Results 81 to 90 of about 25,341,143 (317)

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

Interpretable AI integrated with near-infrared spectroscopy for precise assessment of key factors in flue-cured tobacco leaf quality formation: A case study of moisture

Industrial Crops and Products
Moisture content (MC) during tobacco curing is critical to final sensory quality, yet conventional methods cannot satisfy the need for rapid, non-destructive monitoring.
Yapeng Kang, Jun Jiang, Lingfeng Meng, Yuhang Zhao, Yunfei Ma, Shengjiang Wu, Yingpeng Dai, Kesu Wei   +7 more
doaj   +1 more source

Lane change decision prediction: an efficient BO-XGB modelling approach with SHAP analysis

Transportmetrica A: Transport Science
The lane-change decision (LCD) is a critical aspect of driving behaviour. This study proposes an LCD model based on a Bayesian optimization (BO) framework and extreme gradient boosting (XGBoost) to predict whether a vehicle should change lanes. First, an LCD point extraction method is proposed to refine the exact LCD points with a highD dataset to ...
Haobo Sun, Qixiu Cheng, Pu Wang, Yongqi Huang, Zhiyuan Liu   +4 more
openaire   +3 more sources

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

Comparative analysis of interpretable artificial intelligence methods

Journal of Computer Sciences Institute
The aim of this article is to analyze and compare methods for explaining the results of artificial intelligence methods. Three methods were analyzed: Grad-CAM, SHAP, and LIME, evaluated in terms of their effectiveness on different data types.
Aleksandra Kuszewska, Małgorzata Charytanowicz   +1 more
doaj   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

Advanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil, Isel Grau, Ricardo Grau‐Crespo, Said Hamad, Juan A. Anta   +4 more
wiley   +1 more source

Development and implementation of Shuttle/IUS proximity operations flight design software [PDF]

The High Fidelity Relative Motion Program (HFRMP), a trajectory/attitude numerical integration program, was developed and implemented on the MPAD HP-9825A desk top computer systems. A solar and a lunar ephemeris is included in the HFRMP along with models
Wilson, S. W.
core   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

A Day-Ahead Wind Power Dynamic Explainable Prediction Method Based on SHAP Analysis and Mixture of Experts

Energies
Traditional single-prediction models often exhibit limitations in meeting wind power prediction requirements in complex operational scenarios. Furthermore, the inherent “black-box” nature of deep learning models leads to limited interpretability of ...
Hao Zhang, Guoyuan Qin, Xiangyan Chen, Linhai Lu, Ziliang Zhang, Jiajiong Song   +5 more
doaj   +1 more source

The Role of Artificial Intelligence in Medication Management for Older Adults: A Systematic Review

AGING MEDICINE, EarlyView.
Artificial intelligence enhances medication management for older adults by improving adherence, personalizing treatment, and predicting risks. Despite benefits, challenges remain in usability, trust, ethics, and system integration. Successful adoption requires user‐centered design, ethical safeguards, and seamless healthcare integration to ensure safe,
Dipak Chandra Das, Moustaq Karim Khan Rony, Shovit Dutta, MD. Sami Al Zubair Zujbe, Tapan Bhattacharjee, Niloy Debnath, Shabbir Abdullah Maruf, Chowdhury Galib Mortuza, Farhana Rahman, Akash Das   +9 more
wiley   +1 more source