Results 111 to 120 of about 96,632 (252)

Polychip‐A High‐Throughput Droplet Microfluidics Platform for Interrogating Microbial Interactions

Advanced Science, EarlyView.
Polychip, a fully integrated droplet microfluidics platform, enables high‐throughput, single‐cell resolution screening of polymicrobial interactions. By seamlessly combining six automated microfluidics operations on a single chip, the system accelerates antimicrobial discovery by 11 to 14 times compared to traditional robotic methods.
Jeong Jae Han, Adrian Ryan Guzman, Aifen Zhou, Han Zhang, Rohit Gupte, Haemin Jung, Kaylee Delgado, Sini Skariah, Ali Sultan, Arul Jayaraman, Paul de Figueiredo, Arum Han   +11 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

Influencia de la densidad de plantación y la fertilización nitrogenada en el rendimiento de Morus alba var. tigreada

Pastos y Forrajes
Se evaluó el efecto de la densidad de plantación (12 500, 25 000 y 37 500 plantas/ha) y la fertilización nitrogenada (100, 300 y 500 kg de N/ha/año) en el rendimiento y la composición bromatológica de Morus alba var. tigreada.
Yolai Noda, G. J Martín
doaj  

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

Functional Disorder at the Neural Interface: How Disordered Nanostructures Promote Proper Growth and Differentiation in In Vitro Neural Cultures

Advanced Science, EarlyView.
This work provides a practical guide for neuroengineers to design advanced neural interfaces, embracing and tailoring the concept of functional disorder. By bridging 2D and 3D in vitro models, this work highlights how non‐periodic, spatially heterogeneous, multiscale nanotopography can enable more physiologically relevant platforms for studying neural ...
F. Maita, E. Palmieri, I. Lucarini, L. Montaina, L. Maiolo   +4 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

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Evolutionary Tree in Chemical Space of Natural Products

ABSTRACT Natural products (NPs) are key to biological function and adaptation, with their distribution shaped by complex evolutionary and ecological forces. While it may seem reasonable to assume that closely related species produce chemically similar NPs, this assumption has not been systematically tested at a broad taxonomic scale ...
Yang, Bo, Xiang, Chijian, Li, Tongtong, Liu, Boyuan, Sinitskiy, Anton V., Li, Jianing   +5 more
openaire   +2 more sources

Discovery and Engineering of a Rat Endogenous Retrovirus Reverse Transcriptase for Efficient Prime Editing

Advanced Science, EarlyView.
We screened 558 reverse transcriptases and engineered an optimized rat endogenous retrovirus‐derived variant, enRERV‐RT, via structure‐guided engineering and deep mutational scanning. This enhanced prime editor, based on the engineered RT, outperforms conventional M‐MLV‐RT systems across plant and animal cells, particularly at hard‐to‐edit loci ...
Linsha Ma, Pengcheng Yao, Shengqi Wu, Yuanyuan Shi, Lang Qin, Baitao Li, Jiayi Zhu, Minhua Huang, Yichong Zhu, Yuwen Song, Jinhuan Pang, Ziping Guo, Guochuan Wu, Chen Wang, Kewei Xu, Ruihua Huang, Quan Kuang, Liang Qu, Changtian Pan, Xianrong Xie, Qinlong Zhu, Jiaying Huang, Qiupeng Lin   +22 more
wiley   +1 more source