interest, a structural representation of a molecule by transforming the set of coordinate values included in the point of interest using a decoder network. The method may include outputting a result that identifies, for each of the one or more points of interest, the structural representation of the molecule corresponding to the point of interest.

Computer-implemented methods may include accessing a multi-dimensional embedding space that supports relating embeddings of molecules to predicted values of a given property of the molecules. The method may also include identifying one or more points of interest within the embedding space based on the predicted values. Each of the one or more points of interest may include a set of coordinate values within the multi-dimensional embedding space and may be associated with a corresponding predicted value of the given property. The method may further include generating, for each of the one or more points of interest, a structural representation of a molecule by transforming the set of coordinate values included in the point of interest using a decoder network. The method may include outputting a result that identifies, for each of the one or more points of interest, the structural representation of the molecule corresponding to the point of interest.