Results 111 to 120 of about 22,088 (262)

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 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

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Engineering Microbial Particles for Next‐Generation Biomedical Platforms

Advanced Science, EarlyView.
Microbe‐derived particles (MDPs), which include extracellular vesicles, outer membrane vesicles, inclusion bodies, polysaccharide particles, and virus‐like particles, represent a rapidly expanding category of bioinspired nanomaterials. With their natural origin, intrinsic biocompatibility, and highly programmable functionality, MDPs serve as a ...
Yuting Li, Yunjie Lu, Ziyan Huang, Jianjiang Chen, Yanbin Liu, Lei Qin, Chao Wang, Yumin Wu   +7 more
wiley   +1 more source

Green Hydrogen as a Decarbonization Pathway for Steel Industry in Pakistan

Engineering Proceedings
The global steel industry emits 1.92 tons of CO2 per ton of output and faces urgent pressure to decarbonize. In Pakistan, the sector accounts for 0.29 tons of CO2 per ton of output, with limited mitigation frameworks in place.
Arfa Ijaz, Saleha Qureshi, Ubaid Ur Rehman Zia, Sarim Zia, Saad Ali Ahmed Malik, Muhammad Zulfiqar   +5 more
doaj   +1 more source

Reconfigurable Inflatables Through Controlled Surface Crumpling

Advanced Science, EarlyView.
ABSTRACT Inflatable structures offer remarkable versatility due to their compact storage and rapid deployment, making them ideal for lightweight, quickly assembled, and deployable applications. These structures are typically made from membranes that are nearly inextensible yet highly flexible.
Yi Yang, Hye Jun Youn, Leon Kamp, Renate Sachse, Wenjie Li, Jose Vidal, Jin Feng, Martin Bechthold, Katia Bertoldi   +8 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Ramping-Up Electro-Fuel Production

Energies
Future transport systems will rely on new electrified drives utilizing batteries and hydrogen-powered fuel cells or combustion engines with sustainable fuels. These systems must complement each other and should not be viewed as competing. Properties such
Ralf Peters, Maximilian Decker, Janos Lucian Breuer, Remzi Can Samsun, Detlef Stolten   +4 more
doaj   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Strongly coupled sectors in inflation: gapless theories and unparticles

Journal of High Energy Physics
A bstract We compute correlation functions of the primordial density perturbations when they couple to a gapless, strongly coupled sector of spectator fields — “unparticles” — during inflation.
Pimentel, Guilherme, Yang, Chen
openaire   +2 more sources