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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Using Metadynamics to Reveal Extractant Conformational Free Energy Landscapes

Understanding the impact of extractant functionalization on metal-binding energetics in liquid-liquid extraction is essential to guide the development of better separation processes. Traditionally, computational extractant design uses electronic structure calculations on metal-ligand clusters to determine the metal-binding energy of the lowest energy state. Although highly accurate, this approach does not account for all of the relevant physics encountered under experimental conditions. Such methodologies often neglect entropic contributions such as temperature effects and ligand flexibility, in addition to approximating solvent-extractant interactions with implicit solvent models. In this study, we use classical molecular dynamics simulations with an advanced sampling method, metadynamics, to map out extractant molecule conformational free energies in the condensed phase. Here we generate the complete conformational landscape in solution for a family of bidentate malonamide-based extractants with different functionalizations of the headgroup and the side chains. In particular, we show how such alkyl functionalization reshapes the free energy landscape, affecting the free energy penalty of organizing the extractant into the cis-like metal-binding conformation from the trans-like conformation of the free extractant in solution. Specifically, functionalizing alkyl tails to the center of the headgroup has a greater influence on increasing molecular rigidity and disfavoring the binding conformation than functionalizing side chains. These findings are consistent with trends in metal-binding energetics based on experimentally reported distribution ratios. We also consider a different bidentate extractant molecule, carbamoylmethylphosphine oxide, and show how the choice of solvent can further reshape the conformational energetic landscape. This study demonstrates the feasibility of using molecular dynamics simulations with advanced sampling techniques to investigate extractant conformational energetics in solution, which, more broadly, will enable extractant design that accounts for entropic effects and explicit solvation.

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

A family of ionic supersalts with covalent-like directionality and unconventional multiferroicity

Ionic crystals composed of elemental ions such as NaCl are non-polar due to directionless ionic bonding interactions. Here, we show that these can develop polarity by changing their building blocks from elemental ions to superalkali and superhalogen cluster-ions, which mimic the chemistry of alkali and halogen atoms, respectively. Due to the non-spherical geometries of these cluster ions, corresponding supersalts form anisotropic polar structures with ionic bonding, yet covalent-like directionality, akin to sp 3 hybridized systems. Using density functional theory and extensive structure searches, we predict a series of stable ferroelectric/ferroelastic supersalts, PnH 4 MX 4 (Pn = N, P; M = B, Al, Fe; X = Cl, Br) composed of superalkali PnH 4 and superhalogen MX 4 ions. Unlike traditional ferroelectric/ferroelastic materials, the cluster-ion based supersalts possess ultra-low switching barrier and can endure large ion displacements and reversible strain. In particular, PH 4 FeBr 4 exhibits triferroic coupling of ferroelectricity, ferroelasticity, and antiferromagnetism with controllable spin directions via either ferroelastic or 90-degree ferroelectric switching.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tuning Catalytic Reactivity via Wetting Control through Oxygen Vacancies: Ru Clusters on Anatase TiO 2 and CeO 2 Supports

The shape of supported metal particles regulates their catalytic reactivity and is determined by the degree of wetting between the metal particle and the support surface. Flattened particles that wet support surfaces were reported in various catalytic systems, particularly in the subnanometer size regime. Such consequential metal–support wetting phenomena are poorly understood, and methods to study them on powder catalysts under realistic conditions are lacking. Here, we investigate the size-dependent wetting behaviors of Ru particles on two reducible-oxide supports, anatase TiO 2 (TiO 2 -A) and CeO 2 , under reducing catalytic conditions. X-ray absorption spectroscopy (XAS), low-energy ion scattering (LEIS), and density functional theory (DFT) are combined to determine the shape of Ru particles. Ru particles remain three-dimensional without wetting the TiO 2 -A support within the coverage range studied (0.06–0.98 Ru nm –2 ). In contrast, at low coverages (<0.25 Ru nm –2 ), Ru wets the CeO 2 support to form flat, disordered structures. The higher wettability of CeO 2 than TiO 2 -A is attributed to oxygen vacancies in the near-surface region. The shape difference between small Ru particles or clusters on the two supports leads to drastically contrasting catalytic reactivities in polyolefin hydrogenolysis, despite similar diameters. As a result, this work highlights the implications of metal–support wetting, or cluster shape, on catalytic behaviors of small metal clusters, while establishing the foundation for future systematic studies of such a phenomenon in realistic systems, by delivering a multitechnique methodology and revealing governing fundamental principles.

42 ENGINEERING↗
DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗
DOE OSTI2020

Data-Driven Many-Body Models for Molecular Fluids: CO 2 /H 2 O Mixtures as a Case Study

In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO2) and water (H2O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born–Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO 2 –CO 2 and CO 2 –H 2 O dimers and the energetics of small clusters, as well as to correctly reproduce various properties in both gas and liquid phases. Furthermore, building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions.

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

Tuning Electronic Properties of 2D Materials Using Metal Adsorbates: Cu at WTe 2 Edges

Two-dimensional materials exhibit properties promising for novel applications. Topologically protected states at their edges can be harnessed for use in quantum devices. We use ab initio simulations to examine properties of edges in 1T'-WTe 2 monolayers, known to exhibit topological order, and their interactions with Cu atoms. Comparison of (010)-oriented edges that have the same composition but different terminations shows that, as the number of Cu atoms increases, their thermodynamically-preferred arrangement depends on the details of the edge structure. Cu atoms aggregate into a cluster at the most stable edge; while the cluster is non-magnetic, it spin-polarizes the W atoms along the edge, which removes the topological protection. At the metastable edge, Cu atoms form a chain incorporated into the WTe 2 lattice; the topological state is preserved in spite of the dramatic edge restructuring. This suggests that exploiting interactions of metal species with metastable edge terminations can provide a path towards non-invasive interfaces.

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

Evidence for Low-Valent Electronic Configurations in Iron–Sulfur Clusters

Although biological iron-sulfur (Fe–S) clusters perform some of the most difficult redox reactions in Nature, they are thought to be composed exclusively of Fe 2+ and Fe 3+ ions, as well as mixed-valent pairs with average oxidation states of Fe 2.5+ . We herein show that Fe–S clusters formally composed of these valences can access a wider range of electronic configurations—in particular, those featuring low-valent Fe 1+ centers. We demonstrate that CO binding to a synthetic [Fe 4 S 4 ] o cluster supported by N-heterocyclic carbene ligands induces generation of Fe 1+ centers via intracluster electron transfer, wherein a neighboring pair of Fe 2+ sites reduces the CO-bound site to a low-valent Fe 1+ state. Similarly, CO binding to an [Fe 4 S 4 ] + cluster induces electron delocalization with a neighboring Fe site to form a mixed-valent Fe 1.5+ Fe 2.5+ pair in which the CO-bound site adopts partial low-valent character. Furthermore, these low-valent configurations engender remarkable C–O bond activation without having to traverse highly negative and physiologically inaccessible [Fe 4 S 4 ] o /[Fe 4 S 4 ] – redox couples.

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

Superior Capacitive Energy-Storage Performance in Pb-Free Relaxors with a Simple Chemical Composition

Chemical design of lead-free relaxors with simultaneously high energy density (W rec ) and high efficiency (η) for capacitive energy-storage has been a big challenge for advanced electronic systems. The current situation indicates that realizing such superior energy-storage properties requires highly complex chemical components. Herein, we demonstrate that, via local structure design, an ultrahigh W rec of 10.1 J/cm 3 , concurrent with a high η of 90%, as well as excellent thermal and frequency stabilities can be achieved in a relaxor with a very simple chemical composition. By introducing 6s 2 lone pair stereochemical active Bi into the classical BaTiO 3 ferroelectric to generate a mismatch between A- and B-site polar displacements, a relaxor state with strong local polar fluctuations can be formed. Through advanced atomic-resolution displacement mapping and 3D reconstructing the nanoscale structure from neutron/X-ray total scattering, it is revealed that the localized Bi enhances the polar length largely at several perovskite unit cells and disrupts the long-range coherent Ti polar displacements, resulting in a slush-like structure with extremely small size polar clusters and strong local polar fluctuations. This favorable relaxor state exhibits substantially enhanced polarization, and minimized hysteresis at a high breakdown strength. This work offers a feasible avenue to chemically design new relaxors with a simple composition for high-performance capacitive energy-storage.

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

Introducing metal–sulfur active sites in metal–organic frameworks via post-synthetic modification for hydrogenation catalysis

Metal–sulfur active sites play a central role in catalytic processes such as hydrogenation and dehydrogenation, yet the majority of active sites in these compounds reside on the surfaces and edges of catalyst particles, limiting overall efficiency. Here we present a strategy to embed metal–sulfur active sites into metal–organic frameworks (MOFs) by converting bridging or terminal chloride ligands into hydroxide and subsequently into sulfide groups through post-synthetic modification. We apply this method to two representative MOF families: one featuring one-dimensional metal–chloride chains and another containing discrete multinuclear metal clusters. Crystallographic and spectroscopic analyses confirm structural integrity and sulfide incorporation, and the transformation is monitored by in situ total scattering methods. The sulfided MOFs display enhanced catalytic activity in the selective hydrogenation of nitroarenes using molecular hydrogen. Density functional theory calculations indicate that sulfur incorporation promotes homolytic metal–ligand bond cleavage and facilitates H 2 activation. This work establishes an approach to construct MOFs featuring accessible metal–sulfide sites.

Catalyst synthesis↗
DOE OSTI2020

In search of molecular ions for optical cycling: a difficult road

Optical cycling, a continuous photon scattering off atoms or molecules, plays a central role in the quantum information science. While optical cycling has been experimentally achieved for many neutral species, few molecular ions have been investigated. We present a systematic theoretical search for diatomic molecular ions suitable for optical cycling using equation-of-motion coupled-cluster methods. Inspired by the electronic structure patterns of laser-cooled neutral molecules, we establish the design principles for molecular ions and explore various possible cationic molecular frameworks. The results show that finding a perfect molecular ion for optical cycling is challenging, yet possible. Among various possible diatomic molecules we suggest several candidates, which require further attention from both theory and experiment: YF + , SiO + , PN + , SiBr + , and BO + .

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

Velocity dispersion and dynamical masses for 388 galaxy clusters and groups

The second catalogue of Planck Sunyaev-Zeldovich (SZ) sources, hereafter PSZ2, represents the largest galaxy cluster sample selected by means of their SZ signature in a full-sky survey. For this work, using telescopes at the Canary Island observatories, we conducted the long-term observational program 128- MULTIPLE-16/15B (hereafter LP15), a large and complete optical follow-up campaign of all the unidentified PSZ2 sources in the northern sky, with declinations above –15° and no correspondence in the first Planck catalogue PSZ1. This paper is the third and last in the series of LP15 results, after Streblyanska et al. (2019, A&A, 628, A13) and Aguado-Barahona et al. (2019, A&A, 631, A148), and presents all the spectroscopic observations of the full program. We complement these LP15 spectroscopic results with Sloan Digital Sky Survey archival data and other observations from a previous program (ITP13-08), and present a catalogue of 388 clusters and groups of galaxies including estimates of their velocity dispersion. The majority of them (356) are optical counterparts of PSZ2 sources. A subset of 297 of those clusters are used to construct the M SZ – M dyn scaling relation based on the estimated SZ mass from Planck measurements and our dynamical mass estimates. We discuss and correct for different statistical and physical biases in the estimation of the masses, such as the Eddington bias when estimating M SZ and the aperture and the number of galaxies used to calculate M dyn . The SZ-to-dynamical mass ratio for those 297 PSZ2 clusters is (1 – B) = 0.80 ± 0.04 (stat) ± 0.05 (sys), with only marginal evidence for a possible mass dependence for this factor. Our value is consistent with previous results in the literature, but is associated with a significantly smaller uncertainty due to the use of the largest sample size for this type of study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A coupled cluster framework for electrons and phonons

Here, we describe a coupled cluster framework for coupled systems of electrons and harmonic phonons. Neutral and charged excitations are accessed via the equation-of-motion version of the theory. Benchmarks on the Hubbard–Holstein model allow us to assess the strengths and weaknesses of different coupled cluster approximations, which generally perform well for weak to moderate coupling. Finally, we report progress toward an implementation for ab initio calculations on solids and present some preliminary results on finite-size models of diamond with a linear electron–phonon coupling. We also report the implementation of electron–phonon coupling matrix elements from crystalline Gaussian type orbitals within the PySCF program package.

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

Rank-reduced coupled-cluster. III. Tensor hypercontraction of the doubles amplitudes

In this work, we develop a quartic-scaling implementation of coupled-cluster singles and doubles (CCSD) based on low-rank tensor hypercontraction (THC) factorizations of both the electron repulsion integrals (ERIs) and the doubles amplitudes. This extends our rank-reduced (RR) coupled-cluster method to incorporate higher-order tensor factorizations. The THC factorization of the doubles amplitudes accounts for most of the gain in computational efficiency as it is sufficient, in conjunction with a Cholesky decomposition of the ERIs, to reduce the computational complexity of most contributions to the CCSD amplitude equations. Further THC factorization of the ERIs reduces the complexity of certain terms arising from nested commutators between the doubles excitation operator and the two-electron operator. We implement this new algorithm using graphical processing units and demonstrate that it enables CCSD calculations for molecules with 250 atoms and 2500 basis functions using a single computer node. Furthermore, we show that the new method computes correlation energies with comparable accuracy to the underlying RR-CCSD method.

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

Transferability of data-driven, many-body models for CO 2 simulations in the vapor and liquid phases

Here, extending on the previous work by Riera et al. [J. Chem. Theory Comput. 16, 2246–2257 (2020)], we introduce a second generation family of data-driven many-body MB-nrg models for CO 2 and systematically assess how the strength and anisotropy of the CO 2 –CO 2 interactions affect the models’ ability to predict vapor, liquid, and vapor–liquid equilibrium properties. Building upon the many-body expansion formalism, we construct a series of MB-nrg models by fitting one-body and two-body reference energies calculated at the coupled cluster level of theory for large monomer and dimer training sets. Advancing from the first generation models, we employ the charge model 5 scheme to determine the atomic charges and systematically scale the two-body energies to obtain more accurate descriptions of vapor, liquid, and vapor–liquid equilibrium properties. Challenges in model construction arise due to the anisotropic nature and small magnitude of the interaction energies in CO 2 , calling for the necessity of highly accurate descriptions of the multidimensional energy landscape of liquid CO 2 . These findings emphasize the key role played by the training set quality in the development of transferable, data-driven models, which, accurately representing high-dimensional many-body effects, can enable predictive computer simulations of molecular fluids across the entire phase diagram.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗