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DOE OSTI2025

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)↗

DOE OSTI2024

Gaining insight into lithium-ion battery degradation by a calorimetric approach

With the growing demand for lithium-ion batteries (LIBs) in transportation and renewable energy sectors, ensuring reliability and mitigating degradation are crucial challenges for their widespread deployment. Here this study investigates the relationship between thermal characteristics and degradation/reliability by developing an in-situ heat measurement methodology for LIBs operating under grid services. Using adiabatic mode-based calorimetry, we examine the thermal behavior of two commercial cells with different cathode chemistries (Ni-rich layered oxide and olivine) before and after two years of grid service (peak shaving) and demonstrate a strong correlation between thermal characteristics and electrochemical performance and its degradation. By further analyzing the heat sources separation (differentiating between irreversible and reversible heat), we disclose the underlying degradation mechanisms of LIBs. These findings emphasize the critical role of thermal characteristics in determining LIB reliability and deterioration, while the obtained heat data can aid in the development and calibration of LIB state-of-health models for grid applications.

25 ENERGY STORAGE↗

DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices

Marine energy devices must be attached to the seafloor by their foundations, pilings, or anchors, and will have other parts in the water column like the devices themselves, mooring lines, and power export cables running along the seafloor. The installation and presence of these artificial structures will create physical changes that can disrupt or create new habitats, and potentially alter the behavior of mobile organisms such as fish around a device by attracting them to these new artificial reefs and fish aggregating devices. In this study, we tested a new approach for monitoring fish activity around a marine energy device anchor: a 360-degree underwater camera to keep the target (a wave energy converter’s anchor) in the field of view of the camera. The camera was deployed in three configurations (hand-held, tripod, video lander) at sites with different hydrodynamics and underwater visibilities. The video lander was the best configuration: very stable, versatile, and easy to handle. The 360-degree field of view enabled observing and counting fishes, which were more abundant at dusk than dawn or noon, around the anchor. Despite remaining challenges, 360-degree cameras are useful tools for monitoring animal interactions with marine energy devices.

360-degree camera↗

NASA NTRS1994

HAPEX-Sahel: A large-scale study of land-atmosphere interactions in the semi-arid tropics

The Hydrologic Atmospheric Pilot EXperiment in the Sahel (HAPEX-Sahel) was carried out in Niger, West Africa, during 1991-1992, with an intensive observation period (IOP) in August-October 1992. It aims at improving the parameteriztion of land surface atmospheric interactions at the Global Circulation Model (GCM) gridbox scale. The experiment combines remote sensing and ground based measurements with hydrological and meteorological modeling to develop aggregation techniques for use in large scale estimates of the hydrological and meteorological behavior of large areas in the Sahel. The experimental strategy consisted of a period of intensive measurements during the transition period of the rainy to the dry season, backed up by a series of long term measurements in a 1 by 1 deg square in Niger. Three 'supersites' were instrumented with a variety of hydrological and (micro) meteorological equipment to provide detailed information on the surface energy exchange at the local scale. Boundary layer measurements and aircraft measurements were used to provide information at scales of 100-500 sq km. All relevant remote sensing images were obtained for this period. This program of measurements is now being analyzed and an extensive modelling program is under way to aggregate the information at all scales up to the GCM grid box scale. The experimental strategy and some preliminary results of the IOP are described.

Gutorbe, J-P.↗

DOE OSTI2020

Filament-Free Bulk Resistive Memory Enables Deterministic Analogue Switching

Digital computing is nearing its physical limits as computing needs and energy consumption rapidly increase. Analogue-memory-based neuromorphic computing can be orders of magnitude more energy efficient at data-intensive tasks like deep neural networks, but has been limited by the inaccurate and unpredictable switching of analogue resistive memory. Filamentary resistive random access memory (RRAM) suffers from stochastic switching due to the random kinetic motion of discrete defects in the nanometer-sized filament. Here, this stochasticity is overcome by incorporating a solid electrolyte interlayer, in this case, yttria-stabilized zirconia (YSZ), toward eliminating filaments. Filament-free, bulk-RRAM cells instead store analogue states using the bulk point defect concentration, yielding predictable switching because the statistical ensemble behavior of oxygen vacancy defects is deterministic even when individual defects are stochastic. Both experiments and modeling show bulk-RRAM devices using TiO2-X switching layers and YSZ electrolytes yield deterministic and linear analogue switching for efficient inference and training. Bulk-RRAM solves many outstanding issues with memristor unpredictability that have inhibited commercialization, and can, therefore, enable unprecedented new applications for energy-efficient neuromorphic computing. Beyond RRAM, this work shows how harnessing bulk point defects in ionic materials can be used to engineer deterministic nanoelectronic materials and devices.

36 MATERIALS SCIENCE↗

DOE OSTI2026

CalderaCast Web Interface

CalderaCast may be accessed as a web-based tool at the first link in the references section of this dataset. All of the necessary datasets to run the tool are built into the simulation software running behind the web interface. These input datasets are referenced by the additional links in the references section below. Many of those datasets are taken into machine-learning algorithms by the Caldera team and heavily processed to create internal datasets, which are then relied upon by the simulation to produce individual results. These internal datasets are not accessible and are not necessary for use of the CalderaCast tool.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Identifying Molecular Scale Interactions of Nucleating Agents with Salt Hydrates for Thermal Energy Storage Applications

Latent heat based thermal energy storage is of interest as a method to mitigate and time-shift thermal load peaks and hence reduce energy demands for heating and cooling buildings. Notably, Glauber’s salt (GS) presents a good choice as a phase change material (PCM) for building applications because it has a melting point near room temperature (i.e., 32.4 °C), a large heat of fusion and energy density, and is low cost (~ $100/ton). However, there are several known limitations to using GS as a PCM, such as incongruent melting, high degree of supercooling, and formation of other hydration states, which renders GS unsuitable for practical use. Inorganic crystals acting as nucleating agents can avoid some of these issues with GS [1]. Understanding nucleation behavior through typical calorimetry experiments offers limited insight into the molecular-scale mechanisms. Here, we report isothermal titration calorimetry [2] to investigate the interactions between sodium sulfate salt and an organic nucleating agent - glycine. Our experiments provide qualitative and quantitative understanding of how glycine interacts with sodium sulfate across various temperatures. The findings offer insights into the nucleation onset temperature (24°C) and underscore the pivotal role of glycine's zwitterionic structure in facilitating nucleation. This preliminary work provides a foundation for subsequent exploration of nucleating agents that would be incorporated in different salt hydrate systems. 1. Purohit, B. K., and V. S. Sistla. "Inorganic salt hydrate for thermal energy storage application: A review." Energy Storage 3, no. 2 (2021): e212. 2. Velázquez-Campoy, Adrián, Hiroyasu Ohtaka, Azin Nezami, Salman Muzammil, and Ernesto Freire. "Isothermal titration calorimetry." Current protocols in cell biology 23, no. 1 (2004): 17-8.

calorimetry, nucleation & growth↗

DOE OSTI2024

First characterization of the emission behavior of Mrk 421 from radio to very high-energy gamma rays with simultaneous X-ray polarization measurements

Aims.We have performed the first broadband study of Mrk 421 from radio to TeV gamma rays with simultaneous measurements of the X-ray polarization from IXPE. Methods.The data were collected as part of an extensive multiwavelength campaign carried out between May and June 2022 using MAGIC,Fermi-LAT,NuSTAR,XMM-Newton,Swift, and several optical and radio telescopes to complement IXPE data. Results.During the IXPE exposures, the measured 0.2–1 TeV flux was close to the quiescent state and ranged from 25% to 50% of the Crab Nebula without intra-night variability. Throughout the campaign, the very high-energy (VHE) and X-ray emission are positively correlated at a 4σsignificance level. The IXPE measurements reveal an X-ray polarization degree that is a factor of 2–5 higher than in the optical/radio bands; that implies an energy-stratified jet in which the VHE photons are emitted co-spatially with the X-rays, in the vicinity of a shock front. The June 2022 observations exhibit a rotation of the X-ray polarization angle. Despite no simultaneous VHE coverage being available during a large fraction of the swing, theSwift-XRT monitoring reveals an X-ray flux increase with a clear spectral hardening. This suggests that flares in high synchrotron peaked blazars can be accompanied by a polarization angle rotation, as observed in some flat spectrum radio quasars. Finally, during the polarization angle rotation,NuSTARdata reveal two contiguous spectral hysteresis loops in opposite directions (clockwise and counterclockwise), implying important changes in the particle acceleration efficiency on approximately hour timescales.

Astronomy & Astrophysics↗

DOE OSTI2020

Semiconducting to Metallic Electronic Landscapes in Defects-Controlled 2D π-d Conjugated Coordination Polymer Thin Films

Two-dimensional coordination polymers (2DCPs) have been predicted to exhibit exotic properties such as superconductivity, topological insulating behavior, catalytic activity, and superior ion transport for energy applications; experimentally, these materials have fallen short of their expectation due to the lack of synthesis protocols that yield continuous, large crystallite domains, and highly ordered thin films with controllable physical and chemical properties. Herein, the fabrication of large-area, highly ordered 2DCP thin films with large crystallite domains using chemical vapor deposition (CVD) approaches is described. It is demonstrated that defects and the packing motifs of 2DCP thin films may be controlled by adjusting the vapor–vapor and vapor–solid interactions of the metal and organic linker precursors during the CVD fabrication process. Such control allows for the fabrication of defects-controlled 2DCP thin films that show either semiconducting or metallic behavior. The findings provide the first demonstration of tuning the electrical properties of sub 100 nm-thick continuous 2DCP thin films by controlling their electronic landscape through defect engineering. As such, it is determined that large-area, highly ordered 2DCP thin films may undergo a semiconducting to metallic transition that is correlated to changes in morphology, crystalline domain sizes, crystallite orientation, defect interactions, and electronic structure.

2D coordination polymers↗

DOE OSTI2024

Predicting the heat release variability of Li-ion cells under thermal runaway with few or no calorimetry data

Accurate measurement of the variability of thermal runaway behavior of lithium-ion cells is critical for designing safe battery systems. However, experimentally determining such variability is challenging, expensive, and time-consuming. Here, we utilize a transfer learning approach to accurately estimate the variability of heat output during thermal runaway using only ejected mass measurements and cell metadata, leveraging 139 calorimetry measurements on commercial lithium-ion cells available from the open-access Battery Failure Databank. We show that the distribution of heat output, including outliers, can be predicted accurately and with high confidence for new cell types using just 0 to 5 calorimetry measurements by leveraging behaviors learned from the Battery Failure Databank. Fractional heat ejection from the positive vent, cell body, and negative vent are also accurately predicted. We demonstrate that by using low cost and fast measurements, we can predict the variability in thermal behaviors of cells, thus accelerating critical safety characterization efforts.

25 ENERGY STORAGE↗

DOE OSTI2022

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗

NASA NTRS1999

RXTE Observation of 4U 1630-47 During its 1998 Outburst

During the 1998 outburst of 4U 1630-47 it was extensively observed with the Rossi X-ray Timing Explorer (RXTE). In order to cover the outburst more thoroughly our data (Obs. ID: 30178-0[1-2]- ) were combined with those of Cui et al. (Obs. ID: 30188-02-). These observations were later compared with the complementary observations. Power density and energy spectra have been made for each observation. The data was used to place radio and hard X-ray observations within context. Analysis of SAX (Satellite per Astronomia a raggi X) and BATSE (Burst and Transient Source Experiment) data was also included within the study. The count rate and position in hardness-intensity, color-color diagrams and simple spectral fits are used to track the concurrent spectral changes. The source showed seven distinct types of timing behavior, most of which show differences with the canonical black hole spectral/timing states. In marked contrast to previous outbursts, we find quasi-periodic oscillation (QPO) signals during nearly all stages of the outburst with frequencies between 0.06 Hz and 14 Hz and a remarkable variety of other characteristics. In particular we find large (up to 23% rms) amplitude QPO on the early rise. Later, slow 0.1 Hz semi- regular short (- 5 sec), 9 to 16% deep dips dominate the light curve. At this time there are two QPOS, one stable near 13.5 Hz and the other whose frequency drops from 6-8 Hz to - 4.5 Hz during the dips. BeppoSAX observations during the very late declining phase show 4U 1630-47 in a low state. These results will shortly be published. We are completing a detailed analysis of the energy spectra (in preparation). The QPO/noise properties are being correlated with the concurrent spectral changes. Detailed studies of the QPO are being undertaken using sophisticated timing analysis methods. Finally a comparison with the other outbursts of 1630-47 is being made.

Dieters, Stefan W.↗

DOE OSTI2023

Atomistic simulations of He bubbles in Beryllium

Formation of He bubbles can have a significant effect on the microstructural evolution and properties of irradiated materials. In this report, we use atomistic simulations based on machine learning potentials to investigate the fundamental behavior of He bubbles in Be, with a specific focus on the shape, stability, and diffusivity of bubbles. Stability of He bubbles is quantified in terms of formation energies, which are determined as a function of the ratio of He/V. We find that He bubbles become unstable with respect to plastic deformation through punch-out dislocations around the bubble when the He/V ratio is larger than ~1.25, and the punch-out process induces the change of the regular bubble shape. In general, the bubble shape of He in Be is found to be ellipsoid-like. It is also found that for a fixed He/V ratio, the bubble attracts vacancies to become larger in size. If the bubble size is constant, the bubble attracts additional He atoms until the punch-out reaction occurs. The dominant diffusion mechanism of He bubbles changes from surface diffusion to volume diffusion as the temperature is increased, with a crossover occurring at about 900 K.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Microstructural Effects of High Dose Helium Implantation in ErD 2

Metal hydrides can store hydrogen isotopes with high volumetric density. In metal tritides, tritium beta decay can result in accumulation of helium within the solid, in some cases exceeding 10 at.% helium after only 4 years of aging. Helium is insoluble in most materials, but often does not readily escape, and instead coalesces to form nanoscale bubbles when helium concentrations are near 1 at.%. Blistering or spallation often occurs at higher concentrations. Radioactive particles shed during this process present a potential safety hazard. This study investigates the effects of high helium concentrations on erbium deuteride (ErD 2 ), a non-radioactive surrogate material for erbium tritide (ErT 2 ). To simulate tritium decay in the surrogate, high doses of 120 keV helium ions were implanted into ErD 2 films at room temperature. Scanning and transmission electron microscopy indicated spherical helium bubble formation at a critical concentration of 1.5 at.% and bubble linkage leading to nanoscale crack formation at a concentration of 7.5 at.%. Additionally, crack propagation occurred through the nanocrack region, resulting in spallation extending from the implantation peak to the surface. Electron energy loss spectroscopy was utilized to confirm the presence of high-pressure helium in the nanocracks, suggesting that helium gas plays a predominant role in deformation. This work improves the overall understanding of helium behavior in ErD 2 by using modern characterization techniques to determine: the critical helium concentration required for bubble formation, the material failure mechanism at high concentration, and the nanoscale mechanisms responsible for material failure in helium implanted ErD 2 .

36 MATERIALS SCIENCE↗

DOE OSTI2024

Strain-Induced Shifts in Defective Graphite Phonon Modes Predicted by Density Functional Theory

Carbon fiber composites have gained attention as a structural material because of their high strength-to-weight ratio, and understanding the effect of defects on reactivity and mechanical properties is important for the longevity and safety of the composite. Although it is known that strain causes the underlying graphitic vibrational modes to redshift, it is not clear how strain may alter reactivity and defect-induced vibrational changes. To investigate the strain-induced phonon changes of defective carbon fiber composites, density functional theory calculations of graphite are used, including intercalated hydrogen and fluorine defects. By comparing changes in the bond lengths, formation energies, and phonon density of states for uniaxially and biaxially strained graphite, strain was found to generally make defect formation more favorable and the specific behavior changes are dependent on the strain direction and defect identity. Specifically, intercalated fluorine phonons are more sensitive to strain than hydrogen intercalation phonons, and strain applied along the zigzag direction alters the calculated properties more than strain along the armchair direction. Finally, these results highlight the importance of understanding the microstructural effect of deviations from the ideal material because small changes in strain or defect type can significantly alter the behavior of the carbon fiber composite core.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Onset of anharmonicity and thermal conductivity in SnSe

The anharmonicity in SnSe is investigated through the analysis of moments of 119Sn nuclear resonant inelastic x-ray scattering and ab initio molecular dynamics calculations. Experimental evidences show that the anharmonic behavior started around 300 K, substantially lower than the usually suggested structural transition at 800 K. Both theory and experiments reveal substantial lifetime broadening and frequency renormalization of the optical phonons. Additionally, thermal conductivities calculated from the temporal energy moment using the Einstein diffusion equation are in good agreement with previous experiments. The abrupt increase of the thermal power near 800 K is driven by an electronic factor and not by the enhanced anharmonicity due to structural change.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Hund bands in spectra of multiorbital systems

Spectroscopy experiments are routinely used to characterize the behavior of strongly correlated systems. An in-depth understanding of the different spectral features is thus essential. Here, we show that the spectrum of the multiorbital Hubbard model exhibits unique Hund bands that occur at energies given only by the Hund coupling J H , as distinct from the Hubbard satellites following the interaction U. We focus on experimentally relevant single-particle and optical spectra that we calculate for a model related to iron chalcogenide ladders. The calculations are performed via the density-matrix renormalization group and Lanczos methods. Finally, the generality of the implications is verified by considering a generic multiorbital model within dynamical mean-field theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗