Results 191 to 200 of about 127,719 (261)

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

Dual-phase optimized deep learning framework for accurate, efficient, and robust battery SoC estimation. [PDF]

Sci Rep
R S, Mani G.
europepmc   +1 more source

Accelerated Screening of Halide Double Perovskites via Hybrid Density Functional Theory and Machine Learning for Thermoelectric Energy Conversion

Advanced Energy and Sustainability Research, EarlyView.
This study integrates hybrid density functional theory, Boltzmann transport theory, and machine learning to accelerate the discovery of lead‐free halide double perovskites for thermoelectric energy conversion. By screening 102 compounds, the authors identify high‐performing candidates such as Rb2GeI6 and Cs2SnBr6, offering a sustainable pathway toward ...
Souraya Goumri‐Said, Ghouti Abdellaoui, Mohammed Benali Kanoun   +2 more
wiley   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

Systematic hyperparameter analysis of GRU and LSTM across demand pattern types: a demand-characteristic-driven meta-learning framework for rapid optimization. [PDF]

Sci Rep
El-Meehy AO, El-Kharbotly AK, El-Beheiry MM.   +2 more
europepmc   +1 more source

Design for flexibility: An adjustable robust optimization approach with decision‐dependent uncertainty

AIChE Journal, EarlyView.
ABSTRACT Flexibility is a crucial characteristic of industrial systems that face increasing volatilities and is therefore essential to ensure feasible operation under uncertainty. Flexibility is often closely tied to the design of a system, and careful consideration must be taken to understand the trade‐off between design cost and operational ...
Jnana Sai Jagana, Sreekanth Rajagopalan, Satyajith Amaran, Qi Zhang   +3 more
wiley   +1 more source

Unsupervised learning of spatially varying regularization for diffeomorphic image registration. [PDF]

Med Image Anal
Chen J, Wei S, Liu Y, Bian Z, He Y, Carass A, Bai H, Du Y.   +7 more
europepmc   +1 more source

A multiscale Bayesian optimization framework for process and material codesign

AIChE Journal, EarlyView.
Abstract The simultaneous design of processes and enabling materials such as solvents, catalysts, and adsorbents is challenging because molecular‐ and process‐level decisions are strongly interdependent. Sequential approaches often yield suboptimal results since improvements in material properties may not translate into superior process performance. We
Michael Baldea
wiley   +1 more source

Prediction method for rock shear strength parameters based on data-driven and interpretability analysis. [PDF]

Sci Rep
Jin ZJ, Wang C, Qi S, Liu Y, Yu H, He ZW.   +5 more
europepmc   +1 more source

Hybrid modeling for optimizing cell cultivation in mAb production using a small‐scale automated experimental platform

AIChE Journal, EarlyView.
Abstract This work presents the optimization of cell cultivation for monoclonal antibody (mAb) production. We developed a hybrid model describing the effects of multiple process variables on antibody productivity and impurity generation. An automated platform with 12 × 250 mL bioreactors was set up.
Kosuke Nemoto, Yuki Yoshiyama, Mizuki Morisasa, Junshin Iwabuchi, Yusuke Hayashi, Sara Badr, Hirokazu Sugiyama   +6 more
wiley   +1 more source