Results 211 to 220 of about 72,581 (258)

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Time-resolved XPCS analysis across broad time-scales using multi-tau two-time correlations. [PDF]

J Synchrotron Radiat
Brugnara F, Cammarata M, Chushkin Y, Festi I, Granata M, Hofman D, Leonardi M, Marzi D, Nabari D, Trapananti A, Ziglio S, Zontone F, Zanatta M, Baldi G.   +13 more
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Algorithm-hardware co-design of neuromorphic networks with dual memory pathways. [PDF]

Nat Mach Intell
Sun P, Su Z, Achterberg J, Indiveri G, Goodman DFM, Akarca D.   +5 more
europepmc   +1 more source

Assessment of degenerative states of articular cartilage via sparse laser-based mid-infrared attenuated total reflectance spectroscopy. [PDF]

Osteoarthr Cartil Open
Krebs P, Blazhko U, Nägele M, Tafintseva V, Zimmermann B, Virtanen V, Nippolainen E, Shaikh R, Afara IO, Töyräs J, Saarakkala S, Kohler A, Mizaikoff B.   +12 more
europepmc   +1 more source

Novel sparse decomposition with adaptive evolutionary atoms for nonstationary signal extraction. [PDF]

Sci Rep
Ge S, Gao Z, Li J, Zhang X, Huang W, Feng K, Zhang C, Sun J.   +7 more
europepmc   +1 more source

Deep Learning Super-Resolution Spectrometer Based on Fiber Random Laser With Ultrahigh Spectral Purity. [PDF]

Nanophotonics
Zhao J, Gao X, Lu Z, Zhang F, Shi X, Zhai T.   +5 more
europepmc   +1 more source

Variable rate neural compression for sparse detector data. [PDF]

Patterns (N Y)
Huang Y, Go Y, Huang J, Li S, Luo X, Marshall T, Osborn JD, Pinkenburg C, Ren Y, Shulga E, Yoo S, Yoon BJ.   +11 more
europepmc   +1 more source