Turab Lookman

Nanomaterials Research (United States) — United States

Materials Science · Physical Sciences

64h-index16.8kcitations579works6.32yr avg
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Research Topics

Machine Learning in Materials Science(87), Shape Memory Alloy Transformations(78), Ferroelectric and Piezoelectric Materials(75), Theoretical and Computational Physics(72), Multiferroics and related materials(51)

Publications579 total

Design of shape memory alloys with enhanced thermal management properties via adaptively constrained multi-objective optimization
Acta Materialia·2026· 1 cited
Materials Informatics: Emergence To Autonomous Discovery In The Age Of AI
arXiv (Cornell University)·2026Open Access
Materials Informatics: Emergence To Autonomous Discovery In The Age Of AI
arXiv (Cornell University)·2026Open Access
Spatiotemporal evolution of defects in an additively manufactured alloy monitored through in-situ X-ray computed tomography
Acta Materialia·2025
Metavalent Bonding-Induced Phonon Hardening and Giant Anharmonicity in BeO
arXiv (Cornell University)·2025Open Access
Nested crystal graph neural networks for modeling chemically complex materials
Acta Materialia·2025Open Access
Unlocking the future of materials science: key insights from the DCTMD workshop
Journal of Materials Informatics·2025Open Access
Theory guided data-driven design of superelasticity in TiNi alloys over wide temperature window
Acta Materialia·2025
Mapping microstructure to mechanical property by disentangling strengthening mechanism with deep learning
Acta Materialia·2025
Spatiotemporal microstructure evolution during martensitic transformation in titanium alloys using deep learning
Acta Materialia·2025
Same-group element replacement enhances superconductivity in clathrate-like YH4
arXiv (Cornell University)·2025Open Access
Same-group element replacement enhances superconductivity in clathrate-like YH4
The Journal of Chemical Physics·2025
Regulation of athermal ω formation by one-dimensional chemical ordering in Zr-10% Nb alloys
Physical Review Materials·2025
Detecting deformation mechanisms of metals from acoustic emission signals through knowledge-driven unsupervised learning
Nature Communications·2025· 5 citedOpen Access
Closed-loop inverse design of high entropy alloys using symbolic regression-oriented optimization
Materials Today·2025· 5 cited
Materials design with target-oriented Bayesian optimization
npj Computational Materials·2025· 14 citedOpen Access
Generalizable descriptors for automatic titanium alloys design by learning from texts via large language model
Acta Materialia·2025· 7 cited
Enhanced hydrogen embrittlement resistance of FeCoNiCrMn multi-principal element alloys via local chemical ordering and grain boundary segregation
Acta Materialia·2025· 7 cited
Phase transition behavior in ferroelectric BaTi0.8Zr0.2O3: Evidence of polar cluster reorientation above Curie temperature
Journal of Applied Physics·2025· 2 citedOpen Access
Design of superalloys with multiple properties via multi-task learning
Acta Materialia·2025· 3 cited
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Frequent Co-authors

Dezhen Xue(13), Prasanna V. Balachandran(13), Avadh Saxena(10), Xiangdong Ding(8), Ghanshyam Pilania(6), Ruihao Yuan(5), J. E. Gubernatis(5), Deqing Xue(4), A. R. Bishop(4), K. Ø. Rasmussen(4), Yang Bai(3), Yanjing Su(3), John Hogden(3), James Theiler(3), Yumei Zhou(3), Subodh R. Shenoy(3), Xiaobing Ren(3), R. C. Albers(3), Cheng Wen(2), Changxin Wang(2)