Results 251 to 260 of about 1,858,266 (298)

Atomic‐Scale Mechanisms of Anisotropic Thermal Decomposition in GeSn Alloys With Stepwise Pinning

Advanced Electronic Materials, EarlyView.
Combining in situ TEM with DFT calculations, this work elucidates atomic‐scale anisotropic thermal decomposition in GeSn films, identifying laminar receding in defect‐free regions and stepwise pinning at stacking faults. Driven by crystallographic anisotropy and defect‐mediated energetic penalties, these findings establish a physical framework for ...
YiXin Wang, Qi Liu, XiYan Chang, Chi Xu, Tao Wang, XinZheng Li, ChunLai Xue   +6 more
wiley   +1 more source

Machine learning prediction and hybrid GRA-AHP optimization of AWJM parameters of ultrasonic assisted stir cast Al6061-B[Formula: see text]C-ZrO[Formula: see text] composites. [PDF]

Sci Rep
K A, Shaik AS, Tota RK, Chavda NK, Bodduru K, Alqahtani SS, Kassa MK.   +6 more
europepmc   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Modeling and Performance Analysis of a Liquid Desiccant Cooling and Dehumidification System Using ITSO-TCN-BiGRU-SA. [PDF]

Sensors (Basel)
Ou X, Wang X, Wang Z.
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Optimizing XGBoost via mSMA_plus: A Novel Meta-Heuristic Approach for High-Precision Multiclass Dry Bean Classification. [PDF]

Biomimetics (Basel)
Subaşi N.
europepmc   +1 more source

State-Driven Adaptive Deep-Unfolded PGA Algorithm for Hybrid Beamforming in MIMO-JCAS Systems. [PDF]

Sensors (Basel)
Liu F, Wang Z, Gao Y, Yao Z.
europepmc   +1 more source

Proximal policy optimization integrated with Bayesian optimization for stand structure optimization in <i>Pinus yunnanensis</i> secondary forests. [PDF]

Front Plant Sci
Wang J, Lv C, Yin J, Chen Y, Lv S, Wu B.
europepmc   +1 more source

Identifying predictors of student depression through validated machine learning pipelines. [PDF]

Front Med (Lausanne)
Washton J, Owens T, Sierra A, Toma M.
europepmc   +1 more source