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Solving the electronic structure problem with machine learning

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npj Computational Materials 2019年第1期5卷 959-965页

作者： Anand Chandrasekaran Deepak Kamal Rohit Batra Chiho Kim Lihua Chen rampi ramprasad School of Materials Science and Engineering Georgia Institute of Technology771 Ferst Dr.NWAtlantaGA 30332USA

Simulations based on solving the Kohn-Sham(KS)equation of density functional theory(DFT)have become a vital component of modern materials and chemical sciences research and development *** its versatility,routine DFT calculations are usually limited to a few hundred atoms due to the computational bottleneck posed by the KS *** we introduce a machine-learning-based scheme to efficiently assimilate the function of the KS equation,and by-pass it to directly,rapidly,and accurately predict the electronic structure of a material or a molecule,given just its atomic configuration.A new rotationally invariant representation is utilized to map the atomic environment around a grid-point to the electron density and local density of states at that *** mapping is learned using a neural network trained on previously generated reference DFT results at millions of *** proposed paradigm allows for the high-fidelity emulation of KS DFT,but orders of magnitude faster than the direct ***,the machine learning prediction scheme is strictly linear-scaling with system size.

关键词： solution. equation. structure

Machine learning in materials informatics:recent applications and prospects

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npj Computational Materials 2017年第1期3卷 1-13页

作者： rampi ramprasad Rohit Batra Ghanshyam Pilania Arun Mannodi-Kanakkithodi Chiho Kim Department of Materials Science&Engineering and Institute of Materials Science University of Connecticut97 North Eagleville Rd.Unit 3136StorrsCT 06269-3136USA Fritz-Haber-Institut der Max-Planck-Gesellschaft Faradayweg 4-614195 BerlinGermany Materials Science and Technology Division Los Alamos National LaboratoryLos AlamosNM 87545USA Center for Nanoscale Materials Lamont National Laboratory9700 S.Cass Ave.LemontIL 60439USA

Propelled partly by the Materials Genome Initiative,and partly by the algorithmic developments and the resounding successes of data-driven efforts in other domains,informatics strategies are beginning to take shape within materials *** approaches lead to surrogate machine learning models that enable rapid predictions based purely on past data rather than by direct experimentation or by computations/simulations in which fundamental equations are explicitly ***-centric informatics methods are becoming useful to determine material properties that are hard to measure or compute using traditional methods—due to the cost,time or effort involved—but for which reliable data either already exists or can be generated for at least a subset of the critical *** are typically interpolative,involving fingerprinting a material numerically first,and then following a mapping(established via a learning algorithm)between the fingerprint and the property of ***,also referred to as“descriptors”,may be of many types and scales,as dictated by the application domain and *** may also be extrapolative—extending into new materials spaces—provided prediction uncertainties are properly taken into *** article attempts to provide an overview of some of the recent successful data-driven“materials informatics”strategies undertaken in the last decade,with particular emphasis on the fingerprint or descriptor *** review also identifies some challenges the community is facing and those that should be overcome in the near future.

关键词： overcome subset properly

A universal strategy for the creation of machine learning-based atomistic force fields

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npj Computational Materials 2017年第1期3卷 146-153页

作者： Tran Doan Huan Rohit Batra James Chapman Sridevi Krishnan Lihua Chen rampi ramprasad Department of Materials Science&Engineering and Institute of Materials Science University of Connecticut97 North Eagleville Rd.Unit 3136StorrsCT 06269-3136USA

Emerging machine learning(ML)-based approaches provide powerful and novel tools to study a variety of physical and chemical *** this contribution,we outline a universal strategy to create ML-based atomistic force fields,which can be used to perform high-fidelity molecular dynamics *** scheme involves(1)preparing a big reference dataset of atomic environments and forces with sufficiently low noise,e.g.,using density functional theory or higher-level methods,(2)utilizing a generalizable class of structural fingerprints for representing atomic environments,(3)optimally selecting diverse and nonredundant training datasets from the reference data,and(4)proposing various learning approaches to predict atomic forces directly(and rapidly)from atomic *** the atomistic forces,accurate potential energies can then be obtained by appropriate integration along a reaction coordinate or along a molecular dynamics *** on this strategy,we have created model ML force fields for six elemental bulk solids,including Al,Cu,Ti,W,Si,and C,and show that all of them can reach chemical *** proposed procedure is general and universal,in that it can potentially be used to generate ML force fields for any material using the same unified workflow with little human ***,the force fields can be systematically improved by adding new training data progressively to represent atomic environments not encountered previously.

关键词： utilizing preparing selecting

Impact of oxygen-containing carbonyl and ether groups on dielectric properties of poly(oxa)norbornene cyclic olefins

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Journal of Advanced Dielectrics 2023年第4期13卷 65-68页

作者： Chao Wu Ajinkya A.Deshmukh Lihua Chen rampi ramprasad Gregory A.Sotzing Yang Cao Institute of Materials Science University of Connecticut StorrsCT 06269USA School of Materials Science and Engineering Georgia Institute of Technology AtlantaGA 30332USA Department of Electrical and Computer Engineering University of Connecticut StorrsCT 06269USA

Flexible dielectric polymers that can withstand high electric field and simultaneously have high dielectric constant are desired for high-density energy ***,we systematically investigated the impact of oxygen-containing ether and carbonyl groups in the backbone structure on dielectric properties of a series of cyclic *** comparison to the influence of the-CF3 pendant groups that had more impact on the dielectric constant rather than the band gap,the change of the backbone structure affected both the dielectric constant and band *** one polymer with ether and carbonyl groups in the backbone has the largest band gap and highest discharge efficiency,while it has the lowest dielectric *** polymer without any ether groups in the backbone has the smallest band gap and lowest discharge efficiency,but it has the highest dielectric *** that have no dipolar relaxation exhibit an inversely correlated dielectric constant and band *** the dipolar relaxation through rational molecular structure design can be a novel way to break through the exclusive constraint of dielectric constant and band gap for high-density energy storage.

关键词： Polymer dielectric band gap glass transition conduction energy density DFT

Frequency-dependent dielectric constant prediction of polymers using machine learning

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npj Computational Materials 2020年第1期6卷 1147-1155页

作者： Lihua Chen Chiho Kim Rohit Batra Jordan P.Lightstone Chao Wu Zongze Li Ajinkya A.Deshmukh Yifei Wang Huan D.Tran Priya Vashishta Gregory A.Sotzing Yang Cao rampi ramprasad School of Materials Science and Engineering Georgia Institute of Technology771 Ferst Drive NWAtlantaGA 30332USA Electrical and Computer Engineering University of Connecticut371 Fairfield WayStorrsCT 06269USA Polymer Program Institute of Material ScienceUniversity of Connecticut97 North Eagleville RoadStorrsCT 06269USA Collaboratory for Advanced Computing and Simulations University of Southern CaliforniaLos AngelesCA 90089-0242USA

The dielectric constant(ϵ)is a critical parameter utilized in the design of polymeric dielectrics for energy storage capacitors,microelectronic devices,and high-voltage ***,agile discovery of polymer dielectrics with desirableϵremains a challenge,especially for high-energy,high-temperature *** aid accelerated polymer dielectrics discovery,we have developed a machine-learning(ML)-based model to instantly and accurately predict the frequency-dependentϵof polymers with the frequency range spanning 15 orders of *** model is trained using a dataset of 1210 experimentally measuredϵvalues at different frequencies,an advanced polymer fingerprinting scheme and the Gaussian process regression algorithm.

关键词： dielectric constant polymer

A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing

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npj Computational Materials 2023年第1期9卷 1826-1837页

作者： Pranav Shetty Arunkumar Chitteth Rajan Chris Kuenneth Sonakshi Gupta Lakshmi Prerana Panchumarti Lauren Holm Chao Zhang rampi ramprasad School of Computational Science&Engineering AtlantaGAUSA School of Materials Science and Engineering Georgia Institute of Technology771 Ferst Drive NWAtlanta 30332 GAUSA Department of Metallurgy Engineering and Materials Science Indian Institute of TechnologyIndoreMadhya PradeshIndia

The ever-increasing number of materials science articles makes it hard to infer chemistry-structure-property relations from *** used natural language processing methods to automatically extract material property data from the abstracts of polymer *** a component of our pipeline,we trained MaterialsBERT,a language model,using 2.4 million materials science abstracts,which outperforms other baseline models in three out of five named entity recognition *** this pipeline,we obtained~300,000 material property records from~130,000 abstracts in 60 *** extracted data was analyzed for a diverse range of applications such as fuel cells,supercapacitors,and polymer solar cells to recover non-trivial *** data extracted through our pipeline is made available at *** which can be used to locate material property data recorded in *** work demonstrates the feasibility of an automatic pipeline that starts from published literature and ends with extracted material property information.

关键词： property insight pipeline

Noise degradation system using Wiener filter and CORDIC based FFT/IFFT processor

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Journal of Central South University 2015年第10期22卷 3849-3859页

作者： Yasodai A ramprasad A V Department of Electronics and Communication Engineering Vickram College of Engineering Department of Electronics and Communication Engineering K L N College of Engineering

On augmentation of past work, an effective Wiener filter and its application for noise suppression combined with a formed CORDIC based FFT/IFFT processor with improved speed were executed. The pipelined methodology was embraced for expanding the execution of the system. The proposed Wiener filter was planned in such an approach to evacuate the iteration issues in ordinary Wiener filter. The division process was supplanted by a productive inverse and multiplication process in the proposed design. An enhanced design for matrix inverse with reduced computation complexity was executed. The wide-ranging framework processing was focused around IEEE-754 standard single precision floating point numbers. The Wiener filter and the entire system design was integrated and actualized on VIRTEX 5 FPGA stage and re-enacted to approve the results in Xilinx ISE 13.4. The results show that a productive decrease in power and area is developed by adjusting the proposed technique for speech signal noise degradation with latency of n/2 clock cycles and substantial throughput result per every 12 clock cycles for n-bit precision. The execution of proposed design is exposed to be 31.35% more effective than that of prevailing strategies.

关键词： Wiener filter iterations power spectrum FFT/IFFT floating point noise suppression speech enhancement VLSI speed power area

Parental attitudes towards influenza vaccination for children in South India

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World Journal of Pediatrics 2017年第1期13卷 84-90页

作者： Chethan ramprasad Rajeev Zachariah Mark Steinhoff Anna Simon University of Miami Miller School of Medicine MiamiFloridaUSA Christian Medical College VelloreTamil NaduIndia Cincinnati Children's Hospital Medical Center CincinnatiOhioUSA Christian Medical College VelloreTamil NaduIndia

Background:The rate of influenza vaccination is low for children in *** purpose of this study is to assess parental attitudes towards influenza vaccination in South ***:Participants were parents who brought their children to the Well Baby Clinic of Christian Medical College Hospital,Vellore,India for routine *** answered questions by written survey while waiting for their children’s vaccination.

关键词： doctor recommendation influenza immunization parental attitudes vaccination

Synthesis and antimycobacterial screening of new N-(4-(5-aryl-3-(5-methyl-1,3,4-oxadiazol-2-yl)-1H-pyrazol-1-yl)phenyl)-4-amide derivatives

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Chinese Chemical Letters 2016年第3期27卷 365-369页

作者： Nagabhushana Nayak Jurupula ramprasad Udayakumar Dalimba Perumal Yogeeswari Dharmarajan Sriram Organic Chemistry Laboratory Department of ChemistryNational Institute of Technology Karnataka Medicinal Chemistry and Drug Discovery Research Laboratory Pharmacy GroupBirla Institute of Technology and Science-PilaniHyderabad Campus

This article demonstrates the synthesis, characterization and the study of in vitro antitubercular activities of twenty four new N-（4-（5-aryl-3-（5-methyl-1,3,4-oxadiazol-2-yl）-1H-pyrazol-1-yl）phenyl）-4-amide derivatives（8a–x）. The antitubercular activity of the compounds against Mycobacterium tuberculosis H37Rv（MTB） revealed that 2-chloro-N-（4-（5-（4-chlorophenyl）-3-（5-methyl-1,3,4-oxadiazol-2-yl）-1H-pyrazol-1-yl）phenyl）benzamide（8n） is the most promising lead molecule with a MIC of1.56 mg/m L, while the corresponding unsubstituted benzamide derivative（8o） is the next most active molecule with a MIC of 3.13 mg/m L. Interestingly, the pyrazole intermediate 5b containing chlorophenyl and N-acylcarbohydrazide substituents also showed significant activity（MIC = 3.13 mg/m L）. Further, the active molecules did not show toxicity against a normal NIH 3T3 cell line, signifying their suitability for further drug development.

关键词： Pyrazole-oxadiazole hybrids Antitubercular activity SC-XRD analysis In vitro cytotoxicity