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A gold standard for computational materials science codes

Physicists and materials scientists can choose from a whole family of computer codes that simulate the behavior of materials and predict their properties. The accuracy of the results obtained by t .

Switzerland generalGiovanni pizziEmanuele bosoniHossein mirhosseiniPaul scherrer instituteData groupNational centre for computational designMaterials softwareNature reviews physicsNational centreComputational designNovel materialsAdvanced systems understandingHelmholtz zentrum dresden rossendorfScientific managerMaterial science

Oxygen vacancies boost performance of aqueous zinc ion batteries, study finds

Oxygen vacancies boost performance of aqueous zinc ion batteries, study finds
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Yuqi pengLi zhaoqianChinese academy of scienceElectrochemical reaction kineticsDensity functional theoryHefei institutesPhysical scienceChinese academyOxygen vacanciesCharge transferAqueous zincIon batteries

Machine Learning Approaches for Accelerated Materials Discovery

The use of machine learning has provided a significant boost to the field of materials discovery, and experts are using this advanced technique to discover various types of materials.

Ibtisam abbasijanIbtisam abbasiUs department of energyOverview of machine learning for materials sciencesArgonne national laboratoryMaterials researchSummit artMachine learningAnnual reviewMolecular scienceAccelerated materials discoveryCrystallographic symmetryPhysical chemistryInorganic crystal structure databaseDensity functional theoryScientists use machine learning

Catalytic combo converts CO2 to solid carbon nanofibers

Scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and Columbia University have developed a way to convert carbon dioxide (CO2), a potent greenhouse gas, into carbo .

Jingguang chenZhenhua xieSooyeon hwangNational synchrotron light sourceBrookhaven labBrookhaven chemistry divisionQuickx ray absorptionInner shell spectroscopyElectron microscopyFunctional nanomaterialsPing liuChemistry divisionCarbon dioxideCarbon nanofibersElectrochemical reactionsCarbon emissions

Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries

Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries
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South koreaKyongsang buktoSoult ukpyolsiHyunguk kwonJeonghyun koMonte carloKyeounghak kimYeongjun yoonUniversity of notre damePennsylvania state universityDepartment of materials scienceGeorgia institute of technologyBattery rd centerA software package for deep potential modelsEnergy lettUniversity of seoul