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1
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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2
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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3
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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4
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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5
Discovery and recovery of crystalline materials with property-conditioned transformers

von Bone, Cyprien ; Walker, Matthew ; Leng, Kuangdai ; et al.

Schlagworte: Materials Science; Disordered Systems and Neural Networks
- View full text via Arxiv
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6
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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7
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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8
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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9
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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10
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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11
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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12
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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13
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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14
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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15
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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16
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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17
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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18
2026 roadmap toward sustainable thermoelectrics

von Bos, Jan Willem G. ; Mohanty, Trupti ; Sparks, Taylor D. ; et al.

Schlagworte: sustainable; sustainable materials; thermoelectric materials; thermoelectrics
- View full text via BASE
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19
Self-optimizing machine learning potential assisted automated workflow for highly efficient complex systems material design

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

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
The carbon cost of materials discovery: Can machine learning really accelerate the discovery of new photovoltaics?

von Walker, Matthew ; Butler, Keith T. ; Engineering and Physical Sciences Research Council

Materials Horizons ; volume 13, issue 4, page 1993-2004 ; ISSN 2051-6347 2051-6355
- View full text via BASE
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22
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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23
Band alignments of complex heterojunctions from first principles: The case of the α-Fe 2 O 3 /BaTiO 3 interface

von Ontaneda, Jorge ; Bustamante, Joana ; Pal, Subhajit ; et al.

Journal of Physics: Materials ; ISSN 2515-7639
- View full text via BASE
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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
Accelerating molecular dynamics by going with the flow

von Ismail, Ahmed Y. ; Martin, Bradley A. A. ; Butler, Keith T.

Nature Machine Intelligence. 7(10):1598-1599
- Volltextverfügbarkeit prüfen (via ReDI)
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