Advancing fundamental understanding and application of hydrogen storage materials through experiments and modeling. Follows, RTs and mentions ≠ endorsements.
A new preprint from HyMARC researchers
@SandiaLabs in collaboration with @UU_University @UniofNottingham@UPECactus highlights a data-driven approach to identify Pareto optimal high entropy hydrides. Learn more⬇️
https://t.co/3FiQLRfq0J
Hydrogen could be used to power everything from vehicles to the grid, if it’s stored properly. New research explores how to get the storage options just right for different applications. Learn more ⤵️ https://t.co/Rf3YYo1nNG
Loving this new @NatureChemistry Perspective on hydrogen storage/transport materials from some of the @HyMARC_Labs folks. Hope everyone working in this area gives it a read to gain some important insights.
https://t.co/RVvViStDTF
If you're interested in data-driven materials discovery, graph neural networks, and/or water-splitting, check out a pre-print (https://t.co/GzIqnxBNy5) from the HydroGEN consortium with contributions from @SandiaLabs @NREL and @Livermore_Lab !
An exciting new post doc opportunity has just been posted within @Sandia's Energy Nanomaterials Department! Applications with a strong computational skill set and interest in ML-based materials discovery are encouraged to apply!
https://t.co/kYhTZ7NONB
Congratulations to YongJun, Vitalie and team on their recent publication in @acsnano! Using N-doped carbon hosts can turn nanoconfined LiAlH4 into a reversible hydrogen storage material! Another @HyMARC_Labs collaboration. https://t.co/w5AE7ctcMZ
Our @SandiaLabs @UU_University @UniofNottingham collaboration's paper on machine learning for discovery and synthesis of high entropy alloy hydrides is out in @ChemMater! Check it out for a mix of ML, DFT, and experiments on new hydrogen storage compounds https://t.co/b6muCocYuR
Our Sandia/Uppsala/Nottingham collaboration shows how to use ML techniques to identify and synthesize high entropy alloys hydrides with desired thermodynamic stability! Check out the preprint here: https://t.co/ON78WFdYzh
Checkout a new HyMARC preprint: adsorption modeling probes optimal deliverable capacity materials that exploit nonporous to porous transitions without volume change https://t.co/rXoVMcwCl4
Out in @J_A_C_S: Chemical reduction of iron-pyrazolate MOFs yields high selectivity for O2 at RT or even 200 °C. These MOFs have coordinatively saturated iron centers, so adsorption occurs through outer-sphere electron transfer! @ReimerLab@UCB_Chemistry https://t.co/V7UgtphDuv
Vitalie and coworkers demonstrate that subtle changes in isoreticular MOF structure affect catalytic activity now published in Chemical Science https://t.co/SRTlwpgADZ