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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluating the industrial potential of emerging biomass pretreatment technologies in bioethanol production and lipid recovery from transgenic sugarcane

The selection of pretreatment methods is critical to achieving high product yields during bioconversion of lignocellulosic biomass. Hydrothermal, soaking-in-aqueous ammonia, and ionic liquid pretreatment methods are viable candidates for minimizing sugar decomposition, permitting the effective hydrolysis of structural carbohydrates, and producing a fermentable substrate suitable for achieving industrial ethanol titers and yields. In this study, the effect of these three pretreatment methods on non-modified sugarcane cultivar CP88-1762 and two transgenic lipid-accumulating sugarcane lines, oilcane 1565 and oilcane 1566, were investigated and compared in terms of lipid recovery, sugar yield, and ethanol yields within the lignocellulosic biomass conversion pipeline. Fed-batch enzymatic hydrolysis at high solid loading yielded hydrolysates capable of supporting industrial bioethanol titers across all conditions. The highest sugar yields were obtained on ammonia-pretreated biomass hydrolysate (253.73 g L −1 ), followed by hydrothermally pretreated hydrolysate (213.10 g L −1 ) and ionic liquid-pretreated hydrolysate (154.20 g L −1 ). Commercially viable ethanol titers of 100.62 g L −1 , 64.47 g L −1 , and 52.95 g L −1 were achieved from ammonia, hydrothermal, and ionic liquid pretreated hydrolysate with the corresponding ethanol productivities of 2.08 g L −1 h −1 , 0.53 g L −1 h −1 , and 0.36 g L −1 h −1 . The lower acetic acid concentration in ammonia-pretreated hydrolysate may have enhanced its fermentability relative to the hydrothermal pretreatment condition, as indicated by the differences in ethanol titer and productivity. Lower sugar yields and ethanol productivities under the ionic liquid conditions likely resulted from the inhibitory effect of cholinium lysinate. Oilcane 1565 and oilcane 1566 bagasse accumulated over 16- and 3 times higher lipids than the non-modified sugarcane CP88-1762. The total fatty acid content in the oilcane samples was reduced in ammonia and ionic liquid-pretreated bagasse relative to the hydrothermal pretreatment condition. While all pretreatment techniques tested are industrially viable, the observed differences in titer, productivity, and lipid content indicate that careful selection and validation of upstream processing methods can contribute to improved economic and environmental outcomes.

09 BIOMASS FUELS↗
DOE OSTI2025

Data for "Evaluating the industrial potential of emerging biomass pretreatment technologies in bioethanol production and lipid recovery from transgenic sugarcane"

The selection of pretreatment methods is critical to achieving high product yields during bioconversion of lignocellulosic biomass. Hydrothermal, soaking-in-aqueous ammonia, and ionic liquid pretreatment methods are viable candidates for minimizing sugar decomposition, permitting the effective hydrolysis of structural carbohydrates, and producing a fermentable substrate suitable for achieving industrial ethanol titers and yields. In this study, the effect of these three pretreatment methods on non-modified sugarcane cultivar CP88-1762 and two transgenic lipid-accumulating sugarcane lines, oilcane 1565 and oilcane 1566, were investigated and compared in terms of lipid recovery, sugar yield, and ethanol yields within the lignocellulosic biomass conversion pipeline. Fed-batch enzymatic hydrolysis at high solid loading yielded hydrolysates capable of supporting industrial bioethanol titers across all conditions. The highest sugar yields were obtained on ammonia-pretreated biomass hydrolysate (253.73 g L−1), followed by hydrothermally pretreated hydrolysate (213.10 g L−1) and ionic liquid-pretreated hydrolysate (154.20 g L−1). Commercially viable ethanol titers of 100.62 g L−1, 64.47 g L−1, and 52.95 g L−1 were achieved from ammonia, hydrothermal, and ionic liquid pretreated hydrolysate with the corresponding ethanol productivities of 2.08 g L−1 h−1, 0.53 g L−1 h−1, and 0.36 g L−1 h−1. The lower acetic acid concentration in ammonia-pretreated hydrolysate may have enhanced its fermentability relative to the hydrothermal pretreatment condition, as indicated by the differences in ethanol titer and productivity. Lower sugar yields and ethanol productivities under the ionic liquid conditions likely resulted from the inhibitory effect of cholinium lysinate. Oilcane 1565 and oilcane 1566 bagasse accumulated over 16- and 3 times higher lipids than the non-modified sugarcane CP88-1762. The total fatty acid content in the oilcane samples was reduced in ammonia and ionic liquid-pretreated bagasse relative to the hydrothermal pretreatment condition. While all pretreatment techniques tested are industrially viable, the observed differences in titer, productivity, and lipid content indicate that careful selection and validation of upstream processing methods can contribute to improved economic and environmental outcomes.

biomass analytics↗
DOE OSTI2024

The Zwicky Transient Facility Bright Transient Survey. III. BTSbot: Automated Identification and Follow-up of Bright Transients with Deep Learning

Abstract The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright ( m peak ≤ 18.5 mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection (“scanning”) to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5 yr of ZTF operations. We present BTSbot , a multimodal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼1 hr quicker than scanners). We also find that BTSbot is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. BTSbot has been integrated into Fritz and Kowalski , ZTF’s first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. Between 2023 December and 2024 May, BTSbot selected 609 sources in real time, 96% of which were real extragalactic transients. With BTSbot and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human time needed to scan.

Rehemtulla, Nabeel (ORCID:0000000256832389)↗
DOE OSTI2025

Laser-induced selective local patterning of vanadium oxide phases

The same elements can form different compounds with widely different physical properties. Synthesis of a single-phase material is commonly achieved by controlling experimental conditions. Synthesizing materials that incorporate multiple specific spatially distributed chemical phases is often challenging, especially if different phases must be organized into well-defined spatial patterns. Here, we present an efficient solid reaction laser annealing (SRLA) approach to directly write regions of different local chemical compositions. We demonstrate the practical utility of our approach by locally writing microscale patterns of distinct chemical phases in vanadium oxide thin films. Specifically, we achieved the controlled local recrystallization of a uniform V 2 O 3 matrix into VO 2 , V 3 O 5 , and V 4 O 7 regions exhibiting sharp 1st- and 2nd-order metal–insulator phase transitions over a wide range of critical temperatures, i.e., a characteristic feature of select vanadium oxides that is extremely sensitive to even minute structural or compositional imperfections. We utilized the local chemical phase writing to pattern spiking oscillators with distinct electrical behavior directly in the thin film sample without employing elaborate lithography fabrication. Our laser tuning local chemical composition opens a pathway to synthesize a wide range of artificially micropatterned composite materials, with precision and control unattainable in conventional material synthesis methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Photoselective isotope fractionation dynamics of N 2 with cosmo and atmospheric chemistry perspectives

Stable isotope ratio measurements provide valuable insights into a broad range of natural processes, from planetary atmospheres and climate to interstellar chemistry. Nitrogen, which has two stable isotopes, exhibits varying isotope ratios across the solar system. To model these observations, the isotope fraction as a function of energy is essential. At the Advanced Light Source (ALS), we measured the photodissociation of molecular nitrogen (N 2 ) with vacuum UV photons where a single photon is sufficiently energetic to dissociate the strong bond. The nitrogen atoms produced are scavenged with H 2 to form ammonia, whose isotopic makeup is determined. Blending the experiments with dynamical computations that include the shielding of light, we examine the isotopic composition and electronic atomic states produced. The measured photodissociation of N 2 at a natural isotopic composition with a frequency broad light beam exceptionally strongly favors the formation of the heavier nitrogen isotope, 15 N. Computations concur and suggest that the maximum in the quantum yield reflects significant variations in the specific electronic quantum states of the product N atoms that have quite different reactivities. Our quantum computations show that at similar energies, photodissociation of 14 N 14 N and 15 N 14 N can lead to different product channels. The computed dynamics include extensive state-selective spin–orbit and nonadiabatic couplings affecting the light absorption and dissociation pathways that proceed via the triplet manifold of states. Our results are relevant for future exploration missions, both in situ and sample-return and for other molecules such as O 2 and CO.

Komarova, Ksenia [Hebrew Univ. of Jerusalem (Israe↗
DOE OSTI2025

Benchmarking the performance of a high-Q cavity qudit using random unitaries

High-coherence cavity resonators are excellent resources for encoding quantum information in higher-dimensional Hilbert spaces, moving beyond traditional qubit-based platforms. A natural strategy is to use the Fock basis to encode information in qudits. One can perform quantum operations on the cavity mode qudit by coupling the system to a non-linear ancillary transmon qubit. However, the performance of the cavity-transmon device is limited by the noisy transmons. It is, therefore, important to develop practical benchmarking tools for these qudit systems in an algorithm-agnostic manner. We gauge the performance of these qudit platforms using sampling tests such as the heavy output generation test as well as the linear cross-entropy benchmark, by way of simulations of such a system subject to realistic dominant noise channels. We use selective number-dependent arbitrary phase and unconditional displacement gates as our universal gateset. Our results show that contemporary transmons comfortably enable controlling a few tens of Fock levels of a cavity mode. This framework allows benchmarking even higher dimensional qudits as those become accessible with improved transmons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling

We introduce a novel semi-supervised learning approach, named Teacher-Student Bayesian Optimization (TSBO ), integrating the teacher-student paradigm into BO to minimize expensive labeled data queries for the first time. TSBO incorporates a teacher model, an unlabeled data sampler, and a student model. The student is trained on unlabeled data locations generated by the sampler, with pseudo labels predicted by the teacher. The interplay between these three components implements a unique selective regularization to the teacher in the form of student feedback. This scheme enables the teacher to predict high-quality pseudo labels, enhancing the generalization of the GP surrogate model in the search space. To fully exploit TSBO , we propose two optimized unlabeled data samplers to construct effective student feedback that well aligns with the objective of Bayesian optimization. Furthermore, we quantify and leverage the uncertainty of the teacher-student model for the provision of reliable feedback to the teacher in the presence of risky pseudo-label predictions. TSBO demonstrates significantly improved sample-efficiency in several global optimization tasks under tight labeled data budgets. The implementation is available at https://github.com/reminiscenty/TSBO-Official.

Yin, Yuxuan↗
DOE OSTI2024

Rapid and high-throughput determination of sorghum ( Sorghum bicolor ) biomass composition using near infrared spectroscopy and chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum (Sorghum bicolor) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

09 BIOMASS FUELS↗
DOE OSTI2025

Investigation of the Effect of Framework Flexibility on CO 2 Adsorption in SIFSIX-3-Cu Using a Machine-Learned Force Field

Metal–organic frameworks (MOFs) offer promise as selective CO 2 sorbents, but successful MOF sorbent materials need high CO 2 binding affinity and selectivity for CO 2 over water. This work focuses on the use of machine-learned force fields (MLFFs) to model CO 2 adsorption in flexible MOFs, with a focus on SIFSIX-3-Cu, an anion-pillared MOF known for its high CO 2 affinity. A preliminary high-throughput screening of over 900 anion-pillared MOFs was performed using rigid UFF+DDEC6 force fields to predict zero-loading heats of adsorption for CO 2 and H 2 O. SIFSIX-3-Cu was selected for further computational study due to its predicted CO 2 heat of adsorption and experimental relevance. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies and forces, with an iterative sampling scheme combining molecular dynamics, geometry optimization, random geometric insertion, and NVT Monte Carlo-based configuration generation to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included, contrasting with previous models that approximated the MOF as rigid. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations with the MLFF produced CO 2 adsorption isotherms in good agreement with experimental data at direct air capture (DAC) pressures (e.g., 40 Pa), in contrast to previous overestimations of CO 2 sorption by models with rigid structures. Bond and angle histogram analysis showed that MOF flexibility increased the variance of fluorine–fluorine diagonal distances at adsorption sites, resulting in a lower predicted sorption for flexible, asymmetric SIFSIX-3-Cu pore geometries compared to the rigid, symmetric DFT-optimized SIFSIX-3-Cu pore geometry. A detailed description of flexibility afforded by the MLFF resulted in an accurately predicted CO 2 uptake (0.88 mmol/g) at low pressure (40 Pa) compared to the experimentally measured value (1.24 mmol/g). In conclusion, these results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low-pressure applications.

adsorption↗
DOE OSTI2026

Propane Dehydrogenation Catalyzed by Supported Group IV (Ti, Zr, Hf) Organometallics on Silicon Nitride

Mesoporous silicon nitride (Si 3 N 4 ) enables access to chemisorbed group IV organometallics catalysts active for propane dehydrogenation (PDH) compared to the organometallic analogues on mesoporous silica under the same reaction conditions. The series of Si 3 N 4 -supported materials are active catalysts, (Zr > Hf > Ti k f = 290, 232, and 162 mol mol Metal -1 h -1 at 450 °C with 2% C 3 H 8 in Ar, respectively) with selectivity above 95%, demonstrating additional examples of Ti and Hf systems for PDH. However, the underlying mechanism of the improved performance relative to oxide supported homologues is not well-understood. Characterization of thermally treated samples (DRIFTS, XAS and SSNMR) and computational modeling of this catalyst series was utilized to differentiate between potential amido - (C-H activation along the M-N bond) and imido - (C-H activation along the M=N bond) mechanisms. Due to remaining mechanistic ambiguity, a Ga analogue was synthesized and evaluated for PDH activity as an indirect probe to experimentally differentiate pathways. An inversion of the oxide/nitride performance trend is observed for the Ga congener which does not form a Ga=N bond, most consistent with different mechanisms dictating the performance of the group IV/Si 3 N 4 catalysts vs Ga/Si 3 N 4 .

heterolytic cleavage↗
DOE OSTI2024

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗
DOE OSTI2025

Methods for Carbon Mass Closure in Polyolefin Hydrocracking

Heterogeneous catalytic hydrocracking of polyolefins is a promising approach for the processing of postconsumer plastics, but product quantification methods remain inconsistent across the literature. In systems that generate a large fraction of vapor-phase products, typical product capture methods can result in large carbon balance deficits, exceeding 50%, compromising reported yields and selectivities. Here, we identify the major sources of product loss and develop enhanced capture methods to improve the quantification accuracy. Seven supplemental techniques were evaluated, targeting either increased vapor recovery (by increasing the volatility or system volume) or enhanced retention in the liquid phase (by decreasing volatility). Among these, a flow collection approach using a continuous helium sweep and downstream gas sampling bag capture yielded the highest recovery, achieving a 96 ± 9.2% carbon balance closure. We show that the efficacy of these methods is strongly dependent on product distribution. In general, solvent addition was most effective when condensable species dominate the product distribution, while flow collection was preferred when both condensable species and light gases are present in high concentrations. These results highlight the need for method-specific workup strategies and demonstrate that no single protocol is universally optimal. We provide general guidelines for selecting and implementing robust product capture techniques, enabling accurate yield and selectivity determinations in polyolefin hydrocracking systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Electron beam irradiation effects on bulk metals: a comparative study of polycrystalline versus single-crystalline structures

This study investigates the effects of electron beam (e-beam) irradiation on the mechanical and structural properties of eight bulk metallic samples, comprising both polycrystalline (PC) and single-crystalline (SC) forms of Ni, Cr, V, and Ti. These metals were evaluated as potential candidates for beam exit windows in high-power (MW-class) particle accelerators. The primary objective is to identify metals capable of withstanding the conditions of high-power/MW-class e-beam accelerators and serve effectively as exit windows. Selection criteria were based on each metal’s intrinsic properties, power dissipation capability, and irradiation-induced changes in mechanical behavior, including hardness, elastic modulus, and defect density. Comprehensive characterization was conducted using field-emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDS), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), and nanoindentation, performed both before and after exposure to a ~¿66 kGy dose from a 10 MeV e-beam accelerator. Results revealed that e-beam irradiation induced hardening in PC Ni, whereas PC Ti, commonly used in beam exit windows, exhibited softening. The observed softening in PC Ti is attributed to grain coarsening, elongation, and the formation of twins and twin boundaries, in contrast to the smaller, compressed grains in the pristine (Pr) PC Ti samples, consistent with the Hall–Petch relationship. The stresses due to twinning are small and insignificant in influencing the overall hardening of the PC Ti irradiated sample when compared to the stresses due to the dislocation density. Conversely, SC Ti samples exhibited irradiation-induced hardening. The SC Ti irradiated samples developed additional irradiation-induced modifications in crystallographic texture of (100), (101), (110), (200), (112), (004), and (211) as evidenced from the XRD results, which could probably explain the hardening effect that is caused by irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ToF-SIMS in material research: A view from nanoscale hydrogen detection

Hydrogen in materials has attracted tremendous interest as its incorporation leads to significant alterations in nanoscale structure, composition, and chemistry, impacting functional properties. It has also been integral to nuclear fusion reactors and is considered a future clean energy source. However, nanoscale characterization and manipulation of hydrogen in materials are challenging as only a selected few analytical techniques can readily detect hydrogen, among which time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a unique and powerful one due to its excellent detection limit along with decent depth and lateral resolutions. Here, in this review, we discuss, using selected examples, how to detect and quantify hydrogen in materials by ToF-SIMS and its impact on revealing the hydrogenation/protonation-induced novel functional states in different classes of materials. In addition, we present our protocols on sample preparation and experimental conditions optimization, allowing us to achieve the best possible results. Finally, we highlight future research directions that can lead to the discovery of novel functional states and ultimately provide a deeper understanding of scientific questions in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Influence of preheating on tungsten damage under pulsed hydrogen plasma exposure

Preheated tungsten plate behavior under multiple pulsed hydrogen plasma irradiations in the PW-7 plasma accelerator was investigated. The preheating temperature was 973 K, which is above the ductile to brittle transition temperature (DBTT ≈ 673 K). The plate was exposed to three consecutive series of 13 plasma pulses each. Preheating sufficiently suppressed surface cracking at the early irradiation stage: after 13 pulses, cracks were rare, localized, and did not form extensive fractures. During subsequent irradiation series, the area fraction of fine cracks increased by ∼ 2% due to accumulation of dislocations around the pre-existing defects. However, their width remained nearly constant, averaging 0.2–0.3 μm, with rare cracks up to 1 μm in size. Repeated plasma exposure resulted in pronounced surface roughening associated with multiple melting cycles, crater formation and blister rupture, with roughness reaching ∼ 204 nm and a recorded sample mass loss of ∼ 2.8 mg. These results indicate that controlling tungsten preheating well above DBTT effectively reduces damage. However, the surface condition during initial irradiation significantly influences its subsequent morphological evolution. Preheating to 773 K, selected regarding the minimum DBTT value, has previously been demonstrated to be an effective approach for limiting crack growth. A further increase in temperature of approximately ∼ 1000 K did not qualitatively improve results: crack still formed and widths did not decrease. At the same time, the absence of further crack coarsening indicates that the limiting effect of preheating has been reached. Considering the increased energy costs, further increasing the preheating temperature seems unjustified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Integrated Off-Gas System Tests on the DM1200 Melter with RPP-WTP LAW Sub-Envelope Bl Simulants, VSL-03R3851-1, Rev. 0 (Oct 2003)

The report documents melter and off-gas performance results obtained on the DM1200 melter during processing of LAW Sub-Envelope B1 feed. The principal objectives of the DM1200 melter testing were to demonstrate suitable processing and production rates for LAW B1 feed; characterize the glass product for elemental composition; measure elemental emission rates and decontamination factors (DFs) across the melter and off-gas treatment components; and provide additional data on the performance of the thermal catalytic oxidation and selective catalytic reduction (TCO/SCR) unit efficiency in treating organic emissions. The feed was spiked with organic compounds for part of the testing duration. All data were collected for use in engineering and system design purposes. No sampling and analysis to collect environmental data was performed during these tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Novel ceramic capacitors with ultrahigh energy density and efficiency (Final Technical Report)

Antiferroelectric ceramics are a special class of material that have shown great potential as the dielectric in electrical capacitors due to their high energy- and power-density. During each charge-discharge cycle, the ceramic undergoes transformation to a ferroelectric phase and resumes its antiferroelectric phase. The hysteresis associated with the transitions leads to a mediocre energy efficiency and service lifetime of antiferroelectric capacitors and, hence, their almost absence in commercial products. Under the support of this research project, we first formulated a universal lattice-compatibility theory that included electrostatic polarization energy along with elastic energy and thermal energy to understand the origin of the hysteresis in antiferroelectric oxides. Guided by this compatibility theory, we conducted high-throughput density functional theory (DFT) calculations to assess chemical modifiers and their effect on crystal structures of 400+ PbZrO 3 -based compositions. Down-selected compositions were experimentally validated for their suppressed hysteresis and higher energy efficiency. The verified low-hysteresis compositions were then expanded to an antiferroelectric ceramic library with nearly 500 new compositions (more than 1,500 samples) using high-throughput experiments involving ceramic synthesis and property screening. The large quantity of data generated (theory and experimental) in these tasks were processed by machine-learning techniques and identified trends were fed to the next iteration. In the end, we successfully discovered four compositions with near-zero hysteresis, yielding a world-record energy efficiency of 98.2% at an energy density of 3.0 J/cm 3 . Furthermore, our antiferroelectric ceramic capacitor reaches 79.5 million charge-discharge cycles lifetime, a factor of 80 enhancement over previous antiferroelectric ceramics with large hysteresis. These research accomplishments have not only met the milestones set in the SOPO, but also led to two patent filings, three journal publications (one of them was in Advanced Materials, impact factor 29.4), and nine oral presentations at various venues. Through the course of the project, three postdocs, four Ph.D. students, and one M.S. student were trained. In short, our project established a new methodology in searching next-generation functional ceramics on the fundamental side and discovered several high-efficiency antiferroelectric compositions for capacitors on the applied side. Once fabricated into the multilayer form for commercial applications, these ceramic capacitors can potentially enable the high temperature high power density DC-link capacitors that are critical for the next generation inverters in electric vehicles. The project also significantly contributed to the nation’s workforce development in the STEM fields.

36 MATERIALS SCIENCE↗