Research [ASAP] Historical Data Mining Deep Dive into Machine Learning-Aided 2D Materials Research in Electrochemical Applications LikeLiked Date: June 23, 2025 Less than 1 MinRead Views: 14 ACS Materials Au DOI: 10.1021/acsmaterialsau.5c00030 Source: http://dx.doi.org/10.1021/acsmaterialsau.5c00030 Tags:Materials Industry FacebookTwitterLinkedinWhatsAppTelegramEmail ALT-Lab-Ad-1ALT-Lab-Ad-2ALT-Lab-Ad-3ALT-Lab-Ad-4ALT-Lab-Ad-5ALT-Lab-Ad-6ALT-Lab-Ad-7ALT-Lab-Ad-8ALT-Lab-Ad-9ALT-Lab-Ad-10ALT-Lab-Ad-11ALT-Lab-Ad-12ALT-Lab-Ad-13 Recent Articles Solvent selection enables sustainable and affordable lignin biocomposite for cement-free construction Research February 25, 2026 Research February 25, 2026 Current-carrying-coil magnetic field influences methane production in anaerobic digestion of water hyacinth by modulating reactive oxygen species levels Research February 25, 2026 Breaking new ground in sustainability (SD): a novel integrated framework for eco/green-innovation (EI) and green supply chain management (GSCM) implementation in emerging economies –... Research February 25, 2026 [ASAP] Hollow Mesoporous Manganese Dioxide Nanoprobes for Hepatocellular Carcinoma Diagnosis and Therapy Research February 25, 2026 Prioritizing protection Food & Agriculture February 25, 2026 Activated carbon–embedded free-standing glucomannan membrane for efficient dye removal Research February 25, 2026 Assessing environmental and policy dimensions of LEED adoption in ready-made garments of Bangladesh: Drivers, barriers, and strategies for sustainable industrial green transformation Waste Management February 24, 2026 Gen AI could transform packaging pricing: McKinsey Packaging February 24, 2026 Webb Maps Uranus’ Upper Atmosphere Research February 24, 2026 Load more
