An explainable machine learning framework for predicting the compressive strength of sustainable metakaolin mortars

Molecular dynamics screening of water desalination through a graphdiyne–Ti3C2F2 Janus-type bilayer membrane: Observed salt rejection and water permeation under accelerated conditions

Nour El Haq El Macouti, Mohamed El Bouanounou, Abdelmajid Assila, E.K. Hlil, Y. Boughaleb, Mouhaydine Tlemçani, et al.

Classical molecular dynamics simulations were used as a preliminary mechanistic screening tool to examine water desalination through an asymmetric graphdiyne–Ti 3 C 2 F 2 Janus-type bilayer membrane. A single 10 ns trajectory was performed at 300 K using a 0.6 M NaCl feed solutio…Read more

Autonomous laboratories for sustainable nanomaterials discovery

Aarti Jathar, Beena Nawghare, Ketankumar A. Ganure

Autonomous nanomaterials discovery is rapidly transforming conventional trial-and-error experimentation into intelligent closed-loop scientific ecosystems that integrate artificial intelligence (AI), robotics-assisted experimentation, autonomous characterization, and cyber–physic…Read more

A review on bearing fault diagnosis methods with emphasis on machine learning and deep learning applications

Prachi Dixit, Pawan Pingle, Adinath Funde, Kedarnath Chaudhary, Vikas Kanake

A numerical investigation of carbon conversion using a random pore model in gasification process for selected carbonaceous feedstocks, kinetics studies, artificial intelligence and machine learning applications

Prasanta Das

Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review

Mohsen Soori, Behrooz Arezoo

Gel mechanics as a design basis for magnetic soft robotic swimmers

R. Pramanik