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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Establishing defect-property relationships for 2D-nanomaterials (Final technical report)

Studies of new families of two-dimensional nanomaterials (2DNMs) have established that they possess unique properties that diverge from those of their bulk counterparts. This project aimed to determine how tolerant 2DNMs are to extreme photon and particle fluxes and to identify the mechanisms governing their radiation response. Early work indicated that graphene is not as representative of other 2DNMs as previously assumed; however, the origin of this difference remained unclear. To address these knowledge gaps, this project investigated the physical processes occurring at multiple length scales in transition metal dichalcogenides (TMDs) and quantified their structural stability and property evolution under far-from-equilibrium conditions. In-situ and ex-situ ion and electron irradiations were performed to directly control and monitor defect formation in TMDs. Complementary density functional theory (DFT) and molecular dynamics (MD) simulations were employed to elucidate the mechanisms of defect generation and evolution. The outcomes of this work established mechanistic understanding of irradiation-induced defect formation in 2DNMs, quantified the radiation tolerance of TMDs, and built a fundamental knowledge base for correlating defect structures with material properties. Collectively, these results provide new insights into the stability of low-dimensional materials in extreme environments and enable the predictive design of radiation-tolerant 2DNMs.

2D materials↗
DOE OSTI2025

Abbr. Final report: Self-assembled molecular containers as artificial water channels: towards biomimetic desalination membranes

Global water scarcity demands advances in desalination technologies that can deliver more fresh water with less energy. Current reverse osmosis membranes are fundamentally limited by a trade-off between how much water they can pass and how well they block salts. To address this challenge, we developed a bottom-up strategy to design and test artificial water channels that mimic the efficiency of biological proteins but are built from robust synthetic molecules. Over two years, we synthesized and evaluated more than twenty molecular channel candidates, including supramolecular macrocycles and nanographene pores with atomically precise structures. We showed that small chemical modifications allow direct control over pore size and chemistry, which in turn govern water permeability and salt rejection. In collaboration with university partners, we reported the first experimental demonstration of water transport through a nanographene pore, bridging a long-standing gap between simulation and experiment. Several of the artificial channels we developed achieved water–salt selectivity beyond conventional polymer membranes, highlighting their potential for next-generation desalination and precision separations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗
DOE OSTI2025

High Power Density, Carbon Neutral Electrical Power Generation for Air Vehicles

The synergistic integration of a Solid Oxide Fuel Cell-Combustor (SOFC-C) with a turbogenerator (TG) will provide a very high fuel-to-electricity conversion efficiency while maintaining high power-to-weight ratio during high-altitude flight. The proposed SOFC-C-TG power generation technology exceeds the REEACH technical performance targets (TPT). This unique concept addresses many of the challenges faced in all electric propulsion-based aviation. The system has high part-load efficiency (more than 65% lower heating value (LHV)) during long cruise times, load following capability, high-power capacity at high altitudes adapting to low temperatures and pressures, rapid startup time of less than 30 minutes (proven with current SOFC technology), high power density (more than 3.2 kW/kg), efficient thermal management, and a foundation for a compact, efficient electrical storage and power generation system (ESPG). The SOFC-C concept achieves the technology targets by reducing the complexity of traditional fuel cell-gas turbine hybrid systems (FC-GT). The SOFC-C does not require heat exchangers and dramatically reduces the balance of plant increasing power density and performance in efficiency. The reduction in mass through elimination of heat exchangers, external reformer, and other components dramatically decreases the overall thermal dampening of the system which enables rapid startup and load following capability. Direct control of the cathode inlet temperature of the SOFC-C enables rapid warm-up of the SOFC tubes with the ability to reach operating temperature and full power in less than 30 minutes.

03 NATURAL GAS↗
DOE OSTI2026

Thermodynamic Control of Interface Directs MnO 2 Nucleation Chemistry for Dense and Conformal Electrodeposition

Manganese dioxide (MnO 2 ) is widely recognized as a promising material for high-energy-density energy storage systems due to its broad applicability and facile electrodeposition. However, achieving uniform, thin, and high-mass-loading MnO 2 coatings on high-surface-area electrodes remains a significant challenge. Conventional electrodeposition methods typically yield nonuniform, thick layers with poor conductivity and limited material utilization, restricting their practical use. Here, we uncover a thermodynamically engineered vanadyl/pervanadyl (VO 2+ /VO 2 + ) interface that fundamentally reshapes MnO 2 electrodeposition chemistry, enabling highly uniform and dense coatings. Here, combining in situ AFM measurement, Classical Nucleation Theory, and Johnson–Mehl–Avrami–Kolmogorov modeling, we show that this interface reduces early-stage detectable MnO 2 island size by 35-fold and shifts the MnO 2 growth from diffusion-limited to reaction-limited progressive nucleation. This thermodynamically controlled interface yields highly dense and conformal MnO 2 films with record-high mass loading of 241 mg cm –2 (1607 mg cm –3 ) on 3D-printed graphene aerogels, without compromising porosity or inducing thickness gradient. As a prototype demonstration, the resulting MnO 2 electrodes deliver record-setting volumetric performance in both capacitors (106 F cm –3 ) and Zn//MnO 2 pouch cells (162 mAh cm –3 ). Beyond energy storage, our findings demonstrate the significance of thermodynamic interface control in MnO 2 nucleation chemistry for achieving dense and uniform coatings on various substrates, with implications for electrocatalysis, semiconductor processing, and advanced materials manufacturing.

Batteries↗
DOE OSTI2025

Stochastic Model Predictive Control With Gaussian Wind Direction Preview for Wake Steering

This article addresses the problem of wake steering control for wind farms that explicitly consider the tradeoff between farm-level power generation and yaw duty cycle under variable and uncertain wind conditions. A novel stochastic model predictive control (MPC) algorithm is presented, which utilizes a stochastic model of the freestream wind field components in a receding horizon framework to compute optimal yaw set points that maximize the expected value of the farm power while constraining the yaw actuation. Different configurations of the algorithm are evaluated using a steady-state wind farm simulator. The proposed stochastic MPC algorithm can plan control actions over a future prediction horizon based on probabilistic estimates of the incoming wind magnitude and direction.

17 WIND ENERGY↗
DOE OSTI2025

Electronic Structure Progression across the ACu 2 Q 2 (MQ 2 ) n Semiconductor Series

Moving beyond the engineering of known materials and elemental substitution within common structure types is critical for designing unique properties. Here, we present a new homologous series, ACu 2 Q 2 (MQ 2 ) n (A = Sr, Ba, 2Na; MQ 2 = ZrS2, HfSe 2 ), establishing 11 new members. In β-BaCu 2 Q 2 and Na 2 Cu 2 Se 2 (n = 0), the [Cu 2 Q 2 ] 2– motifs extend in two dimensions, whereas those in α-BaCu 2 Q 2 extend in three dimensions. Hence, there are two structural evolutions within the ACu 2 Q 2 (MQ 2 )n family driven by the polymorphism of the host structures. MQ 2 (n → ∞) displays 2D layers of edge-sharing [MQ 6 ] 8– octahedra that are 1-octahedron-thick and connected via van der Waals bonding. Each insertion of MQ 2 into ACu 2 Q 2 incorporates [MQ 6 ] 8– octahedra extending infinitely in one direction, confined to being 1-octahedron-thick in the second direction, with n controlling the number of [MQ 6 ] 8– octahedra in the third direction. Therefore, increasing n predictively expands the [Cu 2 MnQ 2n+2 ] 2– network in the direction controlled by n and relative to the A + /A 2+ ions. We demonstrate that for a given set of elements, one can enforce a “Host(Insertion)n” formula to systematically evolve both crystal and electronic structures from the host (n = 0) to the insertion (n → ∞) materials through intermediate values of n. Specifically, the energetic misalignment of the electronic band extrema of the parents predictively determines the band extrema and the resulting band gaps of all intermediate n members.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Extended State Observer-Based Robust Model Predictive Velocity Control for Permanent Magnet Synchronous Motor

This article proposes an extended state observer based robust model predictive velocity control to decrease system prediction error under parameter uncertainties for permanent magnet synchronous motor (PMSM). We develop a new PMSM model that consists of velocity and acceleration to lump the system information and an external disturbance into a disturbance. The extended state observer (ESO) is designed to estimate the velocity, acceleration, and disturbance. By estimating the state variables and disturbance using the ESO, the model predictive control (MPC) finds the optimal control input by predicting future system behavior. Additionally, the direct current controller is designed so that the direct current converges to zero. Because the proposed method is not designed based on the cascade structure from the viewpoint of velocity control, the optimization control for the velocity and currents can be defined. Thus, the proposed method is robust against external disturbances and parameter uncertainties owing to feedback linearization, state feedback, and ESO-based MPC using the acceleration PMSM model. The proposed control algorithm was experimentally verified and it showed improved velocity tracking performance compared with ESO-based MPC using the conventional PMSM model.

42 ENGINEERING↗
DOE OSTI2024

Instant Startup and Grid Synchronization of Inverter Based Resources

This paper introduces an innovative approach for instant startup of inverter-based resources (IBRs), which attains synchronization with the grid via the already embedded direct current feedback control. The startup process utilizes direct current control throughout each switching cycle, enabling a process that is free from inrush current. Uniquely, this method determines the grid phase angle by evaluating the current differences across switching cycles, a significant difference from traditional methods that often rely on grid or points of common coupling (PCC) voltage. An analytical model has been constructed, highlighting that the grid phase angle can be obtained in just two switching cycles. The paper details the principle of instant grid synchronization and presents both simulation and experimental results to substantiate the proposed method.

He, Yuchen↗
DOE OSTI2026

Substrate-Directed Dimensional and Phase Control of Peptide Assemblies on Two-Dimensional van der Waals Materials

Understanding and controlling biomolecular self-assembly on van der Waals (vdW) materials has the potential to advance hybrid bioelectronic devices by enabling precise tuning of the interface and modulation of the resulting electronic properties of the biomolecule-vdW heterostructure. However, how surface properties of vdW materials direct biomolecule assembly remains poorly understood. To fill this knowledge gap, we investigated the assembly of a peptide known to assemble into two-dimensional (2D) crystalline films on MoS 2 on three representative vdW surfaces: WS 2 , MoS 2 , and highly oriented pyrolytic graphite (HOPG). Using in situ atomic force microscopy (AFM), we find that assembly is substrate-dependent, resulting in multilayers on WS 2 , monolayers on MoS 2 , and multiple coexisting phases on HOPG. WS 2 exhibits a higher negative charge, strong long-range electrostatic interactions, and extensive hydration layering that may promote multilayer stacking. In contrast, MoS 2 has stronger short-range interactions with the peptides but much weaker long-range interactions and hydration structure, which may favor monolayer formation. Molecular dynamics simulations predict a corresponding switch from monolayer to multilayer aggregates of the adsorbed monomers, reflected in their relative mobilities. On hydrophobic HOPG, the peptides bind most strongly and remain as monomers with high surface mobility. The peptide dimers comprising the basic unit of the crystals are more compact on HOPG, which has a smaller lattice constant than WS 2 or MoS 2 , suggesting strain contributes to stabilizing multiple phases. Our results provide mechanistic insights into how surface charge and hydration structure, and the lattice structure of the substrates governs peptide assembly on vdW materials, offering a framework to rationally control the 2D peptide-vdW heterostructures.

Molecular dynamics simulations↗
DOE OSTI2024

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry↗
DOE OSTI2024

DIRECT RF SAMPLING BASED LLRF CONTROL SYSTEM FOR C-BAND LINEAR ACCELERATOR

Low Level RF (LLRF) control systems of linear accel- erators (LINACs) are typically implemented with hetero- dyne based architectures, which have complex analog RF mixers for up and down conversion. The Gen 3 Radio Fre- quency System-on-Chip (RFSoC) device from AMD Xilinx integrates data converters with maximum RF frequency of 6 GHz. This enables direct RF sampling of C-band LLRF signal typically operated at 5.712 GHz without any analogue mixers, which can significantly simplify the system architec- ture. The data converters sample RF signals in higher order Nyquist zones and then up or down convert digitally by the integrated data path in RFSoC. The closed-loop feedback control firmware implemented in FPGA integrated in RF- SoC can process the base-band signal from the ADC data path and calculate the updated phase and amplitude to be up- mixed by the DAC data path. We have developed a C-band LLRF control RFSoC platform with direct RF sampling, which targets Cool Copper Collider (𝐶3) and other C or S band LINAC research and development projects. In this paper, the architecture of the platform will be described. We have optimized the configuration of the data converter and characterized performance of them with RF pulses. The test results for some of the key performance parameters for the LLRF platform with our custom solid-state amplifier, such as phase and amplitude stability, will be discussed in this paper.

Liu, C↗
DOE OSTI2025

Degrees of rate control and AutoDiff-driven direct sensitivity analysis in heterogeneous catalysis

Despite the wide application and benefits of the degree of rate control (DRC) analysis, several details remain argued, particularly about the conservation of DRCs at transient (TR) and steady-state (SS) conditions, especially for complex reaction networks. This work argues that previous proofs about the conservation properties of DRCs have been incomplete, and we provide new mathematical proofs at TR and SS conditions. In addition, we use both analytical (automatic differentiation) and numerical (finite difference) approaches to compute DRCs for the case study of ethane hydrogenolysis (EH) over Pt(111). This work confirms that at both TR and SS conditions, the sum of all DRCs, i.e., sum of the degrees of kinetic (DKRC) and thermodynamic rate control (DTRC), is conserved at zero. At SS conditions, the sum of DKRC is conserved at 1 while the sum of DTRC is conserved at −1. In corroboration of previous works, we show that the DTRC for any adsorbate at SS is equal to the product of the species coverage and a constant. In contrast, at TR conditions, the individual sums of both DTRC and DKRC are not conserved and can be any real number, with potential implications for the novel field of dynamic catalysis. Finally, we show that the conventional finite difference (FD) approach, only useful at SS, is prone to inaccuracy and very sensitive to the value of the differential change applied. The optimal differential value also varies significantly with system and rate definition. Consequently, we describe and illustrate in this work the application of the automatic differentiation (AD) approach for the more accurate determination of DRCs at both TR and SS conditions.

Automatic differentiation↗
DOE OSTI2026

How Improved Forecasting Can Increase the Bulk Power System Value of Price-Responsive Electric Vehicle Managed Charging

Personal light-duty vehicle (LDV) electric vehicle managed charging (EVMC) can reduce power system costs by better aligning electric vehicle (EV) charging with locations and times of low energy cost or infrastructure use. The need to coordinate charging demand across thousands to millions of vehicles while preserving mobility service is a barrier to realizing the value of EVMC. Price-responsive dispatch mechanisms like time-of-use rates (TOU) and hourly real-time prices (RTP) are attractive compared to direct load control (DLC) because they only require one-way communications and local controls. However, increasing participation in price responsive mechanisms can induce costly-to-serve spikes in load and otherwise increase, rather than decrease, production costs. We quantify the ability of improved EVMC forecasting to sustain savings from price responsive mechanisms beyond the limit of 14% of LDVs actively participating observed in previous work. Perfect forecasting of price-responsive EV load makes TOU and RTP value-competitive with a low-error DLC formulation with up to 27% (within-week flexibility) to 45% or more (within-session flexibility) of LDVs participating in EVMC in an envisioned New England power system with 84% clean energy. Additional costs of implementing DLC should be no more than tens of dollars per vehicle-year if DLC is to be value-competitive with accurately forecast price-responsive EVMC for double-digit percentage shares of LDVs participating.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

A Scalable, Distribution Network-Aware, Customer Privacy-Preserving Framework for Operation of Virtual Power Plants

This poster presents a hierarchical control framework for a virtual power plant that leverages behind-the-meter resources for grid services while maintaining customer privacy during setpoint disaggregation. Unlike many existing approaches, the virtual power plant model uses a hierarchical control strategy and an iterative approach to determine the optimal set point dis-aggregation without direct load control while maintaining system-level power flow and voltage constraints. The proposed approach is numerically validated on a synthetic distribution feeder in San Francisco, demonstrating the ability of the framework to provide privacy-preserving virtual power plant services.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗