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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluation of fluxon synapse device based on superconducting loops for energy efficient neuromorphic computing

With Moore’s law nearing its end due to the physical scaling limitations of CMOS technology, alternative computing approaches have gained considerable attention as ways to improve computing performance. Here, we evaluate performance prospects of a new approach based on disordered superconducting loops with Josephson-junctions for energy efficient neuromorphic computing. Synaptic weights can be stored as internal trapped fluxon states of three superconducting loops connected with multiple Josephson-junctions (JJ) and modulated by input signals applied in the form of discrete fluxons (quantized flux) in a controlled manner. The stable trapped fluxon state directs the incoming flux through different pathways with the flow statistics representing different synaptic weights. We explore implementation of matrix–vector-multiplication (MVM) operations using arrays of these fluxon synapse devices. We investigate the energy efficiency of online-learning of MNIST dataset. Our results suggest that the fluxon synapse array can provide ~100× reduction in energy consumption compared to other state-of-the-art synaptic devices. This work presents a proof-of-concept that will pave the way for development of high-speed and highly energy efficient neuromorphic computing systems based on superconducting materials.

42 ENGINEERING↗
DOE OSTI2026

A High Power Density and High Efficiency Traction Drive Based on a Segmented Inverter and an Axial and Radial Flux Hybrid Machine

Eaton Corporation and Oak Ridge National Laboratory (ORNL) collaborated to develop a high performance traction drive system aimed at increasing power density and overall efficiency. The system integrates Eaton’s hybrid flux motor—combining radial and axial flux paths to convert end-winding and structural elements into torque-producing components—with ORNL’s high-power-density segmented inverter. This motor design achieves higher torque density within the same footprint as traditional radial flux machines by effectively utilizing end turns. ORNL’s segmented inverter reduces the DC bus capacitor requirement by over 50% compared to standard voltage source inverters (VSIs), achieving power densities exceeding 100 kVA/L. The dual-module architecture also enables six-phase operation, aligning with Eaton’s motor design. Together, the motor and inverter offer a compact, efficient traction drive system with the potential for significant reductions in system weight and improvements in powertrain efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Manipulating symmetry-breaking charge separation employing molecular recognition

The exploration of symmetry-breaking charge separation (SB-CS) is imperative when designing functional light-harvesting materials. Past explorations, however, have been confined to covalent systems, more often than not requiring complicated/demanding syntheses and facing inconvenient regulation of charge transfer processes. Here, in this work, we present a concept that regulates the efficiency of SB-CS through molecular recognition utilizing a pyridinium-based cyclophane as a host. This host undergoes photo-driven excited-state SB-CS. By employing different guests with distinct frontier molecular orbital energy levels, we have achieved comprehensive control of electron transfer pathways in the cyclophane, modulating between accelerated (>10-fold) intramolecular SB-CS involving superexchange and direct intermolecular electron transfer between the host and guest. The improvement in SB-CS efficiency results in catalytic activity for the photo-oxidation of a sulfur-mustard simulant. This research offers an opportunity for tuning SB-CS by utilizing molecular recognition, which holds the potential for achieving precise regulation without complicated organic syntheses.

charge transfer↗
DOE OSTI2020

High-Performance Thermoelectric Generators for Field Deployments

Thermoelectric power generation is a reliable energy harvesting technique for directly converting heat into electricity. Recent studies have reported the thermal-to-electrical energy conversion efficiency of thermoelectric generators (TEGs) up to 11% under laboratory settings. However, the practical effectiveness of TEGs deployed under real environments is still not more than a few percent. In this study, we provide fundamental insight on the operation of TEGs in realistic environments by illustrating the combinatory effect of thermoelectric material properties, device boundary conditions, and environmental thermal resistivity on TEG performance in conjunction with the module parameters. Using numerical and experimental studies, we demonstrate the existence of a critical heat transfer coefficient that dramatically affects the design and performance of TEGs. Results provide a set of concrete design criteria for developing efficient TEGs that meet the metrics for field deployments. High-performance TEGs demonstrated in this study generated up to 28% higher power and 162% higher power per unit mass of thermoelectric materials as compared to the commercial module deployed for low-grade waste heat recovery. This advancement in understanding the TEG operation will have a transformative impact on the development of scalable thermal energy harvesters and in realizing their practical targets for efficiency, power density, and total output power.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Modulation of Photoinduced Iodine Expulsion in Mixed Halide Perovskites with Electrochemical Bias

Hole trapping at iodine (I) sites in MAPbBr 1.5 I 1.5 mixed halide perovskites (MHP) is responsible for iodine migration and its eventual expulsion into solution. We have now modulated the photoinduced iodine expulsion in MHP through an externally applied electrochemical bias. At positive potentials, electron extraction at TiO 2 /MHP interfaces becomes efficient, leading to hole buildup within MHP films. This improved charge separation, in turn, favors iodine migration as evident from the increased apparent rate constant of iodine expulsion (k expulsion = 0.0030 s –1 ). Conversely, at negative potentials (-0.3 V vs Ag/AgCl) electron–hole recombination is facilitated within MHP, slowing down iodine expulsion by an order of magnitude (k expulsion = 0.00018 s –1 ). The tuning of the EFermi level through external bias modulates electron extraction at the TiO 2 /MHP interface and indirectly controls the buildup of holes, ultimately inducing iodine migration/expulsion. Suppressing iodine migration in perovskite solar cells is important for attaining greater stability since they operate under internal electrical bias.

14 SOLAR ENERGY↗
DOE OSTI2025

Air‐Stable High‐Voltage Li‐Ion Organic Cathode Enabled by Localized High‐Concentration Electrolyte

While lithium‐ion batteries have revolutionized the field of energy storage, their reliance on critical minerals such as cobalt and nickel raises significant concerns over resource availability and supply chain uncertainty. In this study, we revisit dithiin‐fused dilithium naphthazarin (5,8‐dihydroxy‐1,4‐naphthoquinone) (DNP‐Li) as a high‐voltage Li‐ion organic cathode and evaluate its performance in conjunction with localized high‐concentration electrolyte (LHCE). DNP‐Li exhibits remarkable air and thermal stability, a high operating potential of 3.55 V vs. Li + /Li, and a specific capacity of 232 mAh g −1 , positioning it as one of the most promising candidates among Li‐ion organic cathodes. Furthermore, the electrochemical behavior of DNP‐Li is strongly influenced by the electrolyte composition, giving distinct two‐plateau or four‐plateau voltage profiles accompanied by reversible or irreversible phase transitions in carbonate‐based or LHCE electrolyte formulations, respectively. The reduced solubility of DNP‐Li‐based redox intermediates in LHCE enhances cycling stability, achieving a capacity retention of 85% after 50 cycles at 0.1C and 75% after 160 cycles at 0.5C, demonstrating a significant improvement compared to the carbonate‐based electrolyte. This work highlights the critical role of solute–electrolyte interactions in modulating the electrochemical performance of multielectron small‐molecule organic cathodes, offering new pathways for advancing sustainable and high‐efficiency energy storage technologies.

Lakraychi, Alae Eddine [Department of Electrical a↗
DOE OSTI2025

OpenEdge: A collaborative, open-source, multi-purpose direct simulation Monte Carlo for plasma simulation in magnetic fusion environments

OpenEdge is a collaborative, open-source, object-oriented Direct Simulation Monte Carlo (DSMC) code, designed specifically for plasma simulations in magnetic fusion environments. Here, the code features include advanced structures, robust capabilities, and an effective parallelization strategy, all of which significantly enhance performance. It includes specialized modules for managing complex particle interactions, including collisions, ionization/recombination, and reflection/sputtering. Benchmarks and performance analyses have confirmed its efficiency and scalability. Versatile and adaptable, OpenEdge is applied across a broad spectrum of plasma-material interaction studies and charged particle transport in various fusion research settings.

Boundary plasma↗
DOE OSTI2022

Optimal design of multi-stage vacuum membrane distillation and integration with supercritical water desalination for improved zero liquid discharge desalination

Herein this paper proposes a novel concept for the optimal design of multi-stage vacuum membrane distillation (VMD). Generally, a multi-stage VMD is designed with an equal temperature difference between each stage. However, such a design is energy inefficient and increases VMD area. An analytical methodology for calculating the optimal stage temperature is proposed. By selecting the optimal stage temperature, the energy efficiency and required membrane area can be potentially improved by 16% and 30%, respectively. The proposed concept applies to all heat sources, including latent, sensible, and waste heat. To illustrate the method, multi-stage VMD is integrated with the waste heat from a supercritical water desalination (SCWD) system to achieve zero liquid discharge. SCWD is an energy-intensive process, requires high-quality thermal heat (>450 °C), and exhibits high waste heat rejection. The integrated VMD-SCWD approach is approximately 50% more energy-efficient and 35% more cost-efficient than the standalone SCWD system. Compared to the commercially used brine concentrator and crystallizer, the multi-stage VMD-SCWD system is more energy efficient for feed concentrations >5%. VMD-SCWD system is 30% cheaper, due to less expensive membrane distillation modules compared to a brine concentrator. The proposed design concept can replace the brine concentrator and crystallizer as an improved alternative for a zero-liquid discharge desalination system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tuning the Wettability of Metal–Organic Frameworks via Defect Engineering for Efficient Oil/Water Separation

Zirconium-based metal–organic frameworks (MOFs) have attracted interest due to their chemical and thermal stabilities and structural tunability. In this article, we demonstrate the tuning of the wettability of a UiO-66 structure via defect-engineering for efficient oil/water separation. UiO-66 crystals with controlled levels of missing-linker defects were synthesized using a modulation approach. As a result, the hydrophilicity of the defect-engineered UiO-66 (d-UiO-66) can be varied. In addition, a thin layer of hydrophilic d-UiO-66 was successfully fabricated on a series of stainless steel meshes (d-UiO-66@mesh), which exhibited excellent superhydrophilic and underwater superoleophobic properties and displayed interesting separation performance for various oil/water mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tailoring the Intermediate Phase to Control Formation of γ‑CsPbI3 Films

Controlling the crystallization pathway of inorganic CsPbI3 perovskite is essential for achieving high efficiency and stability in optoelectronic devices. Here, we report a solvent-engineering strategy that combines an antisolvent process with vacuum treatment (AVT) to modulate evaporation dynamics of the precursor, guiding the formation of highly oriented (CH3)2NH2PbI3 (DMAPbI3) and Cs4PbI6 intermediate phases. Synchrotron and in situ analyses revealed correlations between intermediate orientation and γ-CsPbI3 crystallinity. This directional crystallization pathway promotes vertical alignment and grain enlargement in γ-CsPbI3 films, resulting in fewer voids, lower defect densities, and reduced tensile strain. Photovoltaic devices based on AVT-processed films achieved a power conversion efficiency of 18.47% with a fill factor of 83.14% and retained 101.9% of their initial efficiency after 526 h without encapsulation. This study first reports that the quality of DMAPbI3 and Cs4PbI6 intermediates, controlled by combination of antisolvent and vacuum treatment, plays a crucial role in achieving high-quality γ-CsPbI3 films.

Yoon, Geon Woo↗
DOE OSTI2020

Improving Energy Transfer within Metal–Organic Frameworks by Aligning Linker Transition Dipoles along the Framework Axis

Crystalline metal-organic frameworks (MOFs) can assemble chromophoric molecules into a wide range of spatial arrangements, which are controlled by the MOF topology. Like natural light-harvesting complexes (LHCs), the precise arrangement modulates interchromophoric interactions, in turn determining excitonic behavior and migration dynamics. To unveil the key factors that control efficient exciton displacements within MOFs, we first developed linkers with low electronic symmetry (as defined by large transition dipoles) and then assembled them into MOFs. These linkers possess extended conjugation along one molecular axis, engendering low optical bandgaps and improved oscillator strength for their lowest-energy transition (S 0 → S 1 ). This enhances absorption-emission spectral overlap and boosts the efficiency of Forster resonance energy transfer, which was observed experimentally by a sizable decrease in emission quantum yield (QY), accompanied by a faster population decay profile. We find that MOFs that orient these elongated linkers along their asymmetric pore channel, e.g., the hexagonal pores in an xly network, manifested >50% decrease in their emission QY with faster decay profiles relative to their corresponding solution dissolved linkers. This is due to an efficient migration of photogenerated excitons at the crystallite peripheral sites to internal sites, which was facilitated by polarized absorption-emission overlap among the parallelly aligned linkers. In contrast, symmetric MOFs, such as those with sqc-a topological net, orient elongated linkers along two perpendicular crystal axes, which hinders efficient exciton migration. This study underscores that MOFs are promising to develop artificial LHCs, but that to achieve an efficient exciton displacement, appropriate topology-guided assembly is required to fully realize the true potential of linkers with low electronic symmetry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Differentiable, Learnable, Regionalized Process-Based Models With Multiphysical Outputs can Approach State-Of-The-Art Hydrologic Prediction Accuracy

Predictions of hydrologic variables across the entire water cycle have significant value for water resources management as well as downstream applications such as ecosystem and water quality modeling. Recently, purely data-driven deep learning models like long short-term memory (LSTM) showed seemingly insurmountable performance in modeling rainfall runoff and other geoscientific variables, yet they cannot predict untrained physical variables and remain challenging to interpret. Here, we show that differentiable, learnable, process-based models (called δ models here) can approach the performance level of LSTM for the intensively observed variable (streamflow) with regionalized parameterization. We use a simple hydrologic model HBV as the backbone and use embedded neural networks, which can only be trained in a differentiable programming framework, to parameterize, enhance, or replace the process-based model's modules. Without using an ensemble or post-processor, δ models can obtain a median Nash-Sutcliffe efficiency of 0.732 for 671 basins across the USA for the Daymet forcing data set, compared to 0.748 from a state-of-the-art LSTM model with the same setup. For another forcing data set, the difference is even smaller: 0.715 versus 0.722. Meanwhile, the resulting learnable process-based models can output a full set of untrained variables, for example, soil and groundwater storage, snowpack, evapotranspiration, and baseflow, and can later be constrained by their observations. Both simulated evapotranspiration and fraction of discharge from baseflow agreed decently with alternative estimates. The general framework can work with models with various process complexity and opens up the path for learning physics from big data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Manipulating chiral spin transport with ferroelectric polarization

A magnon is a collective excitation of the spin structure in a magnetic insulator and can transmit spin angular momentum with negligible dissipation. This quantum of a spin wave has always been manipulated through magnetic dipoles (that is, by breaking time-reversal symmetry). Here we report the experimental observation of chiral spin transport in multiferroic BiFeO 3 and its control by reversing the ferroelectric polarization (that is, by breaking spatial inversion symmetry). The ferroelectrically controlled magnons show up to 18% modulation at room temperature. The spin torque that the magnons in BiFeO 3 carry can be used to efficiently switch the magnetization of adjacent magnets, with a spin-torque efficiency comparable to the spin Hall effect in heavy metals. Utilizing such controllable magnon generation and transmission in BiFeO 3 , an all-oxide, energy-scalable logic is demonstrated composed of spin-orbit injection, detection and magnetoelectric control. In conclusion, our observations open a new chapter of multiferroic magnons and pave another path towards low-dissipation nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Expanding the genetic toolset: using serine recombinases to integrate riboregulatory elements into industrially relevant microbial chassis

To realize the full potential of biomanufacturing, the breadth of industrial microbes used to consume diverse feedstock and generate bioproducts needs to expand. As such, portable tools are required that can be used by multiple hosts for straightforward genomic manipulation and precise gene expression. Here, we demonstrate the co-utilization of two synthetic biology tools to achieve these goals: cis-repressors (CRs) and serine recombinase-assisted genome engineering (SAGE). CRs are small, noncoding RNAs that are placed upstream of the target gene to modulate bacterial translation rates at varying, discrete levels. SAGE uses site-specific serine recombinases to catalyze highly efficient, unidirectional insertion of DNA into the chromosome of diverse organisms. We used SAGE to integrate a suite of CRs into the industrially relevant hosts Pseudomonas putida, Corynebacterium glutamicum, and Cupriavidus necator. Using a fluorescent reporter as a readout of CR functionality, we found that CR performance across these backgrounds was similar—providing a range of translational repression up to 100-fold. Overall, these results demonstrate the high portability of CRs across bacterial genetic backgrounds, which ideally can be used in future microbial engineering efforts pertinent to biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Analysis of High Frequency AC Link Isolated Three Port Resonant Converter for UAV Applications

A high frequency AC link isolated three port semi-bridgeless resonant converter is analyzed for unmanned aerial vehicle (UAV) applications in this study. The proposed topology is established by replacing rectifier lover diodes with synchronous switches. A phase shifted pulse width modulation (PS-PWM) technique adjusts bi-directional power flow between ports. Proposed control technique provides high efficiency by reducing switching losses with zero voltage switching (ZVS) and zero current switching (ZCS) in a wide power range regulation. Compared to integrated PWM converters in a bi-directional mode, the proposed topology reduces the number of converter stages and allows centralized control at high operating frequency. Theoretical and experimental results demonstrate the feasibility and effectiveness of the proposed converter at a full power of 500 W in laboratory conditions.

Asa, Erdem↗
DOE OSTI2021

Constant Frequency ZVS PWM Converter

In this paper, a simple yet novel buck or boost adaptive zero-voltage switching (ZVS) converter topology is proposed for soft switching pulse-width modulation (PWM) dc / dc converters. The converter is designed for the high switching frequency that can achieve high efficiency by reducing switching losses for the entire load range at low and high power. Besides, the output at the load terminals is maintained by a PWM signal at a fixed switching frequency, a phase shift signal between converter ports (legs) controls the system circulating current in order to provide the ZVS condition in all load conditions. With the proposed controller, the converter, thus, is suitable for high switching frequency and high-power applications with the small volume. The proposed dc / dc converter operation is analyzed, designed, and confirmed by simulation results for 240 V input, 400 V / 5 A output, and 200 kHz operating frequency at full load.

Asa, Erdem↗
DOE OSTI2022

Silicon nitride stress-optic microresonator modulator for optical control applications

Modulation-based control and locking of lasers, filters and other photonic components is a ubiquitous function across many applications that span the visible to infrared (IR), including atomic, molecular and optical (AMO), quantum sciences, fiber communications, metrology, and microwave photonics. Today, modulators used to realize these control functions consist of high-power bulk-optic components for tuning, sideband modulation, and phase and frequency shifting, while providing low optical insertion loss and operation from DC to 10s of MHz. In order to reduce the size, weight and cost of these applications and improve their scalability and reliability, modulation control functions need to be implemented in a low loss, wafer-scale CMOS-compatible photonic integration platform. The silicon nitride integration platform has been successful at realizing extremely low waveguide losses across the visible to infrared and components including high performance lasers, filters, resonators, stabilization cavities, and optical frequency combs. Yet, progress towards implementing low loss, low power modulators in the silicon nitride platform, while maintaining wafer-scale process compatibility has been limited. Here we report a significant advance in integration of a piezo-electric (PZT, lead zirconate titanate) actuated micro-ring modulation in a fully-planar, wafer-scale silicon nitride platform, that maintains low optical loss (0.03 dB/cm in a 625 µm resonator) at 1550 nm, with an order of magnitude increase in bandwidth (DC - 15 MHz 3-dB and DC - 25 MHz 6-dB) and order of magnitude lower power consumption of 20 nW improvement over prior PZT modulators. The modulator provides a >14 dB extinction ratio (ER) and 7.1 million quality-factor (Q) over the entire 4 GHz tuning range, a tuning efficiency of 162 MHz/V, and delivers the linearity required for control applications with 65.1 dB·Hz 2/3 and 73.8 dB·Hz 2/3 third-order intermodulation distortion (IMD3) spurious free dynamic range (SFDR) at 1 MHz and 10 MHz respectively. We demonstrate two control applications, laser stabilization in a Pound-Drever Hall (PDH) lock loop, reducing laser frequency noise by 40 dB, and as a laser carrier tracking filter. This PZT modulator design can be extended to the visible in the ultra-low loss silicon nitride platform with minor waveguide design changes. This integration of PZT modulation in the ultra-low loss silicon nitride waveguide platform enables modulator control functions in a wide range of visible to IR applications such as atomic and molecular transition locking for cooling, trapping and probing, controllable optical frequency combs, low-power external cavity tunable lasers, quantum computers, sensors and communications, atomic clocks, and tunable ultra-low linewidth lasers and ultra-low phase noise microwave synthesizers.

Wang, Jiawei (ORCID:0000000257965220)↗