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Type: Organization
Type: Organization
Atomic interaction potentials based on artificial neural networks
Avalon is a high-throughput task manager for computational science with a strong focus on longtime-running and API access ability.
BLAS source of choice
Dataset are embed within our packages
Base images for xenonpy project
Lime: Explaining the predictions of any machine learning classifier
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
Collection of data sets of molecules for a validation of properties inference
Sample code for "Predicting polymer-solvent miscibility using machine-learned Flory-Huggins interaction parameters
Pol II density estimated by statistical inference of transcription elongation rates by total RNA-seq
A knowledge graph for Materials Science.
Python module for quantum chemistry
Python module to perform high-throughput first-principles calculation in 'Xenonpy' package.
Docker files for building/running quantum ESPRESSO in docker
The ability to manipulate domains and domain walls underpins function in a range of next-generation applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properties, such approaches lack an internal feedback loop required for automation. Here, using a deep sequence-to-sequence autoencoder we automate the extraction of features of nanoscale ferroelectric switching from multichannel hyperspectral band-excitation piezoresponse force microscopy of tensile-strained PbZr0.2Ti0.8O3 with a hierarchical domain structure. Using this approach, we identify characteristic behavior in the piezoresponse and cantilever resonance hysteresis loops, which allows for the classification and quantification of nanoscale-switching mechanisms. Specifically, we are able to identify elastic hardening events which are associated with the nucleation and growth of charged domain walls. This work demonstrates the efficacy of unsupervised neural networks in learning features of the physical response of a material from nanoscale multichannel hyperspectral imagery and provides new capabilities in leveraging multimodal in operando spectroscopies and automated control for the manipulation of nanoscale structures in materials.
Template-free prediction of organic reaction outcomes
C library for finding and handling crystal symmetries
Crystallographic space group library in Python
XenonPy is a Python Software for Materials Informatics
A Web/API server to provide a searching and downloading service for pre-trained models
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.