Results 171 to 180 of about 65,604 (247)

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

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Interpretable Machine Learning of Nanoparticle Stability through Topological Layer Embeddings. [PDF]

J Phys Chem A
Hawthorne F, Seixas L, Almeida JM, Woellner CF, Tromer RM.   +4 more
europepmc   +1 more source

Ultrasound‐Responsive Piezoelectric Fibrous Membrane Promotes Neurological Recovery After TBI by Modulating Microglial Polarization via Restoring Mitochondrial Dynamic Homeostasis

Advanced Science, EarlyView.
We demonstrate a novel therapy for traumatic brain injury TBI using a LIPUS‐responsive Piezoelectric fibrous membrane. It targets microglial mitochondria via in situ electrical signals, restoring homeostasis and reducing oxidative stress to promote an anti‐inflammatory M2 phenotype.
Wei Li, Runzhe Huang, Qingyuan Wu, Pengbo Zhou, Dangli Ren, Jingjing Wang, Hanjie Niu, Zemeng Li, Hongtao Sun, Huiyu Liu   +9 more
wiley   +1 more source

Organoid Brain‐Machine‐Interface Devices for Central Nervous System Repair

Advanced Science, EarlyView.
We envision organoid brain‐machine‐interface (Organoid‐BMI) devices as new biohybrid bidirectional communication pathways to connect the human CNS and the external world for personalized CNS repair and regeneration. ABSTRACT Central nervous system (CNS) repair and regeneration suffer from tremendous clinical challenges due to current limitations in ...
Yantao Xing, Yang Yang, Zichen Hong, Chunhui Tian, Huiyu Chu, Susanne Clara Prokop, Hongwei Cai, Mingxia Gu, Jason Tchieu, Ken Mackie, Feng Guo   +10 more
wiley   +1 more source

Leveraging Large Language Models for Understanding Fundamental Principles of Catalysis. [PDF]

J Phys Chem C Nanomater Interfaces
Michtavy SS, Perera SMHD, Porosoff MD.
europepmc   +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‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Mechanistically Interpretable Artificial Intelligence for Designing Oxygen Electrocatalysts. [PDF]

Adv Mater
Hu X, Zhou Y, Li H, Luo Z, Shi N, Ding Y, Wang W, Zhang W, Kim D, Kim C, Ahn Y, Govindarajan N, Zou M, Liu Z, Song Y, Liu M.   +15 more
europepmc   +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