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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 145 records · Page 8

Progressive evolutions of non-fused ring electron acceptors toward efficient organic solar cells with improved photocurrent and reduced energy loss

Resolving competitive counterbalance between high external quantum efficiency (EQE) response and low energy loss is critical for achieving efficient organic solar cells (OSCs), including those based on low-cost non-fused-ring electron acceptor (NFREA). In this work, we performed a comparable study by utilizing four NFREAs with progressive evolutions in molecular structures, energetic levels, spectral coverages, crystallinity, etc, to pair with polymer donor J52. By regulating the terminal and side chains of NFREAs, the enhanced intramolecular charge transfer (ICT) effect allows O-PC-EH possessing the broader spectral coverage for higher photocurrent, the reduced energetic offset enables O-PC-EH-based device owning higher luminescence property for lower energy loss, the strengthened crystallinity endows O-PC-EH-based blend better charge transport property for less charge recombination. With those comprehensive managements from molecule to blend properties, the J52:O-PC-EH-based OSCs achieved the best efficiency of 14.4% (certified: 14.1%) with benefits in all the three device parameters. Here, this work reveals the importance of fine-tuning molecular structures of NFREAs according to paired polymer donor for maximizing the device performances.

14 SOLAR ENERGY↗

Trace Compound Analysis in TATB by Liquid Chromatography coupled with Spectroscopic and Spectrometric Detection

Accurate quantitation of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) is important because of its strategic use as an energetic material. A purity determination is also needed for the proper assessment of performance. A fast and sensitive method has been developed to measure the purity of TATB in polymer-bonded materials. The target material is extracted with DMSO, and the extract is separated on a reversed-phase chromatography column. The column effluent is monitored by diode array detection (DAD) at 354 nm. The characteristic UV-Vis response and retention time identify the individual components when compared to pure compound standards. The chemical structures of compounds with no pure standards available have been determined by high-resolution mass spectrometry (MS) and MS/MS. The major component, TATB, along with 1-chloro-3,5-dinitro-2,4,6-triaminobenzene (T4A) and mono-benzofuroxan (FX1) were quantitated directly from pure compound standards. Several trace concentration components, mono-benzofurazan (F1), 1-bromo-3,5-dinitro-2,4,6-triaminobenzene (Br-T4A), 2,4,6-triamino-1-nitroso-3,5-dinitrobenzene (MN-TATB), 2,4,6-triamino-1-hydroxyl-3,5-dinitrobenzene (HO-TATB), and 2,4,6-triamino-1-nitrile-3,5-dinitrobenzene (Nitrile-TATB) were also detected and structures verified via MS/MS. Approximate concentrations were determined using calibrations from standards of similar structures. Additional trace components were also detected by MS. Contained herein are the results of analyses of TATB-based materials characterized for polymer-bonded formulations compared to different preparations of TATB. The accuracy, details, and process of developing this method are reported here.

36 MATERIALS SCIENCE↗

Data-driven design of novel halide perovskite alloys

The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring combinatorial chemical spaces. Here, in this work, we develop a framework powered by high-throughput computations and machine learning for the design and prediction of mixed cation halide perovskite alloys. In a chemical space of ABX 3 perovskites with a selected set of options for A, B, and X species, pseudo-cubic structures with B-site mixing are simulated using density functional theory (DFT) and several properties are computed, including stability, lattice constant, band gap, vacancy formation energy, refractive index, and optical absorption spectrum, using both semi-local and hybrid functionals. Neural networks (NN) are used to train predictive models for every property using tabulated elemental properties of A, B, and X site species as descriptors. Starting from a DFT dataset of 229 points, we use the trained NN models to predict the structural, energetic, electronic, and optical properties of an extensive dataset of 17955 compounds, and perform high-throughput screening in terms of stability, band gap, and defect tolerance, to obtain 392 promising compounds that are ranked as potential absorbers according to their photovoltaic figure of merit. Compositional trends in the screened set of attractive mixed cation halide perovskites are revealed and additional computations are performed on selected compounds. The data-driven design framework developed here is promising for designing novel mixed compositions and can be extended to a wider perovskite chemical space in terms of A, B, and X species, different kinds of mixing at the A, B, or X sites, non-cubic phases, and other properties of interest.

36 MATERIALS SCIENCE↗

A perspective on ordered vacancy compound and parent chalcopyrite thin film absorbers for photoelectrochemical water splitting

Chalcopyrites could fill the gap between the low-cost, poor-efficiency single junction metal oxide photoelectrochemical (PEC) water splitting cells and the high efficiency, yet costly III–V tandems. In this Perspective, we first review the key barriers that must be addressed by the community to enable economical chalcopyrite-based PEC water splitting. Then, we highlight how theoretical modeling can be used to identify promising ordered vacancy compound absorbers with improved energetics compared to their chalcopyrite parents. Finally, we describe how advanced spectroscopic analysis performed on chalcopyrite photocathodes after PEC testing uncovered a new passivation layer candidate for prolonged durability.

08 HYDROGEN↗

Reaction processes at step edges on S-decorated Cu(111) and Ag(111) surfaces: MD analysis utilizing machine learning derived potentials

We report a variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M–S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal–sulfur complexes, especially MS 2 ; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal–sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

THz Radiation Generation to Enable Internal Magnetic Field Measurement of Burning Plasmas (Final Scientific Report)

A one-year experimental program was performed using the Multi-TeraWatt (MTW) laser at the Laboratory for Laser Energetics (LLE) to investigate the efficiency and physical process of laser-driven—wire THz generation. This process was evaluated as a potential high-repetition-rate source of powerful THz pulses for use in THz pulsed polarimetry of a moderate-density magnetic-confinement fusion concept developed by TAE. The goal was to develop a source for short pulses in the THz regime (150 μm wavelength) containing 10’s of mJ. The campaign tested the impact of Cu wire diameter (25, 75, 160 μm), length (250 – 750 μm), and laser irradiation orientation on THz production efficiency in comparison to 20-μm thick Cu foils. Of these targets, the 160 µm diameter, 750 µm long wires with sharpened tips and irradiated at the base were found to produce the highest energy and shortest wavelength THz pulses, exceeding 2.5 Joule/sr and meeting the requirements for the polarimetry diagnostic. The brightest THz signal was radiated in the direction of the sharpened wire tip. A combination of two models – a traveling wave antenna combined with coherent transition radiation – describes the emission pattern, pulse energy, and spectrum observed in the experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Double-power-law Feature of Energetic Particles Accelerated at Coronal Shocks

Recent observations have shown that in many large solar energetic particle (SEP) events the event-integrated differential spectra resemble double power laws. We perform numerical modeling of particle acceleration at coronal shocks propagating through a streamer-like magnetic field by solving the Parker transport equation, including protons and heavier ions. We find that for all ion species the energy spectra integrated over the simulation domain can be described by a double power law, and the break energy depends on the ion charge-to-mass ratio as E B ~ (Q/A) α , with α varying from 0.16 to 1.2 by considering different turbulence spectral indices. We suggest that the double-power-law distribution may emerge as a result of the superposition of energetic particles from different source regions where the acceleration rates differ significantly due to particle diffusion. The diffusion and mixing of energetic particles could also provide an explanation for the increase of Fe/O at high energies as observed in some SEP events. Although further mixing processes may occur, our simulations indicate that either a power-law break or rollover can occur near the Sun and predict that the spectral forms vary significantly along the shock front, which may be examined by upcoming near-Sun SEP measurements from the Parker Solar Probe and Solar Orbiter.

79 ASTRONOMY AND ASTROPHYSICS↗

Molecular Structure and Electron Affinity of Metal-Solvent Complexes: Insights from Density Functional Theory Simulations

A molecular level understanding of the structure and energetics of the monovalent and divalent metal ion complexes is of great importance for development of next-generation batteries. Here, Density Functional Theory (DFT) simulations at the ωb97xD/6-31 + G(d,p) level of theory are performed to investigate the interaction of metal ions (Li + , Na + , K + , Mg 2+ , Ca 2+ , Zn 2+ ) with 26 organic solvent molecules. The reduction energetics (electron affinity and reduction potential) and structural responses of the solvent molecules and the molecular complexes are discussed. The DFT calculations are carried out to investigate the structure, energetics and electron affinities of chelated complexes of water (H 2 O), tetrahydrofuran (THF) and di-methoxy ethane (DME) solvent molecules. Additionally, ab initio dynamic simulations (AIMD) at 298 K using atom centered density matrix propagation (ADMP) formalism are performed to understand the spontaneous structure formation upon electron attachment of the metal ion-solvent complexes. The ADMP simulations indicate the decomposition of Mg + -(DME) 3 complex via cleavage of C–O bond of one of the three DME molecules indicating irreversible decomposition of DME in the presence of the Mg + radical. We believe that the data collected as part of this investigation serves as a library of fundamental knowledge towards a deeper understanding of the electrode-electrolyte interfacial reactions.

25 ENERGY STORAGE↗

Multi-messengers at ultra-high energies with the Pierre Auger Observatory

The Pierre Auger Observatory is an Ultra-High Energy Cosmic Ray (UHECR) detector which has studied cosmic particles with energies above and around 10 18 eV for more than 15 years. It has proved to be the most competitive instrument at these energies and has produced a wealth of valuable results, improving our understanding of UHECRs. A complete understanding of these highest energy particles is crucial to understand the extreme astrophysical events in which they are produced and accelerated, as well as their propagation to Earth. In the same range of energies, UHE photons and neutrinos are of paramount importance as, being electrically neutral, they point back to their origin while charged particles are deflected in the galactic and extragalactic magnetic fields. The flux of extragalactic photons, neutrinos, and cosmic rays are believed to be highly linked, by their origin and their interactions. Each messenger provides different information about the potential sources, and having detection means for all four messengers, including gravitational waves, allows us to shed light on energetic sources of astroparticles. The Pierre Auger Observatory benefits from a large exposure and a good angular resolution, and is efficient in detecting UHE photons and neutrinos. These performances make possible follow-up searches for events detected by gravitational waves, such as the binary mergers observed by the LIGO/Virgo detectors, or any other energetic sources of particles.

Binary black hole mergers↗

Energetics and Structure of Ag–Water Clusters Formed in Mordenite

Zeolite-supported Ag 0 clusters have broad applications from catalysis to medicine, necessitating a mechanistic understanding of the formation of Ag 0 clusters in situ. Density functional theory (DFT) simulations have been performed on silver, water, and silver–water clusters in silica mordenite (Si-MOR), to identify the role of the confinement on the structure and energetics of Ag 0 cluster formation. The most favorable binding energy in the 12-membered ring (MR) pore of the Si-MOR is a 10–15-atom Ag 0 cluster. Computational pair distribution function (PDF) data indicates that the Ag 0 and Ag 0 –H 2 O clusters formed in vacuum versus in Si-MOR exhibit structural differences. Additionally, when the Ag 0 cluster is confined, the density decreases and the surface area increases, hypothesized to be due to the limiting geometry of the 12-MR main channel. An energetic drive toward formation of larger Ag 0 clusters was also identified, with hydrated silver atoms generating higher energy structures. In conclusion, this work identifies mechanistic and structural insight into the role of nanoconfinement on formation of Ag 0 clusters in mordenite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Henkin-McGill critical temperature test for explosives revisited: An overview of historical and modern method development

Many overarching standards, regulations, or other requirements necessitate that the critical temperature (T crit ) of an energetic material be known or estimate prior to operations such as heating. However, they rarely, if ever, provide a specific method for doing so. While other methods exist to calculate T crit , such as the Frank-Kamenetskii equation, computer simulation, etc., these cannot be readily utilized for energetics that are physical mixtures (i.e. most pyrotechnics) or materials where detailed material properties required for such calculations are lacking. Here, in this study, a COTS (commercial off-the-shelf) SBAT (Simulated Bulk Auto-ignition Test) apparatus is modified to perform Henkin cookoff tests. This creates a simple, efficient, and cost-effective solution to estimate required T crit values for energetic materials. After a historical overview of the evolution of the Henkin test, several common energetic materials (PETN, RDX, etc.) for which T crit has been readily calculated, and historical data is available, were analyzed for comparison and verification purposes. This was followed by a variety of pyrotechnic mixtures and other materials to where calculation methods cannot be readily used. The modified apparatus, as well as an updated sample shell sealing method, produced results that aligned well with historical data. It also produced reasonable T crit estimates for those materials where the Frank-Kamenetskii equation cannot be applied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hybrid-gyrokinetic simulations of low- n toroidal Alfvén eigenmodes using gKPSP

Here, we report a benchmark study of toroidal Alfvén eigenmode (TAE) simulation using the hybrid-gyrokinetic code GyroKinetic Plasma Simulation Program (gKPSP). A simulation capability for energetic particles based on the gyrokinetic δf method has been newly implemented in the gKPSP code. Benchmark simulations have been performed in both circular and realistic tokamak geometries. Good agreement has been found with previously reported results, demonstrating the new capability of the gKPSP code. We have investigated the effects of the distribution function on TAE stability by examining both isotropic and anisotropic slowing-down distributions of energetic particles. The slowing-down distribution produces a higher linear growth rate than a Maxwellian distribution, while a growth rate scan with the anisotropy shows an opposite trend. This can be attributed to competition between Landau damping and the linear drive, which are correlated with the fraction of resonant passing particles and their distribution in phase space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sulfonate Group Improves the Solubility and Electrocatalytic Performance of Ru‐Based bda‐ and pda‐Type Water Oxidation Catalysts under Neutral Conditions

Four ruthenium water oxidation catalysts that bear carboxylate and sulfonate groups in the active site have been synthesized and analyzed for their catalytic activity. Here, the sulfonate‐containing catalysts show higher electrochemical activity in pH 7 phosphate buffer with 4 times larger catalytic current, improved durability with sacrificial oxidant, and increased solubility compared to similar species containing two carboxylate groups. Density functional theory calculations suggest that the sulfonate group provides a more favorable geometry for water nucleophilic attack, which is both the energetically most favorable mechanism calculated and the experimentally predicted mechanism under electrochemical conditions. Further experimental studies have been performed to show that under certain conditions catalysts can perform well electrochemically under pH conditions as low as 1.6 and that various structural components can greatly change solubility and catalytic operation.

14 SOLAR ENERGY↗

Molecular insights into the structure-property relationships of 3D printed polyamide reverse-osmosis membrane for desalination

3D-printing is an emerging method for manufacturing polyamide (PA) reserve osmosis (RO) membranes for water treatment and desalination, which can precisely control membrane structural properties, such as thickness, roughness, and resolution. However, the synthesis-structure (i.e., degree of cross-linking (DC), m-phenylenediamine/trimesoyl chloride (MPD/TMC) ratio, and membrane thickness) to property (permeability and water-salt selectivity) relationships for these membranes has not been well understood. At the same time, a microscopic understanding of the physical mechanism of water and salt transport is needed to guide the design of high-performance 3D-printed membranes and improve the printing efficiency. Furthermore, the atomic-scale transport features and energetics of water and salt ions are studied at high pressure for the 3D-printed PA RO membranes with the different DCs and MPD/TMC ratios through non-equilibrium molecular dynamics (NEMD) simulations. Factoring in membrane structure properties, rejection ratio of salt ions and pressure-dependent water flux, 3D-printed PA membranes having an MPD/TMC ratio of 3.0:2.0 and a DC between 80%~90% attains ideal performance: high water flux, high rejection of salt ions, and excellent structural integrity. Mechanistically, water permeability for highly cross-linked PA RO membranes depends on the temporary on-and-off channels that allow water molecules to jump from one cavity to another at high pressure. In addition, higher pressures cause rapid compaction of PA membranes’ free volume and membrane thickness. Membrane failure at high pressure is determined by the DC and MPD/TMC ratios-dependent compressive yield strength. In short, these findings provide physical insights for optimizing existing PA membranes and designing next-generation desalination membranes at the molecular level.

3D-printed PA RO membrane↗

A 3D porous honeycomb carbon as Na-ion battery anode material with high capacity, excellent rate performance, and robust stability

Motivated by the synthesis of three-dimensional (3D) honeycomb carbon structures and the subsequent theoretical prediction of an energetically more favorable hexagonal carbon phase composed of 28 carbon atoms in the unit cell (hC28) with ordered pores, excellent mechanical properties, and metallic feature, we explore its potential for a Na-ion battery (NIB) anode material. Using density functional theory based calculations, we find that hC28 is a promising candidate whose specific capacity of 717 mAh/g is almost three times larger than that of hard carbon (~250 mAh/g). In addition, migration barrier of Na ions along the honeycomb channel is only 0.08 eV and the volume change during the charging/discharging process is merely 2.30%, which are much less than those of other carbon-based NIB anode materials. The average voltage is also low (0.36 eV) which can provide high operating voltage when connected to the cathode. Finally, these encouraging results would pave the way towards the development of hC28 as NIB anode with high capacity, excellent rate performance, low open-circuit voltage, and long-term cycle life.

36 MATERIALS SCIENCE↗

Evolutionary inverse design of defects at graphene 2D lateral interfaces

Grain boundaries (GBs) in two-dimensional (2D) materials often have a profound impact on various material properties from mechanical to optical to electronic, yet predicting all possible GB formations is a challenge. Here, we introduce a workflow based on an evolutionary algorithm for exploring possible GBs formed at a lateral 2D interface. In a departure from conventional genetic algorithm based structure optimization methods, we perform genetic operations in the near interface region that allow us to be computationally efficient. We benchmark our method using graphene, which is a well-studied 2D material with a wide range of point defects. An empirical potential was used as the surrogate of the evolutionary search. More than 11.5 × 106 structures in total were evaluated for 128 GB orientations, and for each orientation, the ten best structures are recorded. A subset of low energy GBs predicted by empirical potential based search was relaxed by first-principles calculations and used to validate the energetic rank order. With the validated formation energy, we rank-ordered the best 128 GB structures and performed a detailed statistical analysis of primitive rings to find the correlation between the ring distribution and the formation energy. We found that for low energy GBs (below 0.5eV/Å), Stone–Wales defects will dominate, while structures with a higher energy (0.5–1.1eV/Å) show an increasing population of heptagons and nine-membered rings to form seven-nine defect pairs. For structures with energy higher than 1.1eV/Å, the percentage of octagons and nine-membered rings increases, which indicates that these two types of rings are not energetically favorable. Our proposed methodology is broadly applicable to explore defective low dimensional materials and represents a powerful tool that enables a systematic search of GBs of lateral interfaces for 2D materials.

Zhang, Jianan↗

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗

Measurement of the inclusive and differential $t\overline{t}γ$ cross sections in the single-lepton channel and EFT interpretation at $\sqrt{s}$ = 13 TeV

The production cross section of a top quark pair in association with a photon is measured in proton-proton collisions at a center-of-mass energy of 13 TeV. The data set, corresponding to an integrated luminosity of 137 fb -1 , was recorded by the CMS experiment during the 2016–2018 data taking of the LHC. The measurements are performed in a fiducial volume defined at the particle level. Events with an isolated, highly energetic lepton, at least three jets from the hadronization of quarks, among which at least one is b tagged, and one isolated photon are selected. The inclusive fiducial $t\overline{t}γ$ cross section, for a photon with transverse momentum greater than 20 GeV and pseudorapidity |η| < 1.4442, is measured to be 798 ± 7(stat) ± 48(syst) fb, in good agreement with the prediction from the standard model at next-to-leading order in quantum chromodynamics. The differential cross sections are also measured as a function of several kinematic observables and interpreted in the framework of the standard model effective field theory (EFT), leading to the most stringent direct limits to date on anomalous electromagnetic dipole moment interactions of the top quark and the photon.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗