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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

In Situ Formed Pt–Ga Hetero Duo-Atomic Catalyst for Efficient Hydrogen Storage in N-Heterocycles

Efficient catalysts for the dehydrogenation and hydrogenation of liquid organic hydrogen carriers (LOHCs) are essential for advancing hydrogen storage and transportation. Conventional nanoparticle catalysts suffer from low metal utilization, while single-atom catalysts (SAC) are limited by isolated active sites. Here, in this work, we present a hetero duo-atomic catalyst, Pt 1 –Ga 1 /CeO 2 DAC, which exhibits exceptional activity, selectivity, stability, and recyclability for N-heterocycle hydrogen storage. Ga plays a critical role in C–H bond activation, acting as a mediator in catalytic bond-breaking and formation. Compared with Pt 1 /CeO 2 SAC, Pt 1 –Ga 1 /CeO 2 DAC enhances metal utilization while overcoming SAC limitations for large substrates. This work establishes a promising strategy for designing highly efficient catalysts for LOHC applications.

Chen, Luning [Univ. of California, Los Angeles, CA↗
DOE OSTI2026

In Situ Imaging Reveals Efficient Charge Separation in Monolayer MoS 2 –WS 2 Type-II Heterojunctions

Covalently bonded in-plane two-dimensional (2D) transition metal dichalcogenide (TMD) heterojunctions with atomically sharp interfaces hold great promise for photocatalytic applications in solar energy conversion and environmental remediation; however, their spatially resolved charge distribution and transport, particularly under operando conditions, remain poorly understood. Here, we employ photoscanning electrochemical microscopy (photo-SECM) to directly visualize photoinduced charge separation in monolayer MoS 2 –WS 2 in-plane heterojunctions. Spatial separation of photogenerated carriers is observed, with electrons accumulating in MoS 2 and holes in WS 2 , leading to strongly asymmetric interfacial kinetics: Fc + reduction proceeds rapidly on MoS 2 (0.6 cm s –1 ), whereas Fc oxidation on WS 2 is significantly slower (0.008 cm s –1 ). High-resolution surface photovoltage microscopy (SPVM) enables a quantitative comparison of charge-separation capacity across architectures. The in-plane MoS 2 –WS 2 heterojunction shows the largest photovoltage contrast (−35 mV in MoS 2 , 20 mV in WS 2 ), exceeding the vertical heterojunction (−18 mV in MoS 2 , 11 mV in WS 2 ) and the individual monolayers (−12 mV for MoS 2 , – 1 mV for WS 2 ), establishing the following trend: in-plane > vertical > monolayers. Ultraviolet photoelectron spectroscopy (UPS) indicates that this directional charge separation is driven by intrinsic type-II band alignment, while photoluminescence (PL) imaging shows that the interface acts as a recombination center that limits efficient carrier extraction. These results provide direct experimental evidence of type-II-driven charge separation in in-plane heterojunctions and offer critical insights for interface design in high-efficiency photocatalytic and optoelectronic systems.

electrical properties↗
DOE OSTI2025

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗
DOE OSTI2025

Doping with phosphorus reduces anion vacancy disorder in CdSeTe semiconductors enabling higher solar cell efficiency

Doping is used in many pn junction devices, such as polycrystalline solar cells, to increase the strength of the junction field to assist charge carrier collection and thus partially mitigate nonradiative recombination losses. We demonstrate a different doping characteristic for inorganic solar cells: using dopants to reduce charge carrier trapping and electronic band tails. Alloying CdTe with Se to form CdSeTe semiconductor reduced recombination, but CdSeTe has more complex defect states which can limit further efficiency gains due to charge carrier trapping and trap-limited mobility. Doping CdSeTe with P (but not N, As, or Sb in this study) reduces band tails (Urbach energies) and lessens the impact of the near valence band trap states, with ambipolar mobilities improving to >50 cm 2 V −1 s −1 , fill factor increasing from 76% to 79%, and efficiencies increasing by 0.9% absolute. Simulations are used to show how such defect reduction improves performance in the radiative limit.

14 SOLAR ENERGY↗
DOE OSTI2026

Enhancing the efficiency of time-dependent density functional theory calculations of dynamic response properties

X-ray Thomson scattering (XRTS) constitutes an essential technique for diagnosing material properties under extreme conditions, such as high pressures and intense laser heating. Time-dependent density functional theory (TDDFT) is one of the most accurate available ab initio methods for modeling XRTS spectra, as well as a host of other dynamic material properties. However, strong thermal excitations, along with the need to account for variations in temperature and density as well as the finite size of the detector significantly increase the computational cost of TDDFT simulations compared to ambient conditions. In this work, we present a broadly applicable method for optimizing and enhancing the efficiency of TDDFT calculations. Our approach is based on a one-to-one mapping between the dynamic structure factor and the imaginary time density–density correlation function, which naturally emerges in Feynman’s path integral formulation of quantum many-body theory. Specifically, we combine rigorous convergence tests in the imaginary time domain with a constraints-based attenuation of narrow-band fluctuations to improve the efficiency of TDDFT modeling without the introduction of any significant bias. As a result, we can report a speed-up by up to an order of magnitude, thus substantially reducing the burden of computational cost required for XRTS analysis.

Moldabekov, Zhandos A. [Helmholtz-Zentrum Dresden-↗
DOE OSTI2025

Overcoming efficiency and cost barriers for large-area quantum dot photovoltaics through stable ink engineering

The bottom-up construction of electronics from colloidal quantum dots (CQDs) could innovate nanotechnology manufacturing through printing. However, the unstable and expensive semiconductive CQD inks make the scaling up of CQD electronics challenging. Here, in this study, we develop a strategy for engineering the solution chemistry of lead sulfide (PbS) CQD inks prepared from a low-cost direct synthesis method. By creating an iodine-rich environment in weakly coordinating solvents, we convert the iodoplumbates into functional anions, which condense into a robust surface shell. The fully charged electrostatic surface layer prevents aggregation and epitaxial fusion of CQDs, yielding stable inks. By eliminating the fusion-induced inter-band states, we print a compact CQD film with uniformity in three dimensions, flattened energy landscape and improved carrier transport. We achieved a certified efficiency of 13.40% on 0.04 cm 2 cells, with a 300-fold increase in active area, scaling up to a 12.60 cm 2 module with a certified efficiency of 10%.

14 SOLAR ENERGY↗
DOE OSTI2024

Efficient conversion of syngas to linear α-olefins by phase-pure χ-Fe5C2

Abstract Oil has long been the dominant feedstock for producing fuels and chemicals, but coal, natural gas and biomass are increasingly explored alternatives 1–3 . Their conversion first generates syngas, a mixture of CO and H 2 , which is then processed further using Fischer–Tropsch (FT) chemistry. However, although commercial FT technology for fuel production is established, using it to access valuable chemicals remains challenging. A case in point is linear α-olefins (LAOs), which are important chemical intermediates obtained by ethylene oligomerization at present 4–8 . The commercial high-temperature FT process and the FT-to-olefin process under development at present both convert syngas directly to LAOs, but also generate much CO 2 waste that leads to a low carbon utilization efficiency 9–14 . The efficiency is further compromised by substantially fewer of the converted carbon atoms ending up as valuable C 5 –C 10 LAOs than are found in the C 2 –C 4 olefins that dominate the product mixtures 9–14 . Here we show that the use of the original phase-pure χ-iron carbide can minimize these syngas conversion problems: tailored and optimized for the process of FT to LAOs, this catalyst exhibits an activity at 290 °C that is 1–2 orders higher than dedicated FT-to-olefin catalysts can achieve above 320 °C (refs. 12–15 ), is stable for 200 h, and produces desired C 2 –C 10 LAOs and unwanted CO 2 with carbon-based selectivities of 51% and 9% under industrially relevant conditions. This higher catalytic performance, persisting over a wide temperature range (250–320 °C), demonstrates the potential of the system for developing a practically relevant technology.

Science & Technology - Other Topics↗
DOE OSTI2025

Spotlight: efficient automated global optimization in rietveld analysis of diffraction data

Performing reliable Rietveld analysis on tens or hundreds of powder diffraction datasets from parametric or time-resolved experiments often poses a bottleneck in extracting meaningful results from the data. While automated analysis of data has recently been demonstrated, high temperature annealing studies, during which phase transformations occur and lattice parameters may change due to repartitioning of elements, are prime examples where automation by a simple phase identification from a database of room temperature structures or automation by sequential refinements is likely to fail. To enable reliable, efficient, automated Rietveld analysis, we present a Python package named Spotlight , building on established Rietveld packages such as MAUD, GSAS , or GSAS-II , which extends the refinement of best fit parameters to a global optimization using an ensemble of optimizers leveraging hierarchical parallel execution on high-performance computing clusters. Spotlight further enables the efficient design of refinement plans through the iterative automated machine-learning of a surrogate for the refinement on which the global optimizations are performed until results from the surrogate converge to the response surface data. We demonstrate Spotlight with the analysis of uranium molybdenum and Ti–6Al–4V datasets, as well as in two open-source tutorials analyzing aluminium oxide and lead sulphate.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tungsten single-atom catalysts for the efficient conversion of isobutene into highly branched liquid hydrocarbons

The catalytic transformation of isobutene into branched liquid hydrocarbons is crucial for the production of reformulated gasoline and fuel additives. Conventional supported catalysts often lack high activity and selectivity toward the desired highly branched dimers and trimers in isobutene oligomerization. Here, by developing a tungsten single-atom catalyst (W SAC ) atomically dispersed on a silica-doped alumina (SDA) support, we report that the W SAC /SDA catalyst enables efficient and selective conversion of isobutene into highly branched C 8 and C 12 liquid olefins while suppressing the formation of heavier hydrocarbons. The atomically dispersed W 1 –O 3 moieties incorporated within the SDA support were synthesized via a high-temperature pyrolysis of a templating zinc metal–organic framework (Zn-MOF) under argon, followed by annealing in static air. The W SAC /SDA catalysts with 1.6–3.7 wt% W loading exhibited single-atom dispersion (∼0.2 nm) and outstanding performance, achieving up to 60% and 95% selectivity to branched C8 olefins at 150 °C and 250 °C, respectively, under ambient pressure. With the demonstrated high activity, selectivity, and stability, the W SAC /SDA catalyst system presents a promising platform for next-generation heterogeneous catalysts for the efficient and selective upgrading of isobutene into high-performance fuel additives.

Branched Olefins↗
DOE OSTI2025

Rigid cationic ligands enable high-efficiency NIR-II photoluminescence in copper( i ) iodide hybrid semiconductors

Near-infrared (NIR) luminescent materials are pivotal for advanced optoelectronic and biomedical applications, yet attaining efficient emission in the NIR-II region (950-1400 nm) remains challenging. Here, we introduce a ligand cationization strategy for designing copper(i) iodide-organic hybrid materials that emit in the NIR-II region (920-1120 nm) with PLQYs up to 8.58%. By incorporating rigid cationic ligands with CuI modules, we synergistically achieve bandgap narrowing (to 1.51 eV) and structural rigidification via ionic-dative bonding, effectively suppressing non-radiative decay while extending emission beyond 1100 nm. Coupled with solution processability-enabled by the successful synthesis of nanometer-sized nanoparticles in various shapes-and excellent thermal stability (≥210 °C), this work establishes ligand cationization as a universal approach for designing efficient NIR-II emitters.

Chen, Jingwen↗
DOE OSTI2025

High-efficiency frost and ice control via sensing-assisted nanovibrational slippery surfaces

Frost and ice accretions on surfaces pose persistent challenges across numerous industrial, residential and transportation systems. While various removal strategies exist, they often suffer from limited effectiveness or high energy consumption, such as frosting delay, ice crack generation, and Joule heating. Here, in this work, we report a novel integrated approach combining vibrational quasi-liquid surface (QLS) and capacitive sensing for efficient condensate, frost, and ice management. Compared to Joule heating, our approach does not rely on complete melting and evaporation for removal, resulting in 68% and 95% energy savings for frost and ice removal, respectively. Our QLS coating significantly reduces surface retention forces, achieving 91% and 87% less residual mass compared to hydrophilic surfaces for frost and ice removal through surface nanovibration, respectively. The integrated capacitive sensor provides real-time detection of different phase states, enabling on-demand removal in precise timeframes. This sensor-assisted approach showed 3.8 times lower energy consumption compared to conventional Joule heating for defrosting. This synergistic integration of surface engineering, nanovibration, and intelligent sensing represents a significant advancement in phase change processes, offering an energy-efficient solution for frost and ice mitigation in energy-intensive systems.

Shen, Yuchen [Univ. of Texas at Dallas, Richardson↗
DOE OSTI2025

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗
DOE OSTI2024

A road map to cosmological parameter analysis with third-order shear statistics: III. Efficient estimation of third-order shear correlation functions and an application to the KiDS-1000 data

Context. Third-order lensing statistics contain a wealth of cosmological information that is not captured by second-order statistics. However, the computational effort it takes to estimate such statistics in forthcoming stage IV surveys is prohibitively expensive. Aims. We derive and validate an efficient estimation procedure for the three-point correlation function (3PCF) of polar fields such as weak lensing shear. We then use our approach to measure the shear 3PCF and the third-order aperture mass statistics on the KiDS-1000 survey. Methods We constructed an efficient estimator for third-order shear statistics that builds on the multipole decomposition of the 3PCF. We then validated our estimator on mock ellipticity catalogs obtained from N -body simulations. Finally, we applied our estimator to the KiDS-1000 data and presented a measurement of the third-order aperture statistics in a tomographic setup. Results. Our estimator provides a speedup of a factor of ∼100–1000 compared to the state-of-the-art estimation procedures. It is also able to provide accurate measurements for squeezed and folded triangle configurations without additional computational effort. We report a significant detection of tomographic third-order aperture mass statistics in the KiDS-1000 data (S/N = 6.69). Conclusions. Our estimator will make it computationally feasible to measure third-order shear statistics in forthcoming stage IV surveys. Furthermore, it can be used to construct empirical covariance matrices for such statistics.

Astronomy & Astrophysics↗
DOE OSTI2024

Rational design of efficient defect-based quantum emitters

Single-photon emitters are an essential component of quantum networks, and defects or impurities in semiconductors are a promising platform to realize such quantum emitters. Here, we present a model that encapsulates the essential physics of coupling to phonons, which governs the behavior of real single-photon emitters, and critically evaluate several approximations that are commonly utilized. Emission in the telecom wavelength range is highly desirable, but our model shows that nonradiative processes are greatly enhanced at these low photon energies, leading to a decrease in efficiency. Our results suggest that reducing the phonon frequency is a fruitful avenue to enhance the efficiency.

Optics↗
DOE OSTI2024

Accurate and efficient open-source implementation of domain-based local pair natural orbital (DLPNO) coupled-cluster theory using a t1-transformed Hamiltonian

We present an efficient, open-source formulation for coupled-cluster theory through perturbative triples with domain-based local pair natural orbitals [DLPNO-CCSD(T)]. Similar to the implementation of the DLPNO-CCSD(T) method found in the ORCA package, the most expensive integral generation and contraction steps associated with the CCSD(T) method are linear-scaling. In this work, we show that the t1-transformed Hamiltonian allows for a less complex algorithm when evaluating the local CCSD(T) energy without compromising efficiency or accuracy. Our algorithm yields sub-kJ mol−1 deviations for relative energies when compared with canonical CCSD(T), with typical errors being on the order of 0.1 kcal mol−1, using our TightPNO parameters. We extensively tested and optimized our algorithm and parameters for non-covalent interactions, which have been the most difficult interaction to model for orbital (PNO)-based methods historically. To highlight the capabilities of our code, we tested it on large water clusters, as well as insulin (787 atoms).

Chemistry↗
DOE OSTI2024

Efficient simulation of open quantum systems coupled to a reservoir through multiple channels

It is challenging to simulate open quantum systems that are connected to a reservoir through multiple channels. For example, vibrations may induce fluctuations in both energy gaps and electronic couplings, which represent two independent channels of system–bath couplings. Systems of this kind are ubiquitous in the processes of excited state radiationless decay. Combined with density matrix renormalization group (DMRG) and matrix product states (MPS) methods, we develop an interaction-picture chain mapping strategy for vibrational reservoirs to simulate the dynamics of these open systems, resulting in time-dependent spatially local system–bath couplings in the chain-mapped Hamiltonian. This transformation causes the entanglement generated by the system–bath interactions to be restricted within a narrow frequency window of vibrational modes, enabling efficient DMRG/MPS dynamical simulations. We demonstrate the utility of this approach by simulating singlet fission dynamics using a generalized spin-boson Hamiltonian with both diagonal and off-diagonal system–bath couplings. This approach generalizes an earlier interaction-picture chain mapping scheme, allowing for efficient and exact simulation of systems with multi-channel system–bath couplings using matrix product states, which may further our understanding of nonlocal exciton–phonon couplings in exciton transport and the non-Condon effect in energy and electron transfer.

Chemistry↗
DOE OSTI2025

Efficient generation and extreme compression of multidimensional solitary states in molecular gas-filled hollow-core fibers driven by picosecond Yb lasers

We present an in-depth study on the impact of spatiotemporal Raman enhancement in molecular gas-filled hollow-core fibers (HCFs), demonstrating the efficient generation and post-compression of multidimensional solitary states (MDSS). Through different experimental scenarios—employing large-core HCFs filled with molecular gases (N 2 and N 2 O) and driven by high energy, sub-picosecond and picosecond Fourier transform-limited ytterbium laser pulses—this work leverages multimode propagation and enhanced spatiotemporal interactions to achieve significant spectral broadening and asymmetric redshift, contrasting sharply with self-phase modulation. Our findings reveal that, beyond the regime of maximum nonadiabatic molecular alignment, spatiotemporal nonlinear enhancement primarily governs spectral broadening for input pulse durations up to 1 ps. The process shows limited sensitivity to input pulse duration and the two investigated molecular gases (N 2 and N 2 O), with only subtle differences in broadening arising from their distinct Raman spectroscopic properties. Furthermore, post-compression of MDSS was achieved in various cases. Notably, using 7 mJ, 1 ps laser pulses, we generated 22 fs pulses with a 47% energy conversion efficiency of the input pulse energy. These results position MDSS as a powerful platform for generating high-energy, ultrashort pulses with tunable wavelengths, offering a robust solution for applications such as high harmonic generation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Tree tensor network hierarchical equations of motion based on time-dependent variational principle for efficient open quantum dynamics in structured thermal environments

In this work, we introduce an efficient method, TTN-HEOM, for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme with the bexcitonic generalization of the numerically exact hierarchical equations of motion (HEOM). The method yields a series of quantum master equations for all core tensors in the TTN that efficiently and accurately capture the open quantum dynamics for non-Markovian environments to all orders in the system–bath interaction. These master equations are constructed based on the time-dependent Dirac–Frenkel variational principle, which isolates the optimal dynamics for the core tensors given the TTN ansatz. The dynamics converges to the HEOM when increasing the rank of the core tensors, a limit in which the TTN ansatz becomes exact. We introduce TENSO, tensor equations for non-Markovian structured open systems, as a general-purpose Python code to propagate the TTN-HEOM dynamics. We implement three general propagators for the coupled master equations: two fixed-rank methods that require a constant memory footprint during the dynamics and one adaptive-rank method with a variable memory footprint controlled by the target level of computational error. We exemplify the utility of these methods by simulating a two-level system coupled to a structured bath containing one Drude–Lorentz component and eight Brownian oscillators, which is beyond what can presently be computed using the standard HEOM. Our results show that the TTN-HEOM is capable of simulating both dephasing and relaxation dynamics of driven quantum systems interacting with structured baths, even those of chemical complexity, with an affordable computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗