Results 171 to 180 of about 4,650,602 (260)

Adult Sex Ratio as a Demographic Feedback Linking Mating Systems, Parental Care, and Evolution

Advanced Science, EarlyView.
Breeding systems are some of the most diverse social behavior, and our team is investigation the evolutionary causes of this diversity. This review summarises our research carried out at the University of Bath. We argue that demographic components of wild populations, especially the adult sex ratio, plays a key role driving breeding system variation ...
Tamás Székely, Oscar G. Miranda
wiley   +1 more source

Underground Signals: The Ecological Power of Root Volatiles

Advanced Science, EarlyView.
Root volatiles mediate rhizosphere chemical communication, shaping interactions among plants, microbes, herbivores, and natural enemies. Their production, transport, and perception underpin ecological adaptation, multitrophic interactions, and plant resilience, offering opportunities for sustainable crop protection, resilient agroecosystems, and ...
Xueyao Cao, Nanli Song, François Verheggen, Meritxell Pérez‐Hedo, Andrea Clavijo McCormick, Antonino Cusumano, Arthur de Fouchier, Bing Wang, Chen‐Zhu Wang, Emmanuelle Jacquin‐Joly, Gary W. Felton, Geoff M. Gurr, Hao Guo, Jiancai Li, Jin Zhang, Li Chen, Manqun Wang, Michele Ricupero, Peng Han, Peng He, Qi Yan, Qingbo Tang, Qingsong Liu, Shiheng An, Xiangbo Kong, Xiaoling Sun, Xueming Ren, Yuanyuan Song, Yang Liu, Yanhui Guo, Yunhe Li, Xiao Sun   +31 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

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

Deciphering Short‐Range Order in 2D Transition Metal Dichalcogenides: From Origin to Multi‐Scale Property Modulation

Advanced Science, EarlyView.
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu, Linggang Zhu, Jian Zhou, Zhimei Sun   +3 more
wiley   +1 more source

Regional dynamics of forest canopy change and underlying causal processes in the contiguous U.S.

The history of forest change processes is written into forest age and distribution and affects earth systems at many scales. No one data set has been able to capture the full forest disturbance and land use record through time, so in this study, we ...
Schleeweis, Karen, Huang, Chengquan, Moisen, Gretchen, Goward, Samuel N., Thomas, Nancy E., Masek, Jeffrey G., Kennedy, Robert E.   +6 more
core   +1 more source

Broadening Hard‐Magnet Discovery Beyond Symmetry Constraints via Unified Effective Anisotropy

Advanced Science, EarlyView.
A unified effective‐anisotropy descriptor (Keff) extends hard‐magnet screening across all seven crystal systems, beyond the uniaxial restriction of conventional searches. Machine‐learning screening of 9320 known ferromagnets and diffusion‐model generation together yield 38 rare‐earth‐free or ‐lean candidates with DFT‐validated magnetic hardness (κ > 1),
Hojae Kim, Hyeondeok Shin, Kyungju Nam, Seunghyo Noh, Donghwi Kim, Yousung Jung   +5 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