Results 171 to 180 of about 1,224 (273)

Design of a broadband noise reduction barrier utilizing acoustic metamaterial with application to a substation. [PDF]

iScience
Xu S, Li L, Wang Q, Meng W, Du X, Xiao X, Wen Z.   +6 more
europepmc   +1 more source

Development and experimental validation of a predictive resilient framework for cyber‐physical systems

AIChE Journal, EarlyView.
Abstract Cyber‐physical process systems integrate process dynamics, control, sensing, actuation, and communication, making them vulnerable to attacks that falsify data, alter control actions, or disrupt networks and drive operations toward unsafe states.
Luyang Liu, Ritu Ranjan, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan   +5 more
wiley   +1 more source

Artificial intelligence in microbiology: implications for metagenomics, diagnostics, and AMR surveillance. [PDF]

Biomed Eng Online
Khangarot R, Kumari V, Mishra R, Singh A.   +3 more
europepmc   +1 more source

Enhanced biogas production via dual‐layer model predictive control for thermophilic anaerobic digesters

AIChE Journal, EarlyView.
Abstract Thermophilic anaerobic digestion (AD) is an attractive process due to its higher biogas yield compared to mesophilic digestion. To mitigate its higher heating demand and potential process instability, a dual‐layer control architecture comprising a decision‐making layer and an adaptive model predictive control (MPC) system is proposed.
Ali Moradvandi, Mohammad Amin Ghanavati, Merle de Kreuk, Ralph E. F. Lindeboom   +3 more
wiley   +1 more source

A transformer-XGBoost based model to fault diagnosis for CPR1000. [PDF]

Sci Rep
Peng Z, Lei J, Ni Z, Wasaye MA, Jiang Y, Cao Y, Yu T.   +6 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Technoeconomic Analysis of Microwave-Assisted Dry Reforming Integrated with Chemical Looping for Production of Methanol. [PDF]

Ind Eng Chem Res
Almaraz O, Riley J, Palanki S.
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

From Atoms to Reactors: A Critical Review of a Decade of Machine Learning in Heterogeneous Catalysis (2017–2026)

Angewandte Chemie, EarlyView.
Machine learning has digitalized heterogeneous catalysis from the top of the length scale downward: prediction at the atom and the material is now mature, yet the reactor and the process remain the open frontier. This critical review traces a decade of progress across the full catalytic value chain and asks where the next decade of impact must be won ...
Rafael Larraz, Avelino Corma
wiley   +2 more sources

Back to the future - from nuclear energy to AI. [PDF]

AI Perspect Adv
Dinov ID.
europepmc   +1 more source