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Loading metrics Open Access Peer-reviewed Research Article Abstract A transfomer oil immersion cooling server is designed and constructed for machine learning applications and first principle calculations that are carried out for materials-related research. CPU, motherboard, random access memory, hard disk drive, solid state drive, graphic card, and the power supply unit are submerged into the transformer oil in order to cool the entire system.
High-Throughput Screening and Literature Data Driven Machine Learning Assisting Investigation of Multi-component La2O3-based Catalysts for Oxidative Coupling of Methane Multi-component La2O3-based catalysts for oxidative coupling of methane (OCM) were designed based on high-throughput screening (HTS) and literature datasets with multi-output machine learning (ML) approaches including random forest regression (RFR), support vector regression (SVR), Gaussian process regression (Bayesian), and...
Transition of wide-band gap semiconductor h-BN(BN)/P heterostructure via single-atom-embedding The transition of band gap in boron nitride/phosphorene(h-BN/P) heterostructure are investigated by single-atom-embedding via first principles calculations. In particular, the single-atom-embedded heterostructures are designed by embedding 10 different single atoms between h-BN/P bilayers to compare the property transition against pure h-BN/P heterostructure.
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