Results 131 to 140 of about 159,034 (226)

Interpretable machine learning models for stroke risk prediction in patients with newly diagnosed atrial fibrillation. [PDF]

NPJ Digit Med
Lin JC, Chang CM, Pan HY, Ho YL, Tu YK, Lai CL.   +5 more
europepmc   +1 more source

Superionic Amorphous Li2ZrCl6 and Li2HfCl6

Advanced Materials, EarlyView.
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley   +1 more source

Insulin Resistance Surrogates and Cognitive Impairment in Parkinson's Disease: A Cross-Sectional Study with Interpretable Machine Learning. [PDF]

Biomedicines
Liang H, Jia Y, Zhang H, Wang D, Yu H, Yan Y, Li J, Chen L, Xue Z.   +8 more
europepmc   +1 more source

Data‐Driven Discovery of Quaternary Ammonium Interlayers for Efficient and Thermally Stable Perovskite Solar Cells

Advanced Materials, EarlyView.
An active learning framework, grounded in independently generated in‐house experimental data, enables reliable discovery of high‐performance interfacial materials for perovskite solar cells. Iterative model refinement autonomously converges toward structurally robust quaternary ammonium architectures, establishing a new design principle for interfacial
Jongbeom Kim, Yang Jeong Park, Chaehoon Jeon, Nahye Shin, Jaewang Park, Seungun Lee, Jino Im, Sungroh Yoon, Sang Il Seok   +8 more
wiley   +1 more source

New‐Era Polymer Thermoelectrics: Material Innovations, Doping Frontiers, Decoupling Strategies, and Unconventional Applications

Advanced Materials, EarlyView.
The field of polymer thermoelectrics is entering a new era, featuring breakthroughs in addressing the conventional performance disparity between p‐type and n‐type polymers, pioneering doping frontiers, and sophisticated decoupling strategies. This review explores innovations in molecular design and superior stabilities, bridging the gap from ...
Suhao Wang
wiley   +1 more source

Interpretable machine learning rationalizes carbonic anhydrase inhibition via conformal and counterfactual prediction. [PDF]

Sci Rep
Ghamsary MS, Rayka M, Naghavi SS.
europepmc   +1 more source

Turning Unpredictable Biomolecule Adsorption to Controlled Corona Formation: Focus on Carbon Nanomaterials

Advanced Materials, EarlyView.
Controlling the protein corona formation onto carbon nanomaterials (CNMs) enhances their functionalities as platforms for cancer theranostics. Here, we reviewed the effects of the intrinsic and acquired properties of CNMs on protein corona formation, the consequent biological and toxicological outcomes, and the strategies to reshape corona formation ...
Yajuan Zou, Yalei Hu, Jie Yu, Naoki Komatsu, Yuta Nishina, Alberto Bianco   +5 more
wiley   +1 more source

Interpretable machine learning for predicting 30-day mortality following intracranial hemorrhage surgery. [PDF]

Front Neurol
Wang Z, Chen W, Shi Y.
europepmc   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source