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Markus J. Buehler
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Journal Articles

X-LoRA: Mixture of low-rank adapter experts, a flexible framework for large language models with applications in protein mechanics and molecular design

Eric L. Buehler, Markus J. Buehler
Journal: APL Machine Learning
APL Mach. Learn. 2, 026119 (2024)
https://doi.org/10.1063/5.0203126
Published: May 2024
View article titled, X-LoRA: Mixture of low-rank adapter experts, a flexible framework for large language models with applications in protein mechanics and molecular design
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Includes: Supplementary data
Journal Articles

Generative pretrained autoregressive transformer graph neural network applied to the analysis and discovery of novel proteins

Markus J. Buehler
Journal: Journal of Applied Physics
J. Appl. Phys. 134, 084902 (2023)
https://doi.org/10.1063/5.0157367
Published: August 2023
View article titled, Generative pretrained autoregressive transformer graph neural network applied to the analysis and discovery of novel proteins
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Journal Articles

Generative discovery of de novo chemical designs using diffusion modeling and transformer deep neural networks with application to deep eutectic solvents

Rachel K. Luu, Marcin Wysokowski, Markus J. Buehler
Journal: Applied Physics Letters
Appl. Phys. Lett. 122, 234103 (2023)
https://doi.org/10.1063/5.0155890
Published: June 2023
View article titled, Generative discovery of <em>de novo</em> chemical designs using diffusion modeling and transformer deep neural networks with application to deep eutectic solvents
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Includes: Supplementary data
Journal Articles

DyFraNet: Forecasting and backcasting dynamic fracture mechanics in space and time using a 2D-to-3D deep neural network

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Yu-Chuan Hsu, Markus J. Buehler
Journal: APL Machine Learning
APL Mach. Learn. 1, 026105 (2023)
https://doi.org/10.1063/5.0135015
Published: April 2023
View article titled, DyFraNet: Forecasting and backcasting dynamic fracture mechanics in space and time using a 2D-to-3D deep neural network
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Journal Articles

Deep language models for interpretative and predictive materials science

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Yiwen Hu, Markus J. Buehler
Journal: APL Machine Learning
APL Mach. Learn. 1, 010901 (2023)
https://doi.org/10.1063/5.0134317
Published: February 2023
View article titled, Deep language models for interpretative and predictive materials science
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Journal Articles

Rapid mechanical property prediction and de novo design of three-dimensional spider webs through graph and GraphPerceiver neural networks

FeaturedScilight
Wei Lu, Zhenze Yang, Markus J. Buehler
Journal: Journal of Applied Physics
J. Appl. Phys. 132, 074703 (2022)
https://doi.org/10.1063/5.0097589
Published: August 2022
View article titled, Rapid mechanical property prediction and <em>de novo</em> design of three-dimensional spider webs through graph and GraphPerceiver neural networks
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Includes: Supplementary data
Journal Articles

Generative design, manufacturing, and molecular modeling of 3D architected materials based on natural language input

Yu-Chuan Hsu, Zhenze Yang, Markus J. Buehler
Journal: APL Materials
APL Mater. 10, 041107 (2022)
https://doi.org/10.1063/5.0082338
Published: April 2022
View article titled, Generative design, manufacturing, and molecular modeling of 3D architected materials based on natural language input
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Includes: Supplementary data
Journal Articles

A deep learning augmented genetic algorithm approach to polycrystalline 2D material fracture discovery and design

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Andrew J. Lew, Markus J. Buehler
Journal: Applied Physics Reviews
Appl. Phys. Rev. 8, 041414 (2021)
https://doi.org/10.1063/5.0057162
Published: December 2021
View article titled, A deep learning augmented genetic algorithm approach to polycrystalline 2D material fracture discovery and design
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Journal Articles

Sonification based de novo protein design using artificial intelligence, structure prediction, and analysis using molecular modeling

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Chi-Hua Yu, Markus J. Buehler
Journal: APL Bioengineering
APL Bioeng. 4, 016108 (2020)
https://doi.org/10.1063/1.5133026
Published: March 2020
View article titled, Sonification based <em>de novo</em> protein design using artificial intelligence, structure prediction, and analysis using molecular modeling
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Includes: Supplementary data
Journal Articles

Atomistic model of the spider silk nanostructure

Sinan Keten, Markus J. Buehler
Journal: Applied Physics Letters
Appl. Phys. Lett. 96, 153701 (2010)
https://doi.org/10.1063/1.3385388
Published: April 2010
View article titled, Atomistic model of the spider silk nanostructure
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Journal Articles

Meso-origami: Folding multilayer graphene sheets

Steven Cranford, Dipanjan Sen, Markus J. Buehler
Journal: Applied Physics Letters
Appl. Phys. Lett. 95, 123121 (2009)
https://doi.org/10.1063/1.3223783
Published: September 2009
View article titled, Meso-origami: Folding multilayer graphene sheets
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Journal Articles

Microscale structural model of Alzheimer A β ( 1 – 40 ) amyloid fibril

Raffaella Paparcone, Markus J. Buehler
Journal: Applied Physics Letters
Appl. Phys. Lett. 94, 243904 (2009)
https://doi.org/10.1063/1.3148641
Published: June 2009
View article titled, Microscale structural model of Alzheimer A β ( 1 – 40 ) amyloid fibril
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Magazine Articles

Plasticity and toughness in bone

Robert O. Ritchie, Markus J. Buehler, Paul Hansma
Journal: Physics Today
Physics Today 62, 41–47 (2009)
https://doi.org/10.1063/1.3156332
Published: June 2009
View article titled, Plasticity and toughness in bone
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