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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Beyond real: alternative unitary cluster Jastrow models for molecular electronic structure calculations on near-term quantum computers

Near-term quantum devices require wavefunction ansätze that are expressive while also of shallow circuit depth in order to both accurately and efficiently simulate molecular electronic structure. While the unitary coupled cluster ansatz (e.g., UCCSD) has become a standard, the high gate count associated with the implementation of this limits its feasibility on noisy intermediate-scale quantum (NISQ) hardware. k -Fold unitary cluster Jastrow (uCJ) ansätze mitigate this challenge by providing O( kN 2 ) circuit scaling and favorable linear depth circuit implementation. Previous work has focused on the real orbitalrotation (Re-uCJ) variant of uCJ, which allows an exact (Trotter-free) implementation. Here we extend and generalize the k -fold uCJ framework by introducing two new variants, Im-uCJ and g-uCJ, which incorporate imaginary and fully complex orbital rotation operators, respectively. Similar to Re-uCJ, both of the new variants achieve quadratic gate-count scaling. Our results focus on the simplest k = 1 model, and show that the uCJ models frequently maintain energy errors within chemical accuracy (∼1 kcal mol −1 ). Both g-uCJ and Im-uCJ are more expressive in terms of capturing electron correlation and are also more accurate than the earlier Re-uCJ ansatz. We further show that Im-uCJ and g-uCJ circuits can also be implemented exactly, without any Trotter decomposition. Numerical tests using k = 1 on H 2 , H 3 + , Be 2 , C 2 H 4 , C 2 H 6 and C 6 H 6 in various basis sets confirm the practical feasibility of these shallow Jastrow-based ansätze for applications on near-term quantum hardware.

Tkachenko, Nikolay V. [University of California, B↗
DOE OSTI2026

Molecular Design Principles for Photosystem I-Based Biohybrid Solar Fuel Catalysts

Direct solar-to-chemical conversion offers a compelling route to clean, dispatchable energy. Photosystem I (PSI), an evolutionarily optimized light-driven oxidoreductase, can be repurposed for solar-fuel production by coupling its photochemistry to catalytic interfaces. However, the molecular determinants that govern productive electron transfer to abiotic catalysts remain poorly understood. Here, we present molecular structures of active PSI-Pt nanoparticle (PtNP) biohybrids that reveal how protein architecture controls catalyst access, binding geometry, and photocatalytic efficiency. Removal of stromal subunits exposes the electron transfer chain and enables PtNP binding proximal to the F X cluster, demonstrating that steric occlusion limits access to native acceptor regions in PSI. In contrast, in trimeric PSI, PtNPs bind at multiple sites per monomer, but only a subset are positioned within electron transfer distance of terminal cofactors, resulting in a heterogeneous population of productive and nonproductive configurations. Structural analyses and molecular dynamics simulations define the interface topology, electrostatics, and cofactor-to-nanoparticle distances that govern catalyst binding and electron transfer. These results establish that catalytic inefficiency arises not only from intrinsic electron transfer constraints but also from the distribution of binding geometries imposed by the protein scaffold. Together, these findings provide a molecular framework linking protein structure to biohybrid function and define design principles for engineering PSI-based solar fuel systems and protein-nanomaterial interfaces for light-driven catalysis.

biohybrid↗
DOE OSTI2025

Unraveling the Heterogeneous but Ordered Microstructure of the Nonionic Deep Eutectic Solvent Formed by Lauric Acid and N -Methylacetamide

The nonionic deep eutectic solvent, formed by lauric acid (LA) and N-methylacetamide (NMA), has been shown to have a heterogeneous molecular structure in which the LA and NMA form nonpolar and polar domains, respectively. Previous vibrational spectroscopy experiments demonstrated that the ability of the LA domains to solvate compounds was limited to long carbon chains, whereas other nonpolar molecules, such as W(CO) 6 , were found to be solvated by both LA and NMA. These experiments were not fully compatible with the previously proposed micelle-like structure of the nonpolar domains of the LA-NMA DES. In this work, the modeling of the DES molecular structure is pursued using classical molecular dynamics simulations. The new classical model reproduces both the SAXS structural factors and the previously experimentally derived interaction map for these LA-NMA DESs. In addition, the simulation also shows that LA-NMA DESs form highly organized LA aggregates that are difficult to disorganize. Further evidence of the correct description provided by the newly derived model is obtained using a moderately polar probe: chloroform-d. Computations using the classical model have a good agreement with the solvation behavior of the probe derived from experiments, in which the location of the probe is found to be mostly within the polar domain of the DES. The computational model also demonstrates that the probe solvation is a consequence of the tightly packed LA structure, which causes nonpolar molecules to be located at the interphase of the DES nonpolar domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Chemical Diversity of Oligomers in Biomass Fast Pyrolysis Oils, Part 2: Heavy Lignin-Derived Molecules and Highly Dehydrated Sugars from Dichloromethane-Insoluble Pyrolytic Lignin

Here, this paper, the second in a series, investigates the water-insoluble, dichloromethane (DCM)-insoluble residue of BTG pyrolysis oil, also known in the literature as high-molecular-weight pyrolytic lignin (HMW-PL). HMW-PL accounts for 9.2 wt % of the original bio-oil, which is known to increase upon aging and contribute to coke formation during bio-oil upgrading. Understanding its composition is crucial for managing pyrolysis oil during the processing. The HMW-PL was fractionated using a silica gel column with solvents of increasing polarity: ethyl acetate (EA), acetone (AC), isopropanol (ISO), and methanol (MeOH), yielding 49.2, 19.9, 8.2, and 8.1 wt %, respectively. Each subfraction was characterized by UV-fluorescence, FTIR, HSQC NMR, and (−)APCI-FT-Orbitrap MS. Analysis revealed that the EA subfraction primarily contained aromatic dimers (C 19 –C 20 ) and trimers (C 17 –C 13 ), while the MeOH subfraction was rich in oxygenated aliphatic monomers (C 8 –C 16 ) likely derived from sugar dehydration products. The resulting fractions were further separated via preparatory HPLC. Fifty-five candidate molecular structures were proposed based on the Orbitrap MS data, supported by UV-fluorescence, FTIR, and NMR results. This fractionation strategy defined four distinct subfractions, enabling the proposal of surrogate molecular structures and advancing the molecular-level understanding of the HMW-PL fraction in the pyrolysis bio-oil.

High-Molecular-Weight PL↗
DOE OSTI2026

Analytic Nuclear Gradients Including Oriented External Electric Fields in a Molecule-Fixed Frame

Electric-field-assisted chemistry has attracted much attention in recent years, particularly in the context of oriented external electric fields for controlling molecular structure and reactivity. Such fields have been explored in a wide range of applications, including switching materials, nanoparticles, controllable catalysts, medicines, and clinical therapies. However, the determination of fixed fields in the laboratory frame becomes ineffective for flexible molecules, as conformational changes can significantly alter the relative orientation between the applied field and molecular structure. In this work, we propose two molecular reference frames─the principal axis frame and the local reference frame─to define oriented electric fields within the molecular framework. These coordinate systems powerfully eliminate ambiguities in the relative orientation between the applied field and the molecule. Analytic nuclear gradients in the presence of external electric fields are derived and implemented, with an initial application to field-dependent geometry optimizations of cis - and trans -formanilide. Analysis of the resulting field-induced equilibrium structures reveals distinct structural responses, validating the accuracy and robustness of the proposed formalism. The analytic gradient framework enables systematic investigations of molecular properties and reactivity under arbitrarily oriented electric fields, opening new opportunities for computational modeling and rational design in electric-field-controlled chemistry.

electric fields↗
DOE OSTI2026

Influence of thermal treatment on structure and catalytic performance of ceria-zirconia supported copper oxide (CuO x /Ce y Zr 1-y O 2 ) catalysts for CO oxidation

Copper oxide (CuO x ) supported on ceria-zirconia (Ce y Zr 1-y O 2 , y = 1.0, 0.5, 0.0) catalysts were investigated to elucidate the effects of thermal treatment on their physicochemical properties and catalytic performance in carbon monoxide (CO) oxidation. Here, the catalysts were synthesized via a one-pot chemical vapor deposition (OP-CVD) method at 700˚C and 900˚C with controlled Cu loading. Characterization techniques, including synchrotron X-ray diffraction (S-XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), inductively coupled plasma spectroscopy (ICP), and N 2 adsorption-desorption, were implemented to probe the crystalline structure, molecular and electronic structure, oxygen vacancies, specific surface area (SSA) and metal loading. CO oxidation was chosen as a model reaction to explore the structure-catalytic performance relationship. A ∼100% CO conversion was achieved at < 150˚C, particularly with the CuO x /CeO 2 catalyst calcined at 700˚C. In contrast, calcination at 900˚C caused a ∼90% decrease in SSA and a ∼24% increase in T 50 . Activity tests revealed that increasing ZrO 2 content lowered CO oxidation activity despite generating more defect sites. In-situ measurement of the 700 °C calcined samples revealed the presence of stable and unstable defects in CuO x /Ce 0.5 Zr 0.5 O 2 and CeO 2 respectively, which play a key role in the activity of the catalysts. The results highlight that catalytic performance is closely related to the SSA. Furthermore, an optimum calcination temperature favor significant oxygen vacancy formation with required CuO x -support interactions, enhancing redox properties and catalytic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Marine Algae Polysaccharides: An Overview of Characterization Techniques for Structural and Molecular Elucidation

Polysaccharides make up a large portion of the organic material from and in marine organisms. However, their structural characterization is often overlooked due to their complexity. With many high-value applications and unique bioactivities resulting from the polysaccharides’ complex and heterogeneous structures, dedicated analytical efforts become important to achieve structural elucidation. Because algae represent the largest marine resource of polysaccharides, the majority of the discussion is focused on well-known algae-based hydrocolloid polymers. The native environment of marine polysaccharides presents challenges to many conventional analytical techniques necessitating novel methodologies. We aim to deliver a review of the current state of the art in polysaccharide characterization, focused on capabilities as well as limitations in the context of marine environments. This review covers the extraction and isolation of marine polysaccharides, in addition to characterizations from monosaccharides to secondary and tertiary structures, highlighting a suite of analytical techniques.

09 BIOMASS FUELS↗
DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗
DOE OSTI2026

Two datasets are better than one: method of double moments for 3D reconstruction in cryo-EM

Cryo-electron microscopy is a powerful imaging technique for reconstructing three-dimensional molecular structures from noisy tomographic projection images of randomly oriented particles. We introduce a new data fusion framework, termed the method of double moments, which reconstructs molecular structures from two instances of the second-order moment of projection images obtained under distinct orientation distributions: one uniform, the other non-uniform and unknown. We prove that these moments generically uniquely determine the underlying structure, up to a global rotation and reflection, and we develop a convex-relaxation-based algorithm that achieves accurate recovery using only second-order statistics. Our results demonstrate the advantage of collecting and modeling multiple datasets under different experimental conditions, illustrating that leveraging dataset diversity can substantially enhance reconstruction quality in computational imaging tasks.

Kam’s method↗
DOE OSTI2025

Molecular and structural characterization of a Bacillus cereus strain producing an anthrax-like capsule

Bacillus cereus is a ubiquitous Gram-positive, spore-forming, rod-shaped saprophytic bacterium, occasionally reported to cause food-borne illnesses. However, instances of B. cereus strains harboring anthrax toxin and capsule genes have elevated certain strains as formidable pathogens and biothreats. This study focuses on the genomic analysis and the structural characterization of capsular material produced by the virulent B. cereus PATH2418 strain, isolated from the wound of a traumatic open fracture patient. The genome was sequenced using Nanopore MinION sequencing, revealing a chromosome of 5,270,283 bp and three plasmids. One plasmid, pATH1, was found to encode an operon for the biosynthesis of a bacterial capsule. This operon had sequence homology to the Bacillus anthracis capBCADE operon, which encodes the poly-γ-D-glutamate (PDGA) capsule. The capsule production in B. cereus PATH2418 was influenced by temperature and CO 2 levels. Structural analysis of the capsular material using a combined approach of nuclear magnetic resonance (NMR) and high-performance liquid chromatography (HPLC) techniques confirmed the presence of a high-molecular-weight poly-γ-glutamate capsule, with an enantiomeric composition of approximately 67% D-glutamic acid and 33% L-glutamic acid, matching that of B. anthracis.

Bacillus cereus↗
DOE OSTI2025

Quantum chemically calculated Abraham parameters for quantifying and predicting polymer hydrophobicity

The leakage and accumulation of plastic in the environment is a significant and growing problem with numerous detrimental impacts and has led to a push toward the design and development of more environmentally benign materials. To this end, we have developed a quantum chemistry-based model for predicting the mobility of polymer materials from molecular structure. Hydrophobicity is used as a surrogate for mobility given that hydrophobic interactions drive much of the partitioning of contaminants in and out of various environmentally relevant compartments. To model polymer hydrophobicity, we adjusted a previously developed Quantum Chemically Calculated Abraham Parameter model to calculate Abraham parameters of small molecules from molecular structure information. The resulting model predicted the octanol-water partition coefficient (K OW ) of polymer repeating units with a root mean square error (RMSE) of 0.48 (log scale). Additionally, the hydrophobicity of high molecular weight polymer materials was captured through solubility parameters and Nile red staining experiments from the literature and predicted with RMSEs of 1.21 (J/cc) 0.5 and 3.42 nm, respectively. Finally, to test the environmental applicability of the model, the relative adsorption capacity of three polymers was predicted and used to unify sorption isotherms across multiple sorbates and polymer sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗
DOE OSTI2026

On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials

Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.

Kidder, Katherine M [Department of Chemistry; Univ↗
DOE OSTI2025

Visualizing the Three-Dimensional Arrangement of Hydrogen Atoms in Organic Molecules by Coulomb Explosion Imaging

Structure-sensitive methods based on femtosecond light or electron pulses are now making it possible to measure how molecular structures change during light-induced processes. Despite significant progress, high-fidelity imaging of nuclear positions remains a challenge even for relatively small molecular systems and, notably, regarding the positions of hydrogen atoms. As demonstrated in recent work, X-ray-induced Coulomb explosion imaging (CEI) may overcome this obstacle, as its sensitivity does not depend on the mass of the imaged atoms. The photoinduced ring opening of the heterocyclic molecule 2(5 H )-thiophenone has attracted recent interest. Here, in this work, we show that CEI offers a powerful route to imaging the peripheral H atoms in this molecule and thus, more generally, to tracking detailed nuclear motions (e.g., isomerizations) in organic molecules on ultrafast time scales. Specifically, we record momentum-space Coulomb explosion images that report on the three-dimensional positioning of all nuclei within the molecule, for instance, distinguishing H atoms in C–H bonds that lie within or are directed out of the plane defined by the heavy atoms. The prospect of imaging peripheral H atoms to probe photochemical dynamics is explored by coupling ab initio molecular dynamics with classical Coulomb explosion simulations, thereby differentiating potential photoproduct isomers, including those whose structures primarily differ in the position of the hydrogens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Synthetically Reversible, Proton-Mediated Nitrite N–O Bond Cleavage at a Dicopper Site

A monocationic dicopper(I,I) nitrite complex [Cu 2 (μ-κ 1 :κ 1 -O 2 N)DPFN][NTf 2 ] (2) (DPFN = 2,7-bis(fluoro-di(2-pyridyl)methyl)-1,8-naphthyridine, NTf 2 – = N(SO 2 CF 3 ) 2 – ), was synthesized by treatment of a dicopper acetonitrile complex, [Cu 2 (μ-MeCN)DPFN][NTf 2 ] 2 (1), with tetrabutylammonium nitrite ([nBu 4 N][NO 2 ]). DFT calculations indicate that 2 is one of three linkage isomers that are close in energy and presumably accessible in solution. Reaction of the μ-κ 1 :κ 1 -O 2 N complex with p-TolSH produces nitrous acid (HONO) and the corresponding dicopper thiolate species via an acid–base exchange reaction. Notably, treatment of 2 with HNTf 2 results in N–O bond cleavage in the putative, HONO-ligated complex to form the more thermodynamically favorable nitrosyl-bridged dicopper complex [Cu 2 (μ-NO)(μ-OH)DPFN][NTf 2 ] 2 (4). This scission can be reversed via deprotonation of the hydroxy ligand with KO t Bu. X-ray diffraction studies confirmed the solid-state molecular structures of 2 and 4. DFT calculations were used to construct a reaction coordinate diagram detailing formation of the μ-NO complex and to describe its electronic structure. The nitrosyl ligand in 4 is chemically labile, as demonstrated by its ready displacement in reactions with CO or NO 2 – .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Engineering Enantiocomplementary Protoglobins for Stereoconvergent Construction of N -Alkylated α-Aminoketones

The synthesis of enantiopure compounds from a mixture of E/Z alkenes represents a notable challenge in synthetic chemistry. While enzymes excel in achieving unparalleled selectivity, their inherent specificity often confines activity to a single stereoisomeric substrate, consequently restricting the overall efficiency of such transformations. Here, we demonstrate that protoglobin-derived hemoproteins can catalyze stereoconvergent intermolecular amination using simple N-alkyl hydroxylamines as nitrene precursors, a transformation which remains elusive in synthetic chemistry. These engineered enzymes process E/Z mixtures of silyl enol ethers, enabling the precise incorporation of N-alkyl amino moieties (−NHAlkyl) into diverse molecular structures (up to 79% yield and 95% ee). Two complementary protoglobin variants were engineered using directed evolution to enable enantiodivergent synthesis of both enantiomers of α-aminoketones. This enzymatic platform achieves stereoconvergent and enantiodivergent transformations, facilitating the conversion of simple chemicals into an array of valuable pharmaceutical compounds featuring aminoketone functionalities.

Alcohols↗
DOE OSTI2024

Characterize and control the multi-range structure of solution-phase systems with resonant x-ray scattering

This work aims at demonstrating the feasibility and impact of Anomalous X-ray Scattering (AXS) in characterizing the multi-range structures of solution-state systems. We will show preliminary investigation of long-range correlations in concentrated aqueous electrolytes with a combination of AXS and molecular dynamics (MD) simulations. We will also start exploring the capability of AXS to capture intra- and inter-molecular structure of dilute molecular systems, and specifically its sensitivity to the chemical environment surrounding active metal sites. We anticipate that the development of this method will help us to understand ion solvation and transport, which affect the performances of, for instance, electrocatalytic cells, as well as to identify/control the intrinsic structural factors that lead to selectivity, efficiency, and stability control during catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fostering a Guiding Multiscale Model for the Development of Advanced MgB 2 Hydrogen Storage Materials (Final Technical Report)

Project Goal and Objective. The demand for energy and for an upgraded energy infrastructure has steadily grown, as have the needs for energy independence and alternatives to our reliance on petroleum. Hydrogen is considered the most viable fuels for wide-scale implementation in the near future as it is less-polluting, non-toxic, and has more stored energy than petroleum. It is envisioned that hydrogen can eventually become the prime energy carrier, integrating the transportation, grid, and chemical sectors in a way that improves resiliency, diversifies feedstocks, and affords new economic opportunities. A key remaining challenge is the development materials with enhanced gravimetric and volumetric hydrogen storage capacities that offer a higher performance than compressed gas. These materials would eliminate the need for large-scale compression, thereby dramatically reducing the footprint and cost of gas storage. The high gravimetric and volumetric hydrogen capacities of complex hydrides has prompted an intensive investigation of the potential of this class of materials as hydrogen storage media over the past 25 years. Among the many complex hydrides that have been explored, magnesium borohydride, Mg(BH 4 ) 2 , has been found to possess the best combination of practical thermodynamic properties. These include a gravimetric H 2 density of 14.9 wt% H 2 and thermodynamics for the dehydrogenation of Mg(BH 4 ) 2 to MgB 2 (equation 1) (ΔH° = 39 kJ/mol H 2 , ΔS = 112 J/K mol H 2 ) which lie in the narrow window required Mg(BH 4 ) 2 $\Leftrightarrow$ MgB 2 + 4 H 2 (1) for reversibility under moderate pressure and temperature. However, overcoming the extremely slow kinetics of the reversible release of hydrogen by this material in the solid state is a daunting challenge. At temperatures greater than 400 °C, the borohydride releases up to 14 wt% hydrogen giving MgB 2 . We discovered that the direct re-hydrogenation of MgB 2 to Mg(BH 4 ) 2 can be accomplished under 950 bar H 2 at 400 °C. While this demonstrated that complete reversibility can be achieved, the conditions employed are far too extreme for commercial hydrogen storage applications. More recently, we found through US DOE funded research projects (EERE HyMARC and HySCOR), that hydrogen cycling, can be accomplish at much milder conditions upon modification of the borohydride or boride. Guided by these discoveries these discoveries, the objective of this research project was to obtain key information that will enable the development of a model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 . The ultimate goal of our efforts is to attain a model of this transformation that can be utilized to accelerate development further advanced materials. This project directly follows on discoveries that were made over the course of a US DOE, EERE HyMARC project that was focused on improvement of the hydrogen cycling kinetics of modified MgB 2 . We found that that mechanical milling with graphene results the desired, pronounced kinetic enhancement. The dramatic lowering of the conditions required for the hydrogenation of MgB 2 is a significant step towards overcoming its chemical inertness allowing its development as a practical onboard hydrogen storage material. However, the exact nature of the modification(s) of MgB 2 that is responsible for its activation towards hydrogenation is completely unknown. This situation is not unique, as efforts to develop hydrogen storage materials typically have a narrow focus rather than a comprehensive approach that takes atomic level bonding and structure; molecular dynamics; long range, nano- and mesoscale-structure and their interconnection all into account. The goal of this project was the development of a comprehensive, multi-scale computational model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 that can be utilized for development of higher performance versions of the modified material. Development of the model requires determination of: 1) the bulk, nano-scale, and meso-scale structural changes occurring at elevated pressure following mechano-chemical modification of MgB 2 ; 2) the reaction pathway of the reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 ; 3) the effect of elevated pressure and mechano-chemical modification on the chemical reaction pathways; 4) the interactions at solid-gas interfaces; and particle surfaces; and 5) the kinetics and thermodynamic parameters associated with each step of the hydrogenation reaction pathway. This investigation required advanced techniques as preliminary, standard XRD, 11 B NMR, and FTIR analysis showed no signs of material modification. In order to gain this level of understanding of modified MgB 2 , required the teaming of a diverse group of experts and state-of-the art experimental capabilities at the University of Hawaii at Manoa (UHM) and collaborating National Laboratories: Craig Jensen , Department of Chemistry (PI and Project Director), solid state, solution, and high pressure NMR spectroscopy; solid-state synthesis; and high pressure hydrogenation (collaboration with SNL); Godwin Severa , Hawaii Natural Energy Institute (co-PI) calorimetry; infrared and Raman spectroscopy (collaboration with NREL); Dera , high pressure X-ray diffraction including in situ experiments (collaboration with ANL); Hope Ishii , Hawaii Institute of Geophysics electron microscopy investigations (collaboration with LBNL); and Joe Brown , Mechanical Engineering , material electronic structure and electric field effects.

08 HYDROGEN↗