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At least 919 records · Page 51

Machine-learning-aided density functional theory calculations of stacking fault energies in steel

A combined large-scale first principles approach with machine learning and materials informatics is proposed to quickly sweep the chemistry-composition space of advanced high strength steels (AHSS). AHSS are composed of iron and key alloying elements such as aluminum and manganese. A systematic exploration of the distribution of aluminum and manganese atoms in iron is used to investigate low stacking fault energies configurations using first principles calculations. To overcome the computational cost of exploring the composition space, this process is sped up using an automated machine learning tool: DeepHyper. Here our results predict that it is energetically favorable for Al to stay away from a stacking fault, but Mn atoms do not affect the stacking fault energy and can stay in the vicinity of the fault. The distribution of Al and Mn atoms in systems containing stacking faults and the effects of their interactions on the equilibrium distribution are systematically analyzed.

36 MATERIALS SCIENCE↗

Understanding and Overcoming Water-induced Interfacial Degradation in Si Modules (Final Technical Report)

Moisture ingress is an established issue for photovoltaic module durability. Durability studies probing moisture effects typically evaluate performance losses at the module level, attributing global power losses to the overall humidity condition of the test environment while leaving local module behavior unknown. This project successfully develops an in situ short-wave infrared probe of moisture content in PV modules with demonstrated detection limits better than 100 ppm in EVA-encapsulated Al-BSF and PERC architectures (66 µg/cm3) and applicability across the range of terrestrial conditions. Combining this optical moisture quantification method (water reflectometry detection, WaRD) with peel testing of interfaces, biased photoluminescence imaging of performance, and first principles computation, we correlate module moisture content and cell performance over the course of accelerated damp heat tests. By performing multi-level humidity and thermal accelerated testing over thousands of hours (0, 65 and 85% RH and 25, 65, and 85°C), we are able to attribute effects of individual environmental stresses and the dependence on module architecture. Using first-principles computational chemistry, we find that the decomposition of EVA to acetic acid (Norrish II) is thermodynamically preferred over a pathway to acetaldehyde (Norrish I), elucidating the underlying chemistry of encapsulant degradation. We also find it is likely that water segregates to the stable interfaces of the cell, especially the SiNx/EVA interface. We find that moisture is strongly correlated with reduction in adhesion at the interfaces of the cells, particularly at Ag fingers. We show uniquely that the peel strength required to delaminate the encapsulant from the front of the cell depends not only on the exposure to a high heat and humid environment, but also to the moisture content during the mechanical testing, indicating an important interaction between when mechanical stresses are faced in terms of the moisture content of the module and its durability. We find that the background sheet resistance (that is, the sheet resistance rise not attributable to finger interruptions or cracks) is substantially higher in the backsheet mini-modules vs glass-glass packages when humidity and temperature are faced. This increase in power loss due to the background resistance increase over time in damp heat in glass-backsheet modules resulted in ~3-4% larger decrease in relative PCE compared to glass-glass modules. In glass-backsheet modules, the effect of the moisture dose alone is comparable or greater than that of the combined temperature and water term, suggesting that glass-backsheet modules are overall more susceptible to moisture induced performance loss. Finally, we show that thin film PV modules are amenable to WaRD measurement, based on the ability to detect moisture in POE encapsulants or in the cell stack itself. The ease of WaRD measurement and its few requirements on the bill of materials should enable broad applicability of this technique for studying the effects of moisture in PV.

14 SOLAR ENERGY↗

Electronic heat generation in semiconductors: Non-equilibrium excitation and evolution of zone-edge phonons via electron–phonon scattering in photo-excited germanium

We investigate experimentally and using first-principles theory the generation of phonons and the relaxation of carriers on picosecond timescales across the Brillouin zone of photo-excited Ge by inter-valley electron–phonon scattering. The phonons generated are typical of those generated in semiconductor devices, contributing to the accumulation of heat within the material. We simulate the time-evolution of phonon populations, based on first-principles band structure and electron–phonon and phonon–phonon matrix elements, and compare them to data from time-resolved x-ray diffuse scattering experiments, performed at the Linac Coherent Light Source x-ray free-electron laser facility, following photo-excitation by a 50 fs near-infrared optical pulse. We show that the intensity of the non-thermal x-ray diffuse scattering signal, which is observed to grow substantially near the L-point of the Brillouin zone over 3–5 ps, is due to phonons generated by scattering of carriers between the Δ and L valleys. These phonons have low group velocities, resulting in a heat bottleneck. With the inclusion of phonon decay through 3-phonon processes, the simulations also account for other non-thermal features observed in the x-ray diffuse scattering intensity, which are due to anharmonic phonon–phonon scattering of the phonons initially generated by electron–phonon scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact of Irradiation-induced Lattice Defects and Dopants on Thermal Transport in Oxide Nuclear Fuels

Advanced nuclear reactor concepts aim to use fuels that must withstand unprecedented temperature and radiation extremes. In these fuels, thermal energy transport under irradiation is directly related to fuel longevity, reactor safety, and is arguably one of the most important performance metrics. Here we provide a comprehensive, first-principles-informed treatment of phonon mediated thermal transport in a defect-bearing actinide oxide with direct comparison to experimental measurements. Pristine and proton irradiated thorium dioxide was chosen as a model system to treat the complexity of thermal transport in the presence of lattice defects. A thermal transport model is implemented using the linearized Boltzmann transport equation (LBTE) with input from first principles calculations and defect evolution models. The output of the LBTE is compared directly to mesoscopic measurements of thermal conductivity on length scales commensurate with defect accumulation. Parametric measurements of conductivity with irradiation dose and temperature reveal a monotonic decrease in conductivity with irradiation dose, in the range of 0.001 dpa to 0.1 dpa. Besides radiation-induced defects, doping the thorium dioxide crystal with small quantities of uranium atoms also results in a drastic reduction in thermal conductivity. Temperature-dependent measurements of thermal conductivity in uranium-doped thorium dioxide single crystals suggests a resonant scattering mechanism is responsible for the observed reduction. This comprehensive, atomistic- to meso-scale treatment provides the necessary basis to investigate thermal transport under irradiation in more complex systems that exhibit strong electron correlation. This is a poster presentation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Defect-induced phonon-resonant scattering and its influence on thermal transport of irradiated thorium-dioxide

Thermal transport in proton irradiated thorium-dioxide (ThO 2 ) is investigated. Using a combination of experiments and first-principles computational framework, the role of lattice defects on thermal conductivity is analyzed. A resonant-phonon scattering mechanism beyond the traditionally considered Rayleigh scattering is found to significantly influence low-temperature thermal transport in the presence of irradiation-induced point defects. The existence of localized phonon modes associated with irradiation-induced defects is suggested by the inability of the first-principles based thermal conductivity model—which considers only three-phonon interactions and phonon-defects scattering using the Tamura formalism—to predict the experimental results, unless a resonant scattering mechanism is included. The emergence of additional peaks in the Raman spectra in the proximity of phonon-resonant frequency provides further evidence for the existence of localized modes. Coupled with a microstructure evolution model, this analysis enables more accurate analysis for contrasting the contributions of different phonon scattering mechanisms across all irradiation doses and temperatures.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multipole-based Cable Braid Magnetic Penetration Model for Conducting Wires

In this report, we investigate the effects of conductor losses in a multipole-based cable braid magnetic penetration model. Our multipole model uses a mesh of the actual cable geometry, which enables us to model more complicated structures. After summarizing the first principles model formulation, we consider a one-dimensional array of wires, for which an analytical solution is known in the lossless case. We extend this solution to the lossy case by using a complex-valued radius. We also model this structure analytically using a conformal-mapping solution. We then compare both the self-impedance and the transfer impedance results from our first principles cable braid electromagnetic penetration model to those obtained using the analytical solutions. An analysis for various frequencies (and skin depths) usually encountered in cable modeling is reported. These results are found in good agreement up to a radius to half spacing ratio of about 0.7, demonstrating a robustness needed for many commercial and non-commercial cables.

36 MATERIALS SCIENCE↗

Thermoelectric power generation in the core of a nuclear reactor

Thermoelectric energy converters offer a promising solution to generate electrical power using heat in the nuclear reactor core. Despite significant improvements in thermoelectric efficiency of nanostructured materials, the performance of these advanced materials has yet to be demonstrated in the harsh radiation environment of a reactor core. Herein, we demonstrate a thermoelectric generator (TEG) made from nanostructured bulk half-Heusler (HH) materials generating stable electrical power density > 1140 W/m 2 after 30 days in the MIT Nuclear Research Reactor under an unprecedented fast-neutron (>1 MeV) fluence of 1.5 × 10 20 n/cm 2 . Despite an initial degradation due to irradiation damage when operating under relatively low temperatures, our TEG showed a 20-fold increase in power output when operating under high temperature due to in-situ annealing and resulting thermoelectric property recovery. First-principles modeling indicates that a chemically disordered metallic phase was formed under irradiation at lower temperatures, resulting in a drastic degradation in thermoelectric properties, while at sufficiently high temperatures the system returned to the initial chemically ordered HH phase and the thermoelectric properties recovered. Transmission electron microscopy and electron diffraction demonstrated that the chemically disordered phase was formed upon ion irradiation, confirming the prediction from first-principles simulations. Furthermore, the results suggest that with proper control over the TEG operating temperatures, the nanostructured bulk TEGs could produce stable electrical power and operate indefinitely in the core of a nuclear reactor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine-learning interatomic potentials for interfaces in all-solid-state batteries: Perspectives on training data, model selection, and validation

Interfaces play a pivotal role in dictating the performance and reliability of all-solid-state batteries (ASSBs), where complex electro-chemo-mechanical phenomena at grain boundaries (GBs) and interfaces can lead to degradation and failure. Traditional atomistic simulation methods, such as first-principles calculations and classical molecular dynamics, face limitations in modeling these interfaces due to either high computational cost or insufficient transferability to the diverse atomic environments evolving at interfaces. Machine-learning interatomic potentials (MLIPs) have emerged as a transformative approach, enabling large-scale, high-accuracy simulations of disordered and chemically complex systems by leveraging the predictability of machine learning models trained on first-principles data. Recent applications of MLIPs have demonstrated their ability to capture intricate behaviors at ASSB interfaces, including ion transport, interfacial evolution, and degradation mechanisms, with accuracy and efficiency unattainable by conventional methods. This prospective paper presents comprehensive analysis and practical guidance for MLIP development for GBs and interfaces in ASSBs, with a focus on three key pillars: data generation, model selection, and validation. Here, we review the current state of MLIP applications for GBs and interfaces in both general and ASSB-specific materials, highlighting best practices and challenges in constructing diverse and representative datasets, choosing appropriate machine learning architectures, and rigorously validating model performance. We also discuss emerging strategies and opportunities for improved reliability and efficiency of MLIPs to simulate realistic interfaces in ASSBs.

Energy - Storage↗

Deep level transient spectroscopy and photoluminescence studies of hole and electron traps in ZnSnP 2 bulk crystals

ZnSnP 2 , an emerging inorganic material for solar cells, was characterized by deep level transient spectroscopy (DLTS) and photoluminescence (PL). Acceptor- and donor-like traps with shallow energy levels were detected by DLTS analysis. The previous study based on first-principle calculation also suggested such traps were due to antisite defects of Zn and Sn. PL measurements also revealed sub-gap transitions related to these trap levels. Furthermore, DLTS found a trap with a deep level in ZnSnP 2 . A short lifetime of minority carrier in previous work might be due to such trap, coming from phosphorus vacancies and/or zinc interstitials suggested by the first-principle study.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Learning dynamical systems from data: An introduction to physics-guided deep learning

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive numerical integration, requiring significant computational resources and domain expertise. While deep learning (DL) provides efficient alternatives for modeling complex dynamics, they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret. Physics-guided DL aims to integrate first-principled physical knowledge into data-driven methods. It has the best of both worlds and is well equipped to better solve scientific problems. Recently, this field has gained great progress and has drawn considerable interest across discipline Here, we introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems. We describe the learning pipeline and categorize state-of-the-art methods under this framework. We also offer our perspectives on the open challenges and emerging opportunities.

97 MATHEMATICS AND COMPUTING↗

Revealing a 3D Fermi Surface Pocket and Electron-Hole Tunneling in UTe 2 with Quantum Oscillations

Spin triplet superconductor UTe 2 is widely believed to host a quasi-two-dimensional Fermi surface, revealed by first-principles calculations, photoemission and quantum oscillation measurements. An outstanding question still remains as to the existence of a three-dimensional Fermi surface pocket, which is crucial for our understanding of the exotic superconducting and topological properties of UTe 2 . This 3D Fermi surface pocket appears in various theoretical models with different physics origins, but has not been unambiguously detected in experiment. Here, in this study, for the first time we provide concrete evidence for a relatively isotropic, small Fermi surface pocket of UTe 2 via quantum oscillation measurements. In addition, we observed high frequency quantum oscillations corresponding to electron-hole tunneling between adjacent electron and hole pockets. The coexistence of 2D and 3D Fermi surface pockets, as well as the breakdown orbits, provides a test bed for theoretical models and aid the realization of a unified understanding of superconducting state of UTe 2 from the first-principles approach.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Sustainable Aviation Fuels from 30,000 feet – Scoping Report

A literature review, first principles analysis, and mapping of the airline-fuel infrastructure were performed to reassess the potential for various means of realizing a sustainable aviation sector. The literature review found a plethora of technical methods to make the airline industry net-zero CO 2 but limited work on the emergent barriers to sustainable aviation implementation such as land use, repurposing of fuel refining assets, and airline cost structures. First principles analyses of the energy, land, and costs of three broad net-zero strategies were performed to determine if sustainable aviation is feasible even in the most optimistic scenarios. Those methods were biomass-derived sustainable aviation fuel (SAF), fuel produced from CO 2 captured from the air and H 2 produced from water electrolysis (air-to-fuel: ATF), and offsetting fossil-derived Jet Fuel with carbon dioxide removal from the atmosphere (direct air capture and storage: DACS). Offsetting CO 2 emissions from using fossil Jet Fuel with DACS was found to consume the least energy, require the smallest quantity of land, and be the cheapest option. Replacing Jet Fuel with SAF was found to be only slightly more expensive than DACS but require substantially more land. ATF was found to be the most expensive and energy intensive option, though it did spare land relative to SAF. We found that calls to utilize waste biomass are well-founded, but wastes alone cannot cover the needs of the global airline industry. This means additional land will need to be allocated for biomass cultivation if SAF becomes the primary pathway to sustainable aviation. While differences were found in the performance of different types of biomass, those differences were small relative to differences with ATF and DACS. An analysis of the pricing structure of the airline industry suggests that some of the cost advantage of DACS may be erased by consumer sentiment which could explain why, to-date, the airline industry is focused primarily on SAF and to a lesser extent ATF. Further work is required to estimate the transportation, capital cost, and financing cost implications of greenfield and brownfield sites for SAF, DACS, and ATF. In the final report, we will analyze the potential to retrofit corn ethanol facilities to operate the ethanol-to-jet fuel process in response to decreasing gasoline demand as the electrification of road transport progresses. We will also construct a prioritization of land use to determine whether each net-zero CO 2 aviation pathway can make claim to the land required by their technology.

09 BIOMASS FUELS↗

Gluon distributions and their applications to Ioffe-time distributions

We investigate unpolarized and polarized gluon distributions and their applications to the Ioffe-time distributions, which are related to lattice QCD calculations of parton distribution functions. Guided by the counting rules based on the perturbative QCD at large momentum fraction x and the color coherence of gluon couplings at small x, we parametrize gluon distributions in the helicity basis. By fitting the unpolarized gluon distribution, the inferred polarized gluon distribution from our parametrization agrees with the one from global analysis. A simultaneous fit to both unpolarized and polarized gluon distributions is also performed to explore the model uncertainty. The agreement with the global analysis supports the (1 - x) power suppression of the helicity-antialigned distribution relative to the helicity-aligned distribution. The corresponding Ioffe-time distributions and their asymptotic expansions are calculated from the gluon distributions. Our results of the Ioffe-time distributions can provide guidance to the extrapolation of lattice QCD data to the region lacking precise gluonic matrix elements. Therefore, they can help regulate the ill-posed inverse problem associated with extracting the gluon distributions from discrete data from first-principle calculations, which are available in a limited range of the nucleon momentum and the spatial separation between the gluonic currents. Given various limitations in obtaining lattice QCD data at large Ioffe time, phenomenological approaches can provide important complementary information to extract the gluon distributions in the entire momentum fraction region, especially at small x. The possibility of investigating higher-twist effects and other systematic uncertainties in the contemporary first-principle calculations of parton distributions from phenomenologically well-determined Ioffe-time distributions in the large Ioffe-time region is also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Machine learning the metastable phase diagram of covalently bonded carbon

Abstract Conventional phase diagram generation involves experimentation to provide an initial estimate of the set of thermodynamically accessible phases and their boundaries, followed by use of phenomenological models to interpolate between the available experimental data points and extrapolate to experimentally inaccessible regions. Such an approach, combined with high throughput first-principles calculations and data-mining techniques, has led to exhaustive thermodynamic databases (e.g. compatible with the CALPHAD method), albeit focused on the reduced set of phases observed at distinct thermodynamic equilibria. In contrast, materials during their synthesis, operation, or processing, may not reach their thermodynamic equilibrium state but, instead, remain trapped in a local (metastable) free energy minimum, which may exhibit desirable properties. Here, we introduce an automated workflow that integrates first-principles physics and atomistic simulations with machine learning (ML), and high-performance computing to allow rapid exploration of the metastable phases to construct “metastable” phase diagrams for materials far-from-equilibrium. Using carbon as a prototypical system, we demonstrate automated metastable phase diagram construction to map hundreds of metastable states ranging from near equilibrium to far-from-equilibrium (400 meV/atom). We incorporate the free energy calculations into a neural-network-based learning of the equations of state that allows for efficient construction of metastable phase diagrams. We use the metastable phase diagram and identify domains of relative stability and synthesizability of metastable materials. High temperature high pressure experiments using a diamond anvil cell on graphite sample coupled with high-resolution transmission electron microscopy (HRTEM) confirm our metastable phase predictions. In particular, we identify the previously ambiguous structure of n -diamond as a cubic-analog of diaphite-like lonsdaelite phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

"Independent" and "Dependent" Scattering by Particles in a Multi-Particle Group

The terms "independent" and "dependent" scattering are ubiquitous in the phenomenological discipline of light scattering by particulate media. Yet there is a wide range of ad hoc definitions of these terms, many of which are vague and conceptually inconsequential. In this paper we perform a first-principles analysis of these terms based on the rigorous volume-integral-equation formulation of electromagnetic scattering. We argue that scattering by a multi-particle group can be called independent if certain optical observables for the entire group can be expressed in appropriate single-particle observables. Otherwise one deals with the dependent scattering regime. The prime (and perhaps the only) examples of independent scattering are scattering scenarios described by the first-order scattering approximation and the first-principles radiative transfer theory.

Particle scattering↗

Emergence of competing electronic states from non-integer nuclear charges

Understanding many-electron phenomena with competing near-degenerate electronic states is of fundamental importance to chemistry and condensed matter physics. One of the most significant challenges for exploring such many-electron phenomena is the necessity for large system sizes in order to realize competing states, far beyond those practical for first-principles methods. Here, we show how allowing non-integer nuclear charges expands the space of computationally tractable electron systems that host competing electronic states. The emergence of competing electronic states from non-integer nuclear charges is exemplified in the simple 2-electron H 2 molecule and used to examine the microscopic structure of doped quasi-1D cuprate chains, showing how non-integer nuclear charges can open a window for first-principles calculations of difficult many-electron phenomena.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Interaction energy and isosteric heat of adsorption between hydrogen and magnesium diboride

Hydrogen storage materials form a crucial research topic for future energy utilization employing hydrogen and among those of interest magnesium diboride (MgB 2 ) has shown its prevalence. In this study, a first-principles analytical adsorption model of one hydrogen molecule in the vicinity of various magnesium diboride crystal surfaces was developed in order to obtain surface thermodynamic properties as a function of molecular and lattice properties. Henry's law constant (K H ) and isosteric heat of adsorption (ΔH ads ) indicators of the affinity between a gaseous molecule and a solid surface are thus calculated. The results in this paper not only address questions pertaining to the first stage of hydrogen storage processes but also advance the understanding of physisorption thermodynamics of a neutral molecule (H 2 ) coming in contact with a layered metallic-like surface (MgB 2 ). Although the model is built from a framework of classical calculations, quantum effects are incorporated as the fractional charge of the ions on the free surfaces, which is essential for the calculation of analytic thermodynamic values that approximate calculations from other methods. To benchmark our theoretical models, periodic density functional calculations were performed to determine the interactions between H 2 and different MgB 2 surfaces from first-principles. By considering both the top and sublayers of MgB 2 in calculating interaction energy, we have analytically and computationally calculated the interaction energies of H 2 molecules and MgB 2 's terminated planes, and witnessed the strong dependence of interaction energies on surface charges. We have also observed a dipole flipping phenomenon which explains the discontinuity seen in the interaction energy graph of Mg(0001). Both analytical and computational results showed heat of adsorption at zero coverage varying at a very low range (<7 kJ mol -1 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab initio translationally invariant nucleon-nucleus optical potentials

We combine the ab initio symmetry-adapted no-core shell model (SA-NCSM) with the single-particle Green's function approach to construct optical potentials rooted in first principles. Specifically, we show that total cross sections and phase shifts for neutron elastic scattering from a 4 He target with projectile energies between 0.5 and 10 MeV closely reproduce the experiment. In addition, we discuss an important new development that resolves a long-standing issue with spurious center-of-mass motion in the Green's function formalism for many-body approaches. Furthermore, the new development opens a path for first-principle predictions of cross sections for elastic scattering of single-nucleon projectiles, nucleon capture, and deuteron breakup reactions, feasible for a broad range of open-shell spherical and deformed nuclei in the SA-NCSM approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗