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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Determining the Role of Synthesis and Reaction Conditions on the Exposed Surface and Shape of ..beta..-Mo2C Catalysts

The production of drop-in quality biofuels typically can be achieved through catalytic fast pyrolysis (CFP) of biomass, followed by hydrodeoxygenation (HDO) of the vapor-phase product to reduce the oxygen content and stabilize the bio-oil product. To favor selectivity toward desired deoxygenation products, bifunctional catalysts with both acidic and hydrogenation sites are often employed. Due to both its oxophilicity and its ability to promote hydrogenation reactions, molybdenum carbide catalysts have shown promise for promoting the HDO of CFP vapors. However, the surface structure and composition of carbide catalyst particles are not well understood, precluding the establishment of fundamental structure-function relationships needed for the rational development of molybdedum carbide for HDO, as well as other reactions. For orthorhombic ..beta..-Mo2C, the (100) facet is largely studied for computational surface-reaction analyses, possibly due to its similarities with the close-packed (111) facet of noble-metal catalysts. However, it has previously been postulated through ab initio thermodynamic studies that the (111), (110), and (011) facets are most stable, though there is no consensus. Furthermore, while a majority of previous surface stability analyses of ..beta..-Mo2C focus on bulk terminations, the highly carburizing synthesis conditions and the use of ..beta..-Mo2C in carbon-containing reaction applications could introduce non-stoichiometric coverages of surface carbon. As such, this study uses ab initio thermodynamics calculations to assess the relative surface stability of the low-index facets of ..beta..-Mo2C, including consideration of varying the coverage of surface carbon. From this information, Wulff constructions are utilized to predict the synthesis and reaction condition-dependent shape and surface carbon composition of ..beta..-Mo2C catalyst particles.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2020

Graph theory approach to determine configurations of multidentate and high coverage adsorbates for heterogeneous catalysis

Abstract Heterogeneous catalysts constitute a crucial component of many industrial processes, and to gain an understanding of the atomic-scale features of such catalysts, ab initio density functional theory is widely employed. Recently, growing computational power has permitted the extension of such studies to complex reaction networks involving either high adsorbate coverages or multidentate adsorbates, which bind to the surface through multiple atoms. Describing all possible adsorbate configurations for such systems, however, is often not possible based on chemical intuition alone. To systematically treat such complexities, we present a generalized Python-based graph theory approach to convert atomic scale models into undirected graph representations. These representations, when combined with workflows such as evolutionary algorithms, can systematically generate high coverage adsorbate models and classify unique minimum energy multidentate adsorbate configurations for surfaces of low symmetry, including multi-elemental alloy surfaces, steps, and kinks. Two case studies are presented which demonstrate these capabilities; first, an analysis of a coverage-dependent phase diagram of absorbate NO on the Pt 3 Sn(111) terrace surface, and second, an investigation of adsorption energies, together with identifying unique minimum energy configurations, for the reaction intermediate propyne (CHCCH 3 *) adsorbed on a PdIn(021) step surface. The evolutionary algorithm approach reproduces high coverage configurations of NO on Pt 3 Sn(111) using only 15% of the number of simulations required for a brute force approach. Furthermore, the screening of potentially hundreds of multidentate adsorbates is shown to be possible without human intervention. The strategy presented is quite general and can be applied to a spectrum of complex atomic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Theoretical and kinetic modeling study of H 2 S pyrolysis

Hydrogen sulfide pyrolysis was investigated theoretically and through chemical kinetic modeling. Reactions on the SHH potential energy surface, primarily S + H 2 (+Ar) ⇌ H 2 S (+ Ar) (R1) and S + H 2 ⇌ SH + H (R6b) were characterized by ab initio calculations. Results for k 1 were in good agreement with experiment, but deviated strongly below 2000 K from values previously used in modeling. Collider efficiencies for H 2 S, S 2 , and N 2 compared to Ar were calculated for R1. Hydrogen sulfide decomposition experiments reported in literature were re-examined in terms of an updated detailed chemical kinetic model. Concentration profiles for the atomic S at high temperature in shock tubes supported the present value of k 1 and served to constrain the rate constants for reaction of S with SH and H 2 S. To explain results from batch and flow reactors, conducted at high H 2 S concentrations in the 900–1400 K range, a very fast rate constant was required for HSS + H ⇌ SH + SH. Under dilute conditions, the gas-phase chemistry was too slow to compete and the decomposition of H 2 S was controlled by loss on the reactor surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

An Ab Initio Multiple Cloning Method for Non-Adiabatic Excited-State Molecular Dynamics in NWChem

The recently developed ab-initio multiple cloning (AIMC) approach based on the multicongurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to non-adiabatic dynamics with a particular strength in the proper description of decoherence effects due to branching of vibrational wavepackets at a level crossing. In this work, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-eld theory to determine the equations of motion for classical trajectories. The multi-dimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based non-adiabatic coupling approach within the AIMC method, all observable are calculated on-the-y in the non-adiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level non-adiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
DOE OSTI2023

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling

Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modelling. Although classical force fields often fail to describe the coupling between electronic states and ionic rearrangements, the more accurate ab initio molecular dynamics suffers from computational complexity that prevents long-time and large-scale simulations, which are essential to study technologically relevant phenomena. Here we present the Crystal Hamiltonian Graph Neural Network (CHGNet), a graph neural network-based machine-learning interatomic potential (MLIP) that models the universal potential energy surface. CHGNet is pretrained on the energies, forces, stresses and magnetic moments from the Materials Project Trajectory Dataset, which consists of over 10 years of density functional theory calculations of more than 1.5 million inorganic structures. The explicit inclusion of magnetic moments enables CHGNet to learn and accurately represent the orbital occupancy of electrons, enhancing its capability to describe both atomic and electronic degrees of freedom. We demonstrate several applications of CHGNet in solid-state materials, including charge-informed molecular dynamics in Li x MnO 2 , the finite temperature phase diagram for Li x FePO 4 and Li diffusion in garnet conductors. We highlight the significance of charge information for capturing appropriate chemistry and provide insights into ionic systems with additional electronic degrees of freedom that cannot be observed by previous MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temperature-Dependent Properties of Molten Li 2 BeF 4 Salt Using Ab Initio Molecular Dynamics

Molten lithium tetrafluoroberyllate (Li 2 BeF 4 ) salt, also known as FLiBe, with a 2:1 mixture of LiF and BeF 2 is being proposed as a coolant and solvent in advanced nuclear reactor designs, such as the molten salt reactor or the fluoride salt cooled high-temperature reactor. We present the results on the structure and properties of FLiBe over a wide range of temperatures, 0–2000 K, from high-throughput ab initio molecular dynamics simulation using a supercell model of 504 atoms. The variations in the local structures of solid and liquid FLiBe with temperature are discussed in terms of a pair distribution function, coordination number, and bond angle distribution. The temperature-dependent electronic structure and optical and mechanical properties of FLiBe are calculated. The optical and mechanical property results are reported for the first time. The results above and below the melting temperature (~732 K) are compared with the experimental data and with data for crystalline FLiBe. The electronic structure and interatomic bonding results are discussed in correlation with the mechanical strength. A novel concept of total bond order density (TBOD), an important quantum mechanical parameter, is used to characterize the internal cohesion and strength in the simulated models. The results show a variation in the rate of change in properties in solid and liquid phases with anomalous behavior across the melting region. The observed trend is the decrease in mechanical strength, band gap, and TBOD in a nonlinear fashion as a function of temperature. The refractive index shows a surprising minimum at 850 K, among the tested temperatures, which lies above the melting point. These findings provide a new platform to understand the interplay between the temperature-dependent structures and properties of FLiBe salt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Strong-field nonsequential double photoionization using virtual-detector theory with path summation

We present an ab initio study of the nonsequential strong-field ionization dynamics of a model two-electron atom with helium character. Single- and double-ionization events are characterized and displayed using detector signals extracted at different points in the two-electron two-dimensional space. The double photoelectron momentum distribution is calculated via coherent path-summation over virtual-particle trajectories. A comparison is made between the momentum distributions obtained with the virtual-detector method, the Schrödinger wave function, and the time-dependent surface flux method developed by Tao and Scrinzi [New J. Phys. 14, 013021 (2012)]. Insights into different ionization and electron recollision pathways are gained from detailed virtual-particle tracking and energy-time readouts. Furthermore, this study demonstrates the extension of virtual-detector theory to strong-field multielectron quantum dynamics and highlights the importance of the evolving quantum phase in quasiclassical electron propagation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

The effect of Cu additions in FePt–BN–SiO 2 heat-assisted magnetic recording media

Structural and chemical order impact magnetic properties of solids, which are governed by spin–orbit coupling and exchange interaction. The ordered L1 0 phase of FePt is a key material to heat-assisted magnetic recording; to enable high storage density, a solid understanding is needed of structural and chemical disorder at small length scales, as well as associated modifications of the electronic band structure. Here, we investigate the effect of boron and copper additions (≲6 mol% Cu) on structural and magnetic properties of L1 0 FePt granular media. Two copper-driven mechanisms, although competing, can lead to improvements in both structural and magnetic properties. In particular, the Cu substitution on the Fe-site leads to a degradation of magnetic properties due to the delocalized electron orbitals originating from a larger Cu d -orbital occupancy. At the same time, Cu substitution leads to an enhanced crystallographic order and consequently magneto-crystalline anisotropy, which offsets the former effect to a large extent. Our study is based on magnetometry, x-ray absorption spectroscopy, ab-initio calculations and a phenomenological theory of disordered FePt granular media. We do not observe a sizable modification to Fe moments and electronic configuration; Cu reveals two different resonances associated with the presence and absence of Cu–B bonds that vary with total Cu concentration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Dynamic Competition between Hubbard and Superexchange Interactions Selectively Localizes Electrons and Holes through Polarons

Controlling the effects of photoexcited polarons in transition metal oxides can enable the long time-scale charge separation necessary for renewable energy applications and controlling new quantum phases through dynamically tunable electron–phonon coupling. In previously studied transition metal oxides, polaron formation is facilitated by a photoexcited ligand-to-metal charge transfer (LMCT). When the polaron is formed, oxygen atoms move away from iron centers, which increases carrier localization at the metal center and decreases charge hopping. Studies of yttrium iron garnet and erbium iron oxide have suggested that strong electron and spin correlations can modulate photoexcited polaron formation. To understand the interplay between strong spin and electronic correlations in highly polar materials, we studied gadolinium iron oxide (GdFeO 3 ), which selectively forms photoexcited polarons through an Fe–O–Fe superexchange interaction. Excitation-wavelength-dependent transient extreme ultraviolet (XUV) spectroscopy selectively excites LMCT and metal-to-metal charge transfer (MMCT) transitions. Here, the LMCT transition suppresses photoexcited polaron formation due to the balance between superexchange and Hubbard interactions, while MMCT transitions result in photoexcited polaron formation within 250 ± 40 fs. Ab initio theory demonstrates that electron and hole polarons localize on iron centers following MMCT. In addition to understanding how strong electronic and spin correlations can control strong electron–phonon coupling, these experiments separately measure electron and hole polaron interactions on neighboring metal centers for the first time, providing insight into a large range of charge-transfer and Mott–Hubbard insulators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ab initio structural dynamics of pure and nitrogen-containing amorphous carbon

Abstract Amorphous carbon (a-C) has attracted considerable interest due to its desirable properties, which are strongly dependent on its structure, density and impurities. Using ab initio molecular dynamics simulations we show that the sp 2 /sp 3 content and underlying structural order of a-C produced via liquid quenching evolve at high temperatures and pressures on sub-nanosecond timescales. Graphite-like densities ( $$\lesssim$$ ≲ 2.7 g/cc) favor the formation of layered arrangements characterized by sp 2 disordered bonding resembling recently synthesized monolayer amorphous carbon (MAC), while at diamond-like densities ( $$\gtrsim$$ ≳ 3.3 g/cc) the resulting structures are dominated by disordered tetrahedral sp 3 hybridization typical of diamond-like amorphous carbon (DLC). At intermediate densities the system is a highly compressible mixture of coexisting sp 2 and sp 3 regions that continue to segregate over 10’s of picoseconds. The addition of nitrogen (20.3%) (a-CN) generates major system features similar with those of a-C, but has the unexpected effect of reinforcing the thermodynamically disfavored carbon structural motifs at low and high densities, while inhibiting phase separation in the intermediate region. At the same time, no nitrogen elimination from the carbon framework is observed above $$\simeq$$ ≃ 2.8 g/cc, suggesting that nitrogen impurities are likely to remain embedded in the carbon structures during fast temperature quenches at high pressures.

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

Mechanism of Antiferroelectricity in Polycrystalline ZrO 2

The size and electric field dependent induction of polarization in antiferroelectric ZrO 2 is the key to several technological applications that are unimaginable a decade ago. However, the lack of a deeper understanding of the mechanism hinders progress. Molecular dynamics simulations of polycrystalline ZrO 2 , based on machine-learned interatomic forces with near ab initio quality, shed light on the fundamental mechanism of the size effect on the transition fields. Stress in the oxygen sublattice is the most important factor. The so constructed interatomic forces allow the calculation of the transition fields as a function of the ZrO 2 film thickness and predict the ferroelectricity at large thickness. The simulation results are validated with electrical and piezo response force microscopy measurements. The results allow a clear interpretation of the properties of the double-hysteresis loops as well as the construction of the free energy landscape of ZrO 2 grains.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermodynamics of the Metal Carbonates and Bicarbonates of Mn, Co, Ni, Cu, and Zn Relevant to Mineral Energetics

The gas phase heats of formation of ground-state MCO 3 , M(HCO 3 ) 2 , and M(HCO 3 )(OH), where M = Mn, Co, Ni, Cu, and Zn, have been predicted using the correlated molecular orbital theory at the CCSD(T) level extrapolated to the complete basis set limit using the Feller–Peterson–Dixon (FPD) approach. Cohesive energies of the carbonates were predicted based on the calculated gas phase and experimental solid heats of formation. Coulombic dissociation energies (CDEs) between metal cations and anions show a near-linear correlation with Shannon metal cation atomic radii, yet no correlation is found with the hardness of these cations. The total reaction dissociation energies (TRDEs) of transition metals are higher than their CDEs for the di-bicarbonates, in contrast to those for Mg and Ca based on our prior work. In addition to differences in the energies needed to prepare the transition metal dications, electron donation from the ligands to the 3d orbitals of open-shell transition metal dications from lone pairs of adjacent O atoms also plays a role. No electron donation from the ligands to the fully occupied 3d orbitals of Zn and Cd was found. Decomposition energies for generating MO, CO 2 , and/or H 2 O were calculated. Gas phase metal exchange energies only partially correlate with the electrochemical series for M(s) → M 2+( aq). The FPD heats of formation were used to benchmark a range of density functional theory exchange–correlation functionals, including those commonly used in solid-state mineral calculations. None of the functionals provided chemical accuracy agreement (±1 kcal/mol) with the FPD results. So, the best agreement with the FPD results is predicted for the $\tau$-HCTH functional with an average unsigned error of 8.3 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The symmetric quasi-classical model using on-the-fly time-dependent density functional theory within the Tamm–Dancoff approximation

The primary computational challenge when simulating nonadiabatic ab initio molecular dynamics is the unfavourable compute costs of electronic structure calculations with molecular size. Simple electronic structure theories, like time-dependent density functional theory within the Tamm–Dancoff approximation (TDDFT/TDA), alleviate this cost for moderately sized molecular systems simulated on realistic time scales. Although TDDFT/TDA does have some limitations in accuracy, an appealing feature is that, in addition to including electron correlation through the use of a density functional, the cost of calculating analytic nuclear gradients and nonadiabatic coupling vectors is often computationally feasible even for moderately sized basis sets. Here in this work, some of the benefits and limitations of TDDFT/TDA are discussed and analysed with regard to its applicability as a ‘back-end’ electronic structure method for the symmetric quasi-classical Meyer–Miller model (SQC/MM). In order to investigate the benefits and limitations of TDDFT/TDA, SQC/MM is employed to predict and analyse a prototypical example of excited-state hydrogen transfer in gas-phase malonaldehyde. Then, the ring-opening dynamics of selenophene are simulated, which highlight some of the deficiencies of TDDFT/TDA. Additionally, some new algorithms are proposed that speed up the calculation of analytic nuclear gradients and nonadiabatic coupling vectors for a set of excited electronic states.

molecular dynamics↗
DOE OSTI2026

Ab initio thermodynamics of Ni and Co incorporation in Mg hydroxide, carbonate, and hydroxycarbonate minerals

Ni and Co are critical elements needed for modern technologies, and a better understanding of the ability of Mg-based minerals to incorporate these elements would benefit strategy development for Ni and Co recovery from mafic and ultramafic deposits. Here, in this work, we performed density functional theory (DFT) calculations of Ni and Co incorporation in six potential products of the carbonation of mafic and ultramafic silicates: brucite (Mg(OH) 2 ), magnesite (MgCO 3 ), nesquehonite (MgCO 3 ⸱3H 2 O), lansfordite (MgCO 3 ⸱5H 2 O), artinite (Mg 2 CO 3 (OH) 2 ⸱3H 2 O), and hydromagnesite (Mg 5 (CO 3 ) 4 (OH) 2 ⸱4H 2 O). The DFT results were used in an ab initio thermodynamics framework to explore the pH 2 O–pCO 2 conditions at which the Mg-based minerals were predicted to be thermodynamically stable and to quantify the Gibbs free energy of Ni and Co substitution at Mg sites. Among the six Mg-based minerals, brucite and magnesite were predicted to have the lowest Ni and Co substitution free energy. An analysis of the effect of temperature indicated that, at low temperature (<100 K), brucite more readily accommodated Ni and Co, while, at higher temperature (>335 K), magnesite more favorably incorporated Ni and Co. Between 100 K and 335 K, Ni was predicted to preferentially substitute for Mg in brucite and Co for Mg in magnesite, thus leading to a driving force for separating Ni and Co in conditions where brucite and magnesite both form. Insights gained in this work could therefore help select experimental conditions that either promote or inhibit incorporation of these critical elements into Mg-based mineral phases.

Critical elements↗
DOE OSTI2024

Additive Molar Volumes in Amorphous Ca/Sr Carbonate Solid Solutions

The development of predictive models of minor element incorporation in crystalline carbonate end products requires an understanding of the fundamental controls on metastable intermediate phase composition. In this study, we used small-angle X-ray scattering (SAXS), X-ray pair distribution function (PDF), thermogravimetric analysis (TGA), inductively coupled plasma mass spectrometry (ICP-MS), and transmission electron microscopy (TEM) to determine the composition-dependent density of an amorphous calcium–strontium carbonate (ACSC) solid solution. The amorphous calcium carbonate (ACC) and strontium carbonate (ASC) measured densities were ρ ACC = 2.19 ± 0.04 g/cm 3 and ρ ASC = 2.97 ± 0.05 g/cm 3 . Throughout our work, the experiments showed a dependence of the water content of the amorphous solid solution on the Sr mole fraction. An equation that relates the molar volume to the average cation radius, the carbonate ion radius, and the water volume was parameterized for hydrated crystalline carbonates and predicted well the molar volume of the ACSC solid solution. This finding indicates that, as for hydrated crystalline carbonates, the molar volumes of amorphous carbonates are additive and that water is a structural component of ACSC. Ab initio molecular dynamics (AIMD) simulations of the ACSC solid solutions showed strong linear correlations between calculated molar volumes and Sr and H 2 O contents, thus supporting the experimental results. In conclusion, our findings highlight the need to consider the full CaCO 3 –MeCO 3 –H 2 O ternary when quantifying metal cation incorporation in ACC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Spin-liquid behavior of the three-dimensional magnetic system Ba 3 NiIr 2 O 9 with S = 1

The quantum spin liquid (QSL) is an exotic phase of magnetic materials where the spins continue to fluctuate without any symmetry breaking down to zero temperature. Among the handful reports of QSL with spin S ≥ 1, examples with magnetic ions on a three-dimensional (3D) magnetic lattice are extremely rare since both larger spin and higher dimension tend to suppress quantum fluctuations. In this work, we offer a new strategy to achieve 3D QSL with high spin by utilizing two types of transition metal ions; both are magnetically active but located at crystallographically inequivalent positions. Furthermore, we design a 3D magnetic system Ba 3 NiIr 2 O 9 consisting of interconnected corner-shared NiO 6 octahedra and face-shared Ir 2 O 9 dimer, both having triangular arrangements in a-b plane. X-ray absorption spectroscopy measurements confirm the presence of Ni 2+ (S = 1). Furthermore, our detailed thermodynamic and magnetic measurements reveal that this compound is a realization of gapless QSL state down to at least 100 mK. Ab initio calculations find a strong magnetic exchange between Ir and Ni sublattices and in-plane antiferromagnetic coupling between the dimers, resulting in dynamically fluctuating magnetic moments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Controlling Structural, Electronic, and Energy Flow Dynamics of Catalytic Processes through Tailored Nanostructures

MoS 2 (molybdenum disulfide) is a highly-versatile catalyst material for support of numerous reactions from hydrodesulfurization and denitrogenation to the focus of this renewal proposal: hydrogenation of CO/CO 2 towards (higher) alcohols. At the same time, MoS 2 is a non-toxic, environmentally-benign and rather inert material- which under ambient conditions for some time has served as a lubricant and, more recently, as next-generation electronic material. The apparent contrast between inertness and stability in ambient, and catalytic activity under reactive conditions is puzzling and calls for a synergistic theoretical and experimental investigation with the long-term objective of enabling the rational design of MoS 2 -based catalysts for alcohol-formation reactions by providing a microscopic understanding of the environmental factors that determines site activity and selectivity. Our research project seeks answers to the questions (a) what conformation does MoS 2 adopt under reaction conditions (as opposed to that under ultrahigh vacuum and low temperatures)?; (b) what reaction pathways exist on such a material?; (c) how can the local environment of the active sites be manipulated so as to make MoS 2 an efficient catalyst for production of higher alcohol from syngas? In particular, research strategies will explore how the basal plane composed of sulfur atoms can be activated so as to exhibit a reactivity of its own, by addressing three research targets and building on extensive preliminary and enabling work: (1) vacancies and vacancy aggregates on the basal plane; (2) non-local catalyst transformation through alkali doping, hydrogenation and phase transition; (3) fabrication of a metal-nanoparticle-activated MoS 2 system, in which particle anchoring, reactive sites and pathways as well as selectivity are controlled by design, as an example of predictive development of a catalyst material,. All strategies are directed to improve the efficacy of the key reactive sites and selectivity of chemical pathways by design, to replace the inefficient methodology of trial and error in catalyst development. This research project represents a synergistic combination of computational guidance, foundational surface-science-based experiments and validation under reactive conditions that aims at transformative new insights into the working of MoS 2 -based hydrogenation-catalysts, a topic squarely at the center of the interest of DOE BES. Guided and led by Talat Rahman, a computational physicist, this project will apply density functional theory to understand structure, reaction pathways and chemical potentials associated with MoS 2 -based CO/CO 2 hydrogenation, augmented by kinetic Monte Carlo methods for reaction rates and prefactors as well as ab-initio molecular dynamics for evaluation of thermal stability. Complementary experimental input and validation will originate from co-PI Ludwig Bartels, a physical chemist and materials scientist, whose group focuses on local imaging and preparation of MoS 2 materials, from co-PI Peter Dowben, an experimental physicist, whose group is expert in the spectroscopy of occupied and unoccupied electronic states, and from senior collaborator Michael White of Brookhaven National Laboratory, whose group generates high-resolution electronic and activity information on size-selected well-defined metal chalcogenide clusters. This collaborative effort will enable a comprehensive understanding of the correlation of structural integrity and catalytic activity of MoS 2 in forms ranging from extended films to individual particles with known geometries and binding sites. Alcohol formation from syngas is a rapidly emerging application that has great potential through facile, economic, and decentralized biomass gasification. CO 2 activation is one of the most pressing concerns of our time: increasing CO 2 levels in the atmosphere change the climate and expose the globe to environmental transformations with the potential for enormous economic and societal impact. We will investigate CO/CO 2 hydrogenation via an interdisciplinary research collaboration with established synergy – one that, in accordance with the mission of the DOE, involves accredited Hispanic-Serving Institutions and that, through student exchange with international collaborators and National Labs, will directly benefit a broad spectrum of communities and generate human resources in sciences essential to their future.

2D materials↗