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Articles

Convolutional neural networks for melt depth prediction and visualization in laser powder bed fusion - The International Journal of Advanced Manufacturing Technology

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By Barati Farimani, Carnegie Mellon
| link.springer.com
Abstract Powder bed fusion is a method of additive manufacturing (AM) where parts are constructed by iteratively melting metal cross-sections to build complex 3D structures. Defects often form during the printing process, where the dynamics of the melt pool can directly contribute to the formation of porous defects in the final part.
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GPT-MolBERTa: GPT Molecular Features Language Model for molecular property prediction

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By Barati Farimani, Rishikesh Magar, Amir Barati Farimani, Yayati Jadhav
| arxiv.org
[Submitted on 20 Sep 2023] Title:GPT-MolBERTa: GPT Molecular Features Language Model for molecular property prediction Download a PDF of the paper titled GPT-MolBERTa: GPT Molecular Features Language Model for molecular property prediction, by Suryanarayanan Balaji and Rishikesh Magar and Yayati Jadhav and and Amir BaratiFarimani Download PDF Abstract:With the emergence of Transformer architectures and their powerful understanding of textual data, a new horizon has opened up to predict the...
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Neural network predicts ion concentration profiles under nanoconfinement

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By Carnegie Mellon, Barati Farimani, J. Ma
| aip.org
Topics Molecular dynamics, Artificial neural networks, Machine learning, Decision theory, Probability theory, Nanochannels, Graphene, Electroosmosis, Ionic liquids, Electrical double layers Nanoconfinement defines a state when fluid is confined in nanoscale spaces, such as nanotube and nanochannel.1 Compared with bulk condition, nanoconfined fluids, such as water, exhibit anomalous viscosity,2,3 diffusion coefficient,4–6 phase,7,8 dynamics,9 and density.4,10,11 These behaviors become more...
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