Results 171 to 180 of about 67,103 (261)

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

Artificial intelligence strategies based on random forests for detecting ischemia-reperfusion injury changes in kidney tissue during intravital imaging. [PDF]

Sci Rep
Pantic I, Paunovic Pantic J, Valjarevic S, Cumic J, Qin P, Corridon PR.   +5 more
europepmc   +1 more source

Light‐Imprinted Chirality in Nanomaterials: From Principles to Applications

Advanced Science, EarlyView.
Light‐induced chirality represents a transformative paradigm for fabricating chiral nanostructures. This review provides a comprehensive framework encompassing light‐based strategies for imprinting and tuning chirality in nanomaterials, which guides researchers in harnessing light to create next‐generation functional materials.
Xinru Jin, Emiliano Cortés, Alexander O. Govorov, Tao Ding   +3 more
wiley   +1 more source

Simulating Public Opinion: Comparing Distributional and Individual-Level Predictions from LLMs and Random Forests. [PDF]

Entropy (Basel)
Miranda F, Balbi PP.
europepmc   +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

Predicting emotional responses in interactive art using Random Forests: a model grounded in enactive aesthetics. [PDF]

Front Psychol
Chen X, Ibrahim Z, Aziz AA.
europepmc   +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

Modeling the Restricted Mean Survival Time Using Pseudo-Value Random Forests. [PDF]

Stat Med
Schenk A, Basten V, Schmid M.
europepmc   +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

Random forests for the analysis of matched case-control studies. [PDF]

BMC Bioinformatics
Schauberger G, Klug SJ, Berger M.
europepmc   +1 more source