Surfactant Induced Synthesis of LiAlH4 and NaAlH4 Nanoparticles for Hydrogen Storage

LiAlH4 and NaAlH4 are considered to be promising hydrogen storage materials due to their high hydrogen density. However, their practical use is hampered by the lack of hydrogen reversibility along with poor kinetics. Nanosizing is an effective strategy to enable hydrogen reversibility under practical conditions. However, this has remained elusive as the synthesis of alanate nanoparticles has not been explored. Herein, a simple solvent evaporation method is demonstrated to assemble alanate nanoparticles with the use of surfactants as a stabilizer. More importantly, the roles of the surfactants in enabling control over particle size and morphology was determined. Surfactants with long linear carbon chains and matching the hard character of alanates are more prone to lead to the formation of small particles of ~10 nm due to steric hindrance. This can result in significant shifts in the temperature for hydrogen release.

Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

Machine learning (ML) approximations to density functional theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present, they are not applicable to varying electronic states, and in particular, they are not well suited for molecular systems in which the local electronic structure is sensitive to the medium to long-range electronic environment. With this issue as the focal point, we present a new machine learning approach called "BpopNN" for obtaining efficient approximations to DFT PESs. Conceptually, the methodology is based on approaching the true DFT energy as a function of electron populations on atoms; in practice, this is realized with available density functionals and constrained DFT (CDFT). The new approach creates approximations to this function with neural networks. These approximations thereby incorporate electronic information naturally into a ML approach, and optimizing the model energy with respect to populations allows the electronic terms to self-consistently adapt to the environment, as in DFT. We confirm the effectiveness of this approach with a variety of calculations on Li_nH_n clusters.

Nanostructured Metal Hydrides for Hydrogen Storage

Knowledge and foundational understanding of phenomena associated with the behavior of materials at the nanoscale is one of the key scientific challenges toward a sustainable energy future. Size reduction from bulk to the nanoscale leads to a variety of exciting and anomalous phenomena due to enhanced surface-to-volume ratio, reduced transport length, and tunable nanointerfaces. Nanostructured metal hydrides are an important class of materials with significant potential for energy storage applications. Hydrogen storage in nanoscale metal hydrides has been recognized as a potentially transformative technology, and the field is now growing steadily due to the ability to tune the material properties more independently and drastically compared to those of their bulk counterparts. The numerous advantages of nanostructured metal hydrides compared to bulk include improved reversibility, altered heats of hydrogen absorption/desorption, nanointerfacial reaction pathways with faster rates, and new surface states capable of activating chemical bonds. This review aims to summarize the progress to date in the area of nanostructured metal hydrides and intends to understand and explain the underpinnings of the innovative concepts and strategies developed over the past decade to tune the thermodynamics and kinetics of hydrogen storage reactions. These recent achievements have the potential to propel further the prospects of tuning the hydride properties at nanoscale, with several promising directions and strategies that could lead to the next generation of solid-state materials for hydrogen storage applications.

Multiple Li+- and Mg2+-decorated PAHs: potential systems for reversible hydrogen storage

Computational exploration of hydrogen storage efficiency of multiple metal ion (Li⁺/Mg²⁺)-decorated PAHs.

Reversible hydrogen storage by NaAlH4 confined within a titanium-functionalized MOF-74(Mg) nanoreactor

We demonstrate that NaAlH(4) confined within the nanopores of a titanium-functionalized metal-organic framework (MOF) template MOF-74(Mg) can reversibly store hydrogen with minimal loss of capacity. Hydride-infiltrated samples were synthesized by melt infiltration, achieving loadings up to 21 wt %. MOF-74(Mg) possesses one-dimensional, 12 Å channels lined with Mg atoms having open coordination sites, which can serve as sites for Ti catalyst stabilization. MOF-74(Mg) is stable under repeated hydrogen desorption and hydride regeneration cycles, allowing it to serve as a "nanoreactor". Confining NaAlH(4) within these pores alters the decomposition pathway by eliminating the stable intermediate Na(3)AlH(6) phase observed during bulk decomposition and proceeding directly to NaH, Al, and H(2), in agreement with theory. The onset of hydrogen desorption for both Ti-doped and undoped nano-NaAlH(4)@MOF-74(Mg) is ∼50 °C, nearly 100 °C lower than bulk NaAlH(4). However, the presence of titanium is not necessary for this increase in desorption kinetics but enables rehydriding to be almost fully reversible. Isothermal kinetic studies indicate that the activation energy for H(2) desorption is reduced from 79.5 kJ mol(-1) in bulk Ti-doped NaAlH(4) to 57.4 kJ mol(-1) for nanoconfined NaAlH(4). The structural properties of nano-NaAlH(4)@MOF-74(Mg) were probed using (23)Na and (27)Al solid-state MAS NMR, which indicates that the hydride is not decomposed during infiltration and that Al is present as tetrahedral AlH(4)(-) anions prior to desorption and as Al metal after desorption. Because of the highly ordered MOF structure and monodisperse pore dimensions, our results allow key template features to be identified to ensure reversible, low-temperature hydrogen storage.