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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25

Molecular dynamics force-field refinement against quasi-elastic neutron scattering data

Quasi-elastic neutron scattering (QENS) is one of the experimental techniques of choice for probing the dynamics at length and time scales that are also in the realm of full-atom molecular dynamics (MD) simulations. This overlap enables extension of current fitting methods that use time-independent equilibrium measurements to new methods fitting against dynamics data. We present an algorithm that fits simulation-derived incoherent dynamical structure factors against QENS data probing the diffusive dynamics of the system. We showcase the difficulties inherent to this type of fitting problem, namely, the disparity between simulation and experiment environment, as well as limitations in the simulation due to incomplete sampling of phase space. We discuss a methodology to overcome these difficulties and apply it to a set of full-atom MD simulations for the purpose of refining the force-field parameter governing the activation energy of methyl rotation in the octa-methyl polyhedral oligomeric silsesquioxane molecule. Our optimal simulated activation energy agrees with the experimentally derived value up to a 5% difference, well within experimental error. We believe the method will find applicability to other types of diffusive motions and other representation of the systems such as coarse-grain models where empirical fitting is essential. In addition, the refinement method can be extended to the coherent dynamic structure factor with no additional effort.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗

Quantum Electrodynamics Coupled-Cluster at Scale: High-Performance Implementation for Complex Systems

Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. Furthermore, we discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.

Basis sets↗

Local Pair Natural Orbital-Based Coupled-Cluster Theory through Full Quadruples (DLPNO–CCSDTQ)

In this work, we implement a local pair natural orbitalbased coupled-cluster method through the full treatment of quadruple excitations (CCSDTQ). The domain-based local pair natural orbital (DLPNO) approach, which has successfully been applied to lower levels of coupled-cluster theory, is utilized in our algorithm, and thus our algorithm is called DLPNO-CCSDTQ. For simplicity in the working equations and in the implementation, we t 1 -dress the twoelectron integrals as well as Fock matrix elements. Our method can recover CCSDTQ-CCSDT and CCSDTQ-CCSDT(Q) energy differences on the order of 0.01−0.05 kcal mol −1 , even at a loose quadruples natural orbital (QNO) occupation number cutoff of 3.33 × 10 −6 . To highlight the capabilities of our code and its potential future applications, we showcase computations that would be intractable with canonical CCSDTQ, such as the benzene dimer, (H 2 O) 17 , and adamantane. With sufficient computing resources, computations up to 15 heavy atoms (40 atoms overall) may be feasible for fully bonded 3D systems.

Cluster chemistry↗

Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms

StochasticGW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. StochasticGW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. Here, we introduce a new implementation, StochasticGW-GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (Si x H y ) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.

Thomas, Phillip S. [Lawrence Berkeley National Lab↗

Discovery of an Acrylic Acid Based Tetrahydroisoquinoline as an Orally Bioavailable Selective Estrogen Receptor Degrader for ERα+ Breast Cancer

Tetrahydroisoquinoline 40 has been identified as a potent ERα antagonist and selective estrogen receptor degrader (SERD), exhibiting good oral bioavailability, antitumor efficacy, and SERD activity in vivo. We outline the discovery and chemical optimization of the THIQ scaffold leading to THIQ 40 and showcase the racemization of the scaffold, pharmacokinetic studies in preclinical species, and the in vivo efficacy of THIQ 40 in a MCF-7 human breast cancer xenograft model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Electronic Structure of [B 10 H 10 ] 2– Dianion Encapsulated by an Octamethylcalix[4]pyrrole Molecule

Despite being an important closo-borate in the condensed phase boron chemistry, isolated B 10 H 10 2- is electronically unstable and has never been detected in the gas phase. Herein, we report a successful capture of this fleeting species through binding with an octamethylcalix[4]pyrrole (omC4P) molecule to form a stable gaseous omC4P·[B 10 H 10 ] 2- complex and its characterizations utilizing negative ion photoelectron spectroscopy (NIPES). The recorded NIPE spectrum, contributed from both omC4P and [B 10 H 10 ] 2- , is deconvoluted by subtracting the omC4P contribution to yield a [B 10 H 10 ] 2- spectrum. The obtained [B 10 H 10 ] 2- spectrum consists of four major bands spanning electron binding energy (EBE) range from 1 to 5 eV with the EBE gaps matching excellently with the energy intervals of computed highly lying occupied molecular orbitals of the B 10 H 10 2- dianion. Finally, this study showcases a generic method to utilize omC4P to capture unstable multiply charged anions in the gas phase for experimental determination of their electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catalight─An Open-Source Automated Photocatalytic Reactor Package Illustrated through Plasmonic Acetylene Hydrogenation

An open-source and modular Python package, Catalight, is developed and demonstrated to automate (photo)catalysis measurements. (Photo)catalysis experiments require studying several parameters to evaluate performance, including the temperature, gas flow rate and composition, illumination power, and spectral profile. Catalight orchestrates measurements over this complicated parameter space and systematically stores, analyzes, and visualizes the results. To showcase the capabilities of Catalight, we perform an automated apparent activation barrier measurement of acetylene hydrogenation over a plasmonic AuPd catalyst on an Al 2 O 3 support, simultaneously varying laser power, wavelength, and temperature in a multiday experiment controlled by a simple Python script. Our chemical results unexpectedly show an increased activation barrier upon light excitation, contrary to previous findings for other plasmonic reactions and catalysts. We show that the reaction rate order with respect to both acetylene and hydrogen remains unchanged upon illumination, suggesting that molecular surface coverage is not changed by light. By analyzing the inhomogeneity of the laser-induced heating, we attribute these results to a partial photothermal effect combined with a photochemical/hot electron-driven mechanism. In conclusion, our findings highlight the capabilities of a new experiment automation tool; explore the photocatalytic mechanism for an industrially relevant reaction; and identify systematic sources of error in canonical photocatalysis experimental procedures.

Catalysts↗

Chemist: A Domain-Specific Language by Chemists for Chemists

Managing the complexity of quantum chemistry (QC) software is key to ensuring it remains accessible, maintainable, and reusable. Noticeably missing from the QC ecosystem are modules targeting bottleneck routines. Here we argue that this is likely due to the difficulty in defining interfaces for such modules. To that end, we introduce the open-source, publicly available Chemist library https://github.com/NWChemEx/Chemist. Chemist is a domain-specific language targeting the QC domain. Chemist has been developed focusing on performance and user-friendliness. Using Chemist, QC tasks are defined using familiar domain concepts such as molecules, wave functions, and operators. The domain objects are hierarchical to ensure a systematic encapsulation of information. Key features of Chemist include: extensibility, the ability to alias existing data, and the ability to succinctly define many common QC tasks. The usefulness of Chemist is demonstrated by discussing the interface of NWChemEx’s Fock build module and by showcasing a proof-of-concept self-consistent field algorithm containing uncertainty propagation.

Algorithms↗

Ultraviolet Superradiance from Mega-Networks of Tryptophan in Biological Architectures

Networks of tryptophan (Trp)–an aromatic amino acid with strong fluorescence response–are ubiquitous in biological systems, forming diverse architectures in transmembrane proteins, cytoskeletal filaments, subneuronal elements, photoreceptor complexes, virion capsids, and other cellular structures. We analyze the cooperative effects induced by ultraviolet (UV) excitation of several biologically relevant Trp mega-networks, thus giving insights into novel mechanisms for cellular signaling and control. Our theoretical analysis in the single-excitation manifold predicts the formation of strongly superradiant states due to collective interactions among organized arrangements of up to >10 5 Trp UV-excited transition dipoles in microtubule architectures, which leads to an enhancement of the fluorescence quantum yield (QY) that is confirmed by our experiments. We demonstrate the observed consequences of this superradiant behavior in the fluorescence QY for hierarchically organized tubulin structures, which increases in different geometric regimes at thermal equilibrium before saturation, highlighting the effect’s persistence in the presence of disorder. Our work thus showcases the many orders of magnitude across which the brightest (hundreds of femtoseconds) and darkest (tens of seconds) states can coexist in these Trp lattices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of X-rays on Perovskite Solar Cells

Synchrotron micro- and nanoprobe beamlines have demonstrated great potential to advance photovoltaic devices. Most importantly, their small X-ray spot size has enabled the direct correlation of electrical performance with elemental composition at subgrain resolution for a variety of polycrystalline solar cells. Whereas the bulk of most inorganic semiconductors is stable under the high X-ray flux of focused X-ray beams, semiconductors with organic components are prone to a variety of degradation mechanisms. This is particularly critical to evaluate for the emerging organometal halide perovskite solar cells. In this study, we investigate the effects of hard X-rays on the nanoscale performance and elemental distribution of these solar cells. We show that their composition does not change during common operando and in situ measurements at synchrotron nanoprobes. However, we found a significant X-ray-induced electronic degradation of solar cells with methylammonium lead iodide absorbers. Time- and dose-dependent measurements unveiled two characteristic degradation time constants on the order of 12 and 200 s that are independent of the X-ray flux. On the basis of heat and dose simulations, we attribute the fast decay to the dose-driven creation of recombination centers, while the slow decay is compatible with the observation of compositional changes. Finally, we detail how degradation-induced measurement artifacts can be outrun and showcase the high correlation of the X-ray-beam-induced current with the iodine and lead distribution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Electrolyte Influence on CO 2 Reduction in Aprotic Solvents

Selective CO 2 capture and electrochemical conversion are important tools in the fight against climate change. Industrially, CO 2 is captured using a variety of aprotic solvents due to their high CO 2 solubility. However, most research efforts on electrochemical CO 2 conversion use aqueous media and are plagued by competing hydrogen evolution reaction (HER) from water breakdown. Fortunately, aprotic solvents can circumvent HER, making it important to develop strategies that enable integrated CO 2 capture and conversion. However, the influence of ion solvation and solvent selection within nonaqueous electrolytes for efficient and selective CO 2 reduction is unclear. In this work, we show that the bulk solvation behavior within the nonaqueous electrolyte can control the CO2 reduction reaction and product distribution occurring at the catalyst-electrolyte interface. We study different tetrabutylammonium (TBA) salts in two electrolyte systems with glyme ethers (e.g., 1,2 dimethoxyethane or DME) and dimethyl sulfoxide (DMSO) as a low and high dielectric constant medium, respectively. Using spectroscopic tools, we quantify the fraction of ion pairs that forms within the electrolyte. Also, we show how ion pair formation is prevalent in DME and is dependent on the anion type. More importantly, we show that as ion pair formation decreases within the electrolyte, CO 2 current densities increase, and a higher CO Faradaic efficiency is observed at low overpotentials. Meanwhile, in an electrolyte medium where the ion pair fraction does not change with the anion type (such as in DMSO), a smaller influence of solvation is observed on CO 2 current densities and product distribution. By directly coupling bulk solvation to interfacial reactions and product distribution, we showcase the importance and utility of controlling the reaction microenvironment in tuning the electrocatalytic reaction pathways. Insights gained from this work will enable novel electrolyte designs for efficient and selective CO 2 conversion to desired fuels and chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Engineering of Copper Catalyst through CO* Adsorbate

The electrochemical reduction of CO 2 with Cu-based catalysts depends intimately on the instantaneous local chemical environment of the catalyst-electrolyte interface. This microenvironment fluctuates according to the concentration of surface-adsorbed competing reaction intermediates and the applied electrode potential. In practice, disentangling these factors is exceedingly challenging, yet they critically determine the electrocatalyst efficiency and selectivity. Using grand canonical quantum-classical hybrid calculations, we quantify the complex interdependence between electrode potential, CO* coverage, and the interfacial field strength. Here we show that the often overlooked CO* coverage effect in fact strongly influences the field strength, with a magnitude change exceeding 1V/Å at certain potentials; among other effects, this change should lower the CO* dimerization barrier that dictates selectivity toward multi-carbon products. Beyond showcasing the importance of surface coverage for CO2 reduction, our results highlight the power of surface additives to modulate interfacial fields toward tailored electrochemical pathways.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Ab Initio Molecular Dynamics Spectra for Characterization of Hydrated Al 2 O 3 Supported MoO x

The structure of supported MoO x /Al 2 O 3 catalysts is investigated using ab initio molecular dynamics (AIMD) and density-functional theory (DFT). Phase diagrams were computed to understand the hydroxylation coverage as a function of the temperature, H 2 O partial pressure, and MoO x loading. We relate the shifts in experimental Raman vibrational frequencies under hydrated conditions to hydrogen bonding interactions and the MoO x anchoring location. We showcase that the use of AIMD as a benchmark for DFT can provide insight into how, under certain hydrated conditions, DFT excels as an inexpensive method for computing vibrational frequencies, while, under dehydrated conditions, it is susceptible to the largest errors. Additionally, to facilitate the analysis of the hydroxyl region of experimental infrared spectra, we compute the power spectra of individual hydroxyls and see a strong relationship between OH stretching frequencies and the surrounding coordination environment, which are also impacted by anchored MoO x . Here, we compare computational and experimental IR and Raman spectra of catalysts synthesized herein under the same conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Density Functional Tight-Binding Enables Tractable Studies of Quantum Plasmonics

Routine investigations of plasmonic phenomena at the quantum level present a formidable computational challenge due to the large system sizes and ultrafast time scales involved. This Feature Article highlights the use of density functional tight-binding (DFTB), particularly its real-time time-dependent formulation (RT-TDDFTB), as a tractable approach to study plasmonic nanostructures from a quantum mechanical purview. We begin by outlining the theoretical framework and limitations of DFTB, emphasizing its efficiency in modeling systems with thousands of atoms over picosecond time scales. Applications of RT-TDDFTB are then explored in the context of optical absorption, nonlinear harmonic generation, and plasmon-mediated photocatalysis. We demonstrate how DFTB can reconcile classical and quantum descriptions of plasmonic behavior, capturing key phenomena such as size-dependent plasmon shifts and plasmon coupling in nanoparticle assemblies. Lastly, we showcase DFTB’s ability to model hot carrier generation and reaction dynamics in plasmon-driven H2 dissociation, underscoring its potential to model photocatalytic processes. Collectively, these studies establish DFTB as a powerful, yet computationally efficient tool to probe the emergent physics of materials at the limits of space and time.

Electrical energy↗

Formulation of Multicomponent Lattice Gas Model Cluster Expansions Parameterized on Ab Initio Data: An Introduction to the Ab Initio Mean-Field Augmented Lattice Gas Modeling Code

A formalism is presented for the construction of multicomponent lattice gas models parameterized with ab initio (typically density functional theory) data. The leave-multiple-out and the leave-one-out cross validation score are showcased, and practical algorithms are developed and implemented in a new code called the Ab initio Mean-field Augmented Lattice Gas Modeling (AMALGM) code. Here, the functionality of these algorithms is demonstrated with a fully worked out example using the O/Fe(100) system. AMALGM and the formalism on which it is based are envisioned as a surface-oriented lattice gas alternative to other cluster expansion codes that are typically geared toward bulk systems whose lateral interactions between components are parameterized using an Ising model. While the formalism is created within the context of surfaces, it is equally applicable to bulk materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cryogenic “Iodide-Tagging” Photoelectron Spectroscopy: A Sensitive Probe for Specific Binding Sites of Amino Acids

This work showcases cryogenic and temperature-dependent “iodide-tagging” photoelectron spectroscopy to probe specific binding sites of amino acids using the glycine-iodide complex (Gly?I-) as a case study. Multiple Gly?I- isomers were generated from ambient electrospray ionization and kinetically isolated in a cryogenic ion trap. These structures were characterized with temperature-dependent “iodide-tagging” negative ion photoelectron spectroscopy (NIPES) where iodide was used as the “messenger” to interpret electronic energetics and structural information of various Gly?I- isomers. Accompanied by theoretical computations and Franck-Condon simulations, a total of five cluster structures have been identified along with their various binding motifs. This work demonstrates that “iodide-tagging” NIPES is a powerful general means for probing specific binding interactions in biological molecules of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗