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Treffer 1 - 25 von 29205, Suchdauer: 0.55s

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1
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models

von Creed, Isabel ; Rein, Tim ; Vitenburgs, Ingvars ; et al.

Schlagworte: Materials Science; Disordered Systems and Neural Networks; Applied Physics; Computational Physics
- View full text via Arxiv
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2
Conditional Generative Models Enable Targeted Exploration of MAX Phase Design Space

von Swain, Jamie ; Bone, Cyprien ; Darby, Matthew T. ; et al.

Schlagworte: Materials Science
- View full text via Arxiv
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3
Materials Informatics Across the Length Scales

von Nasir, Jamal Abdul ; Kavak, Hamide ; Der, Oguzhan ; et al.

Schlagworte: Materials Science
- View full text via Arxiv
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4
A Shift-Invariant Deep Learning Framework for Automated Analysis of XPS Spectra

von Saddiq, Issa ; Fan, Yuxin ; Palgrave, Robert G. ; et al.

Schlagworte: Materials Science
- View full text via Arxiv
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5
Discovering new photovoltaics using optimal transport theory

von Walker, Matthew A. H. ; Zhou, Zibo ; Islam, Junayd Ul ; et al.

Schlagworte: Materials Science; Disordered Systems and Neural Networks
- View full text via Arxiv
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6
Discovery and recovery of crystalline materials with property-conditioned transformers

von Bone, Cyprien ; Walker, Matthew ; Martin, Bradley A. A. ; et al.

Schlagworte: Materials Science; Disordered Systems and Neural Networks
- View full text via Arxiv
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7
Infrared spectral signatures of light r-process elements in kilonovae

von Jerkstrand, Anders ; Pognan, Quentin ; Banerjee, Smaranika ; et al.

Schlagworte: Solar and Stellar Astrophysics; High Energy Astrophysical Phenomena
- View full text via Arxiv
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8
General Learning of the Electric Response of Inorganic Materials

von Martin, Bradley A. A. ; Ganose, Alex M. ; Kapil, Venkat ; et al.

Schlagworte: Materials Science
- View full text via Arxiv
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9
A literature-derived dataset of migration barriers for quantifying ionic transport in battery materials

von Devi, Reshma ; Balasubramanian, Avaneesh ; Butler, Keith T. ; et al.

Schlagworte: Materials Science
- View full text via Arxiv
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10
Leveraging transfer learning for accurate estimation of ionic migration barriers in solids

von Devi, Reshma ; Butler, Keith T. ; Gautam, Gopalakrishnan Sai

Schlagworte: Materials Science
- View full text via Arxiv
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11
Learning disentangled latent representations facilitates discovery and design of functional materials

von Cha, Jaehoon ; Lu, Tingyao ; Walker, Matthew ; et al.

Schlagworte: Materials Science
- View full text via Arxiv
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12
The carbon cost of materials discovery: Can machine learning really accelerate the discovery of new photovoltaics?

von Walker, Matthew ; Butler, Keith T.

Schlagworte: Materials Science; Machine Learning
- View full text via Arxiv
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13
Self-Optimizing Machine Learning Potential Assisted Automated Workflow for Highly Efficient Complex Systems Material Design

von Li, Jiaxiang ; Feng, Junwei ; Luo, Jie ; et al.

Schlagworte: Materials Science; Machine Learning
- View full text via Arxiv
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14
Two-Dimensional Graphene-like BeO Sheet: A Promising Deep-Ultraviolet Nonlinear Optical Materials System with Strong and Highly Tunable Second Harmonic Generation

von Liu, Linlin ; Xie, Congwei ; Tudi, Abudukadi ; et al.

Schlagworte: Condensed Matter - Mesoscale and Nanoscale Physics; Condensed Matter - Materials Science; Physics - Optics
- View full text via Arxiv
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15
Predicting Colloidal Interaction Parameters from Small-Angle X‑ray Scattering Curves Using Artificial Neural Networks and Markov Chain Monte Carlo Sampling

von Wong, Kelvin ; Qi, Runzhang ; Yang, Ye ; et al.

JACS Au. 4(9):3492-3500
- View full text at ACS Publications
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16
Learning Radical Excited States from Sparse Data

von Shen, Jingkun ; Walker, Lucy E. ; Ma, Kevin ; et al.

Schlagworte: Physics - Chemical Physics; Condensed Matter - Materials Science
- View full text via Arxiv
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17
Optimal pre-train/fine-tune strategies for accurate material property predictions

von Devi, Reshma ; Butler, Keith T. ; Gautam, Gopalakrishnan Sai

Schlagworte: Condensed Matter - Materials Science
- View full text via Arxiv
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18
A literature-derived dataset of migration barriers for quantifying ionic transport in battery materials

von Reshma Devi ; Avaneesh Balasubramanian ; Keith T. Butler ; et al.

Scientific Data, Vol 12, Iss 1, Pp 1-11 (2025)

Schlagworte: Science
- View full text via DOI
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19
Leveraging transfer learning for accurate estimation of ionic migration barriers in solids

von Reshma Devi ; Keith T. Butler ; Gopalakrishnan Sai Gautam

npj Computational Materials, Vol 12, Iss 1 (2026)

Schlagworte: Materials of engineering and construction. Mechanics of materials; TA401-492; Computer software; QA76.75-76.765
- View full text via DOI
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20
Model Checking Functional Integration of Human Cognition and Machine Reasoning

von Mercer, Eric ; Butler, Keith ; Bahrami, Ali

2022 IEEE International Systems Conference (SysCon) Systems Conference (SysCon), 2022 IEEE International. :1-8 Apr, 2022
- Zum Volltext in IEEE Xplore
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21
A shift-invariant deep learning framework for automated analysis of XPS spectra

von Butler, Keith T. ; Saddiq, Issa ; Fan, Yuxin ; et al.

In Journal of Electron Spectroscopy and Related Phenomena August 2026 287
- View full text via DOI
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22
Effects of Grain Boundaries and Surfaces on Electronic and Mechanical Properties of Solid Electrolytes

von Xie, Weihang ; Deng, Zeyu ; Liu, Zhengyu ; et al.

Adv. Energy Mater., 2304230 (2024)

Schlagworte: Condensed Matter - Materials Science
- View full text via Arxiv
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23
Crystal Structure Generation with Autoregressive Large Language Modeling

von Antunes, Luis M. ; Butler, Keith T. ; Grau-Crespo, Ricardo

Schlagworte: Condensed Matter - Materials Science
- View full text via Arxiv
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24
Element similarity in high-dimensional materials representations

von Onwuli, Anthony ; Hegde, Ashish V. ; Nguyen, Kevin ; et al.

Schlagworte: Condensed Matter - Materials Science
- View full text via Arxiv
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25
Design of New Ternary Nitrides for Photovoltaic Applications via High-Throughput Calculations

von Xue, Pengyan ; Chu, Dongdong ; Xie, Congwei ; et al.

The Journal of Physical Chemistry C. 126(40):17398-17405
- View full text at ACS Publications
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12 3 4 5 6 7 8 9 10 11 weiter »

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