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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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DOE OSTI2024

Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform

The goal of the Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform project is to derisk the manufacturing scalability for a high chip count heterogeneous smart lighting platform, with the potential to enable significant energy savings through dynamic directional light control and custom. Specifically, the project derisks the scalability of a disruptive new computer controlled microassembly fabrication process SRI International is developing, to address fundamental cost barriers to mass production of high chip count systems. This is key for enabling mass adoption and thus maximum societal energy savings impact. The LED light sheet technology is a smart illumination platform that can be applied to lighting, signage, and display. It has features and a form factor similar to bendable or conformal OLED light sheets but uses more efficient LEDs with a remote phosphor layer that is very close to the LED to deliver a luminous efficacy that exceeds 125 lumen/Watt and enable > 50% Lighting Application Efficiency (LAE) energy savings. During Budget Period 1 (BP1), all of the BP1 milestones were successfully completed: (M2.0.1) Design demonstrator details that will meet the final project goals, (M6.1.1) Show lighting output model can predict illuminance, spatial, spectral distribution for specific light-sheet designs and use case, (M3.2.1) Automated loading supports 200 chip arrays, and (M3.3.1) Finish first interconnect process run for 200 chip array. The BP1 Go/No-Go Decision Point (G/NG 1) 200 chip demonstrator sample was in the process of final assembly and test at the end of BP1 on December 31, 2023. The objective was successfully achieved on January 16, 2024, when a wired 200-chip sample underwent confirmation testing that demonstrated a 93.75% first pass electrical yield that successfully exceeded the 75% first-pass electrical yield BP1 G/NG requirement. In addition, all 93.75% of the sample devices lit up, further demonstrating the ability to assemble and transfer small LED chips without damaging their functionality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗
DOE OSTI2021

Impact of Charge Voltage on Factors Influencing Capacity Fade in Layered NMC622: Multimodal X-ray and Electrochemical Characterization

Ni-rich NMC is an attractive Li-ion battery cathode due to its combination of energy density, thermal stability, and reversibility. While higher delivered energy density can be achieved with a more positive charge voltage limit, this approach compromises sustained reversibility. Improved understanding of the local and bulk structural transformations as a function of charge voltage, and their associated impacts on capacity fade are critically needed. Through simultaneous operando synchrotron X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) of cells cycled at 3–4.3 or 3–4.7 V, this study presents an in-depth investigation into the effects of voltage window on local coordination, bulk structure, and oxidation state. These measurements are complemented by ex situ X-ray fluorescence (XRF) mapping and scanning electrochemical microscopy mapping (SECM) of the negative electrode, X-ray photoelectron spectroscopy (XPS) of the positive electrode, and cell level electrochemical impedance spectroscopy (EIS). Initially, cycling between 3 and 4.7 V leads to greater delivered capacity due to greater lithium extraction, accompanied by increased structural distortion, moderately higher Ni oxidation, and substantially higher Co oxidation. Continued cycling at this high voltage results in suppressed Ni and Co redox, greater structural distortion, increased levels of transition metal dissolution, higher cell impedance, and 3× greater capacity fade.

capacity fading mechanisms↗
DOE OSTI2020

A novel improved model for building energy consumption prediction based on model integration

Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems. Moreover, accuracy is no longer the only factor in revealing model performance, it is more important to evaluate the model from multiple perspectives, considering the characteristics of engineering applications. Based on the idea of model integration, this paper proposes a novel improved integration model (stacking model) that can be used to forecast building energy consumption. The stacking model combines advantages of various base prediction algorithms and forms them into “meta-features” to ensure that the final model can observe datasets from different spatial and structural angles. Two cases are used to demonstrate practical engineering applications of the stacking model. A comparative analysis is performed to evaluate the prediction performance of the stacking model in contrast with existing well-known prediction models including Random Forest, Gradient Boosted Decision Tree, Extreme Gradient Boosting, Support Vector Machine, and K-Nearest Neighbor. The results indicate that the stacking method achieves better performance than other models, regarding accuracy (improvement of 9.5%–31.6% for Case A and 16.2%–49.4% for Case B), generalization (improvement of 6.7%–29.5% for Case A and 7.1%-34.6% for Case B), and robustness (improvement of 1.5%–34.1% for Case A and 1.8%–19.3% for Case B). The proposed model enriches the diversity of algorithm libraries of empirical models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations

Solubility of redox-active molecules is an important determining factor of the energy density in redox flow batteries. However, the advancement of electrolyte materials discovery has been constrained by the absence of extensive experimental solubility datasets, which are crucial for leveraging data-driven methodologies. In this study, we design and investigate a highly automated workflow that synergizes a high-throughput experimentation platform with a state-of-the-art active learning algorithm to significantly enhance the solubility of redox-active molecules in organic solvents. Our platform identifies multiple solvents that achieve a remarkable solubility threshold exceeding 6.20 M for the archetype redox-active molecule, 2,1,3-benzothiadiazole, from a comprehensive library of more than 2000 potential solvents. Significantly, our integrated strategy necessitates solubility assessments for fewer than 10% of these candidates, underscoring the efficiency of our approach. Our results also show that binary solvent mixtures, particularly those incorporating 1,4-dioxane, are instrumental in boosting the solubility of 2,1,3-benzothiadiazole. Beyond designing an efficient workflow for developing high-performance redox flow batteries, our machine learning-guided high-throughput robotic platform presents a robust and general approach for expedited discovery of functional materials.

25 ENERGY STORAGE↗
DOE OSTI2025

Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLSs). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12–16 h (relative standard deviation σQi/Qi=13%). These fluctuations are ubiquitous across multiple resonators, chips, and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence, due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations.

Vallières, André [Northwestern U.; Fermilab] (ORCI↗
DOE OSTI2025

Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025

25 ENERGY STORAGE↗
DOE OSTI2023

Discovery and characterization of a selective IKZF2 glue degrader for cancer immunotherapy

Malignant tumors can evade destruction by the immune system by attracting immune-suppressive regulatory T cells (Treg) cells. The IKZF2 (Helios) transcription factor plays a crucial role in maintaining function and stability of Treg cells, and IKZF2 deficiency reduces tumor growth in mice. Here we report the discovery of NVP-DKY709, a selective molecular glue degrader of IKZF2 that spares IKZF1/3. We describe the recruitment-guided medicinal chemistry campaign leading to NVP-DKY709 that redirected the degradation selectivity of cereblon (CRBN) binders from IKZF1 toward IKZF2. Selectivity of NVP-DKY709 for IKZF2 was rationalized by analyzing the DDB1:CRBN:NVP-DKY709:IKZF2(ZF2 or ZF2-3) ternary complex X-ray structures. Exposure to NVP-DKY709 reduced the suppressive activity of human Treg cells and rescued cytokine production in exhausted T-effector cells. In vivo, treatment with NVP-DKY709 delayed tumor growth in mice with a humanized immune system and enhanced immunization responses in cynomolgus monkeys. NVP-DKY709 is being investigated in the clinic as an immune-enhancing agent for cancer immunotherapy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Global mapping of urban thermal anisotropy reveals substantial potential biases for remotely sensed urban climates

Urban thermal anisotropy (UTA) drastically biases satellite-derived urban surface temperatures and fluxes, and consequently inhibits a more comprehensive understanding of global urban climates. However, UTA patterns and associated biases in observed urban climate variables have not been investigated across an adequate number of global cities with diverse contexts; nor is it known whether there are globally measurable factors that are closely related to the UTA intensity (UTAI, quantified as the maximum difference between the nadir and off-nadir urban thermal radiation). Here we investigate the UTAI over more than 5500 cities worldwide using the moderate resolution imaging spectroradiometer (MODIS) multi-angle land surface temperature (LST) observations from 2003 to 2021. The results show that the global mean UTAI can reach 5.1, 2.7, 2.4, and 1.7 K during summer daytime, winter daytime, summer nighttime, and winter nighttime, respectively. Using nadir LST observations as a reference, our analysis reveals that UTA can lead to an underestimation of satellite-based urban surface sensible heat fluxes ( H ) by 45.4% and surface urban heat island intensity ( I s ) by 43.0% when using LST observations obtained from sensor viewing zenith angles (VZAs) of ±60°. However, practitioners can limit the biases of H and I s within ±10% by using LSTs from sensor VZAs within ±30°. We find that UTAI is closely related to urban impervious surface percentage and surface air temperature across global cities. In conclusion, these findings have implications for angular normalization of satellite-retrieved instantaneous LST observations across cities worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Quantifying Trapped Magnetic Vortex Losses in Niobium Resonators at mK Temperatures

Trapped magnetic vortices in niobium introduce microwave losses that degrade the performance of superconducting resonators. While such losses have been extensively studied above 1 K, we report here their direct quantification in the millikelvin and low-photon regime relevant to quantum devices. Using a high-quality factor 3D niobium cavity cooled through its superconducting transition in controlled magnetic fields, we isolate vortex-induced losses and find the resistive component of the sensitivity to trapped flux S to be approximately 2 nOhm/mG at 10 mK and 6 GHz. The decay rate is initially dominated by two-level system (TLS) losses from the native niobium pentoxide, with vortex-induced degradation of T1 occurring above Btrap~50 mG. In the absence of the oxide, even 10 mG of trapped flux limits performance, Q0 ~ 1010, or T1 ~350 ms, underscoring the need for stringent magnetic shielding. The resistive sensitivity, S, decreases with temperature and remains largely field-independent, whereas the reactive component, S , exhibits a maximum near 0.8 K. These behaviors are well modeled within the Coffey Clem framework in the zero-creep limit, under the assumption that vortex pinning is enhanced by thermally activated processes. Our results suggest that niobium-based transmon qubits can tolerate vortex-induced dissipation at trapped field levels up to several hundred mG, but achieving long coherence times still requires careful magnetic shielding to suppress lower-field losses from other mechanisms

Bafia, Daniel P. [Fermilab]↗
DOE OSTI2026

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗
DOE OSTI2021

Protein 4.1R affects photodynamic therapy for B16 melanoma by regulating the transport of 5-aminolevulinic acid

Highlights: • Protein 4.1R knockout promoted the proliferation, migration, and invasion of B16 cells. • Protein 4.1R knockout induced a decrease expression of 5-ALA transporters GAT-1 and GAT-2. • Protein 4.1R knockout reduced the effect of PDT and downregulated the anti-tumor immune response induced by PDT. Melanoma is the most aggressive malignant tumor of skin cancer as it can grow rapidly and metastasize. Photodynamic therapy (PDT) is a promising cancer ablation method for skin tumors, although it lacks efficiency owing to factors such as tumor characteristics, delivery of photosensitizers, immune response in vivo etc. Extensive investigation of molecules that can potentially modulate treatment efficacy is required. Protein 4.1R is a cytoskeletal protein molecule. Previous studies have shown that protein 4.1R knockdown reduces PDT sensitivity in mouse embryonic fibroblast cells. However, the functional role of protein 4.1R in melanoma is unclear. In this study, we aimed to elucidate the effect of protein 4.1R on PDT for melanoma in mice and the mechanism of anti-tumor immunity. Our results indicated that CRISPR/Cas9-mediated protein 4.1R knockout promotes the proliferation, migration, and invasion of B16 cells. We further investigated the potential mechanism of protein 4.1R on tumor cell PDT sensitivity. Our results showed that protein 4.1R knockout reduced the expression of membrane transporters γ-aminobutyric acid transporter (GAT)-1 and (GAT)-2 in B16 cells, which affected 5-ALA transmembrane transport and reduced the efficiency of PDT on B16 cells. Protein 4.1R knockout downregulated the anti-tumor immune response triggered by PDT in vivo. In conclusion, our data suggest that protein 4.1R is an important regulator in PDT for tumors and may promote the progress and efficacy of melanoma treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Future changes in isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) under the Shared Socioeconomic Pathways: the importance of physicochemical dependency

Abstract. Secondary organic aerosol (SOA) is a dominant contributor of fine particulate matter in the atmosphere, but the complexity of SOA formation chemistry hinders the accurate representation of SOA in models. Volatility-based SOA parameterizations have been adopted in many recent chemistry modeling studies and have shown a reasonable performance compared to observations. However, assumptions made in these empirical parameterizations can lead to substantial errors when applied to future climatic conditions as they do not include the mechanistic understanding of processes but are rather fitted to laboratory studies of SOA formation. This is particularly the case for SOA derived from isoprene epoxydiols (IEPOX SOA), for which we have a higher level of understanding of the fundamental processes than is currently parameterized in most models. We predict future SOA concentrations using an explicit mechanism and compare the predictions with the empirical parameterization based on the volatility basis set (VBS) approach. We then use the Community Earth System Model 2 (CESM2.1.0) with detailed isoprene chemistry and reactive uptake processes for the middle and end of the 21st century under four Shared Socioeconomic Pathways (SSPs): SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5. With the explicit chemical mechanism, we find that IEPOX SOA is predicted to increase on average under all future SSP scenarios but with some variability in the results depending on regions and the scenario chosen. Isoprene emissions are the main driver of IEPOX SOA changes in the future climate, but the IEPOX SOA yield from isoprene emissions also changes by up to 50 % depending on the SSP scenario, in particular due to different sulfur emissions. We conduct sensitivity simulations with and without CO2 inhibition of isoprene emissions that is highly uncertain, which results in factor of 2 differences in the predicted IEPOX SOA global burden, especially for the high-CO2 scenarios (SSP3–7.0 and SSP5–8.5). Aerosol pH also plays a critical role in the IEPOX SOA formation rate, requiring accurate calculation of aerosol pH in chemistry models. On the other hand, isoprene SOA calculated with the VBS scheme predicts a nearly constant SOA yield from isoprene emissions across all SSP scenarios; as a result, it mostly follows isoprene emissions regardless of region and scenario. This is because the VBS scheme does not consider heterogeneous chemistry; in other words, there is no dependency on aerosol properties. The discrepancy between the explicit mechanism and VBS parameterization in this study is likely to occur for other SOA components as well, which may also have dependencies that cannot be captured by VBS parameterizations. This study highlights the need for more explicit chemistry or for parameterizations that capture the dependence on key physicochemical drivers when predicting SOA concentrations for climate studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination↗
DOE OSTI2020

Micro-XRF mapping and quantitative assessment of Cd in rice ( Oryza sativa L.) roots

Understanding Cd uptake and distribution in rice roots is important for breeding varieties that do not accumulate Cd in the grain to any large extent. Here, we examined the physiological and molecular factors responsible for Cd uptake and transport differences between two japonica rice cultivars prescreened as high (zhefu7) or low (Xiangzaoxian45) accumulators of Cd in the grain. No significant differences in Cd uptake between the two cultivars were observed; however, Xiangzaoxian45 retained most of the absorbed Cd in the roots, whereas zhefu7 showed higher transport of Cd from the root to the shoot, regardless of the duration of exposure to Cd. The inability to sequester Cd into root vacuoles caused high accumulation of Cd in the grain in zhefu7, whereas inefficient transport of Cd from roots to shoots in Xiangzaoxian45 caused low accumulation of Cd in the grain. Cd sequestration in the roots and transport from the root to the shoot were greatly influenced by the expression patterns of transport-related genes OsHMA3 and OsHMA2, respectively. Further, micro-X-ray fluorescence spectroscopy mapping confirmed that more Cd was sequestered in the roots of Xiangzaoxian45 than in those of zhefu7, with a significant amount of Cd localized in the root hairs, as well as in the meristematic and elongation zones, and dermal and stele tissues. Finally, we propose that effective Cd sequestration in root vacuoles was the major determinant of divergent Cd-accumulation patterns in the two rice cultivars under study.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

IFNgamma-inducible CXCL10/CXCR3 axis alters the sensitivity of HEp-2 cells to ionizing radiation

Highlights: • IFNgamma/CXCL10/CXCR3 are necessary for effective IR-induced HEp-2 cell killing. • Local IR showed fewer effects on tumor burden in mice carrying CXCL10-KO xenografts. • Loss of CXCL10 showed blockage in the G0/G1 phase when exposed to a moderate dose of IR. Radiotherapy is a conventional approach for anti-cancer treatment, killing tumor cells through damaging cellular DNA. While increasing studies have demonstrated that tumors generated the tolerance to radiation and tumor immune system was found to be correlated to radiotherapy resistance. Therefore, it is critical to identify potential immune factors associated with the efficacy of radiotherapy. Here in this study, we evaluated the sensitivities of different tumor cells to radiation and determined HEp-2 cells as the radio-resistant tumor cells for further investigation. IFNgamma as a key regulator of host immune response showed the potential to sensitize tumors to ionizing radiation (IR). Besides, IFNgamma-induced CXC chemokine ligand 10 (CXCL10) was found to be necessary for effective IR-induced killing of cultured HEp-2 cells. Increased clonogenic survival was observed in CXCL10-depleted HEp-2 cells and CXCL10-KO cells. Additionally, the loss of CXCL10 in HEp-2 cells showed less progression of the G0/G1 phase to G2/M when exposed to IR (8 Gy). Local IR (20 Gy) to nude mice bearing HEp-2 tumors significantly reduced tumor burden, while fewer effects on tumor burden in mice carrying CXCL10-KO tumors were observed. We furtherly evaluated the possible roles the chemokine receptor CXCR3 plays in mediating the sensitivity of cultured HEp-2 cells to IR. Altered expression of CXCR3 in HEp-2 cells affected IR-induced killing of HEp-2 cells. Our data suggest the IFNgamma-activated CXCL10/CXCR3 axis may contribute to the effective radiation-induced killing of HEp-2 cells in vitro.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Mechanistic understanding of support effect on the activity and selectivity of indium oxide catalysts for CO 2 hydrogenation

Herein we present a mechanistic study on the support effect (ZrO 2 and CeO 2 ) of In 2 O 3 catalysts in CO 2 hydrogenation by a combined experimental and computational approach. Kinetic experiments and surface characterization suggested that the activity of In 2 O 3 catalysts cannot be simply correlated with the abundance of surface oxygen vacancies (O v ) formed by either H 2 -reduction or thermal treatment, which has been frequently invoked in previous studies. The support effect should originate from the electronic interactions between In 2 O 3 and the support oxide, rather than geometric factors or the difference in the particle size of In 2 O 3 . Theoretical modelling revealed that surface O v facilitate the formation and stabilization of the formate (HCOO*) intermediate. While a carbonate-like structure is favored for CO 2 adsorption on CeO 2 -supported or unsupported In 2 O 3 catalysts, CO 2 tends to bind strongly in a bent configuration on the O v site at the In 2 O 3 -ZrO 2 interface. The distinct CO 2 adsorption structures on different supported In 2 O 3 catalysts may account for the different reaction energy profiles in the subsequent hydrogenation reactions, especially the rate-limiting step, i.e., hydrogenation of HCOO* to CH 2 O* and methoxy (CH 3 O*). The relatively higher methanol selectivity of In 2 O 3 catalyst supported on ZrO 2 with respect to that on CeO 2 are suggested to stem from the greater energy difference (Δ$E_a$) between the parallel hydrogenation and C-O bond cleavage of HCOO*, which leads to the formation of methanol and CO, respectively. We report this study underlines the important role of metal-oxide-interface in determining the catalytic behavior of oxide-supported In 2 O 3 catalysts in CO 2 conversion.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Dynamic P-Q Capability and Abnormal Operation Analysis of a Wind Turbine with Doubly-Fed Induction Generator

After several accidents occurred in wind farms in the United States and around the world, the subsynchronous oscillation (SSO) issues in grid-connected wind farms have gained serious attention. Particularly, these issues have caused significant challenges to wind turbines with a doubly fed induction generator (DFIG) because it is connected to the grid via both its stator and rotor paths. Traditionally, a P-Q capability chart is utilized to assure the safe operation boundary for a synchronous generator. But the energy conversion characteristics of a DFIG wind turbine are completely different. A critical factor to affect the reliable operation of a DFIG wind turbine is the rated current and pulse-width modulation (PWM) saturation constraints of its power converters. These constraint conditions can be affected by the wind turbine rotating speed and grid conditions. However, a detailed study of DFIG P-Q capability from these perspectives has not been conducted, which has hindered adequate understanding of many abnormal wind turbine operations reported in the literature and the development of advanced control technologies to overcome the challenges. The proposed study in this paper considers vector control implementation to DFIG power electronic converters in the dq reference frame, and the models and algorithms developed for the P-Q capability study have addressed specific DFIG power converter constraints that are different from those of a traditional synchronous generator. The paper especially focuses on exploring the dynamic natures of DFIG P-Q capability under uncertain and variable conditions to explore the root causes of many abnormal operations of DFIG wind turbines reported in the literature. The proposed study is validated through an electromagnetic transient simulation model of a grid-connected DFIG wind turbine. The proposed study has the potential to lead to the development of new DFIG control technologies that can help overcome the challenges for many abnormal operations of DFIG wind turbines.

17 WIND ENERGY↗