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CrysXPP:An explainable property predictor for crystalline materials

npj Computational Materials 2022年第1期8卷 424-434页

作者： Kishalay Das Bidisha Samanta pawan goyal Seung-Cheol Lee Satadeep Bhattacharjee Niloy Ganguly Indian Institute of Technology Kharagpur KharagpurIndia Indo Korea Science and Technology Center BangaloreIndia Leibniz University of Hannover HannoverGermany

We present a deep-learning framework,CrysXPP,to allow rapid and accurate prediction of electronic,magnetic,and elastic properties of a wide range of *** lowers the need for large property tagged datasets by intelligently designing an autoencoder,*** important structural and chemical properties captured by CrysAE from a large amount of available crystal graphs data helped in achieving low prediction ***,we design a feature selector that helps to interpret the model’s *** notably,when given a small amount of experimental data,CrysXPP is consistently able to outperform conventional DFT.A detailed ablation study establishes the importance of different design *** release the large pre-trained model *** believe by fine-tuning the model with a small amount of property-tagged data,researchers can achieve superior performance on various applications with a restricted data source.

关键词： materials. property crystalline

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An artificial neural network for surrogate modeling of stress fields in viscoplastic polycrystalline materials

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npj Computational Materials 2023年第1期9卷 1981-1990页

作者： Mohammad S.Khorrami Jaber R.Mianroodi Nima H.Siboni pawan goyal Bob Svendsen Peter Benner Dierk Raabe Microstructure Physics and Alloy Design Max-Planck-Institut für EisenforschungDüsseldorfGermany Ergodic Labs Lohmühlenstraße 6512435 BerlinGermany Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical SystemsMagdeburgGermany Material Mechanics RWTH Aachen UniversityAachenGermany

The purpose of this work is the development of a trained artificial neural network for surrogate modeling of the mechanical response of elasto-viscoplastic grain *** this end,a U-Net-based convolutional neural network(CNN)is trained using results for the von Mises stress field from the numerical solution of initial-boundary-value problems(IBVPs)for mechanical equilibrium in such microstructures subject to quasi-static uniaxial *** resulting trained CNN(tCNN)accurately reproduces the von Mises stress field about 500 times faster than numerical solutions of the corresponding IBVP based on spectral *** of the tCNN to test cases based on microstructure morphologies and boundary conditions not contained in the training dataset is also investigated and discussed.

关键词： methods boundary faster

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A model on the biological treatment of saline wastewater

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International Journal of Biomathematics 2017年第2期10卷 111-126页

作者： Ashish goyal pawan Sharma School of Mathematics and Statistics The University of New South Wales Sydney NSW 2052 Australia Radisys Bangalore Karnataka India

Water scarcity is not a new issue, neither is water pollution. While 70% of the earth＇s surface is covered with water, only 3% of it is available as fresh water. Moreover the pollution of water resources has dramatically increased the problem of water scarcity over the last century. Bioremediation presents a cheap and effective solution of this problem. In particular, halophiles have been found to be effective in hypersaline wastewater treatment. Therefore, in this paper, we propose a nonlinear mathematical model to study the removal of a pollutant using halophiles in the hypersaline environment. The analysis of the model is being carried out using stability theory of differential equations. The results indicate that halophiles not only help in removing the organic pollutant, but also help in conversion of saline water into fresh water. The numerical simulations along with sensitivity analysis are performed to support the analytical results.

关键词： Halophiles desalination wastewater treatment pollutant mathematical model

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Malignant peripheral nerve sheath tumor of proximal third tibia

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World Journal of Clinical Oncology 2015年第5期6卷 179-183页

作者： Arunkumar Rao Sachin B Ingle pawan Rajurkar Vishav goyal Nikhil Dokrimare Department of Orthopedics Maharashtra Institute of Medical Sciences and ResearchMedical College Department of Pathology Secretary Research and Development and Institutional Review BoardMaharashtra Institute of Medical Sciences and ResearchMedical College

A 16-year-old man had aswelling over the anterior aspect of the proximal third of the tibia for 1 year, which was peanut size initially and progressively increased to its present size of 10 cm × 8 cm. He underwent fine needle aspiration cytology(FNAC) twice during this period and reported aspindle cell sarcoma. Malignant peripheral nerve sheath tumor(MPNST) is a malignancy of the connective tissue surrounding the nerves. Previously, MPNST was also known as neurofibrosarcoma, malignant schwannoma, andneurogenic sarcoma. We are reporting this case for its rarity and peculiar mode of presentation. FNAC/core biopsy can be used as an effective tool to achievethe correct pathological diagnosis.

关键词： Tibial malignant peripheral nerve sheath tumor Fine needle aspiration cytology Histopathology

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