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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mapping in situ the assembly and dynamics in aqueous supramolecular polymers

Supramolecular polymers, bonded through directional non-covalent interactions, closely mimic dynamic behaviors of biological nanofibers. However, the complexity of assembly pathways makes it highly challenging to unravel the nature of supramolecular dynamics in aqueous environments. Here we introduce a precise combinatorial titration methodology to probe in situ the assembly of peptide amphiphiles (PAs). This approach reveals a binary assembly mechanism governed by equilibrium between spheroidal micelles and β-sheet polymers. Weakening hydrogen bonding shifts the equilibrium towards micelles and decreases the internal structural order of filamentous polymers, promoting supramolecular dynamics. Extending this methodology to two-component copolymerization systems, we find a surprising tendency to form blocky nanostructures with reduced internal phase separation as the mismatch in peptide sequence decreases. Interestingly, while well-mixed copolymers acquire different dynamics, mismatched ones retain the characteristic supramolecular motion of their homopolymer counterparts. These critical insights into supramolecular dynamics offer strategies to tailor the dynamic functions of supramolecular nanomaterials.

Molecular self-assembly↗
DOE OSTI2025

Controlling solvation in conducting redox polymers for selective electrochemical separation of nitrate from wastewater

Selective capture of nitrate from wastewater is crucial for ensuring safe drinking water and promoting resource circularity. This study investigated alkylated polyaniline redox polymers as highly-selective electrosorbents to address this challenge. By controlling polymer solvation properties through synthetic functionalization, poly(N-methylaniline) (PNMA) achieves a nitrate uptake of up to 1.38 mmol g −1 -polymer and a separation factor of 7 over chloride. Poly(N-butylaniline) (PNBA) further enhances selectivity, achieving a separation factor beyond 14 due to increased hydrophobicity. The mechanisms underlying this selectivity are investigated using ab initio molecular dynamics (AIMD) and in-situ electrochemical quartz crystal microbalance (EQCM) studies, which reveal that hydrophobicity reduces chloride binding. A technoeconomic analysis indicates that methylation on PANI reduces nitrate removal costs by 50% compared to non-functionalized PANI, due to enhanced selectivity and uptake, and decreased energy consumption. PNMA electrodes demonstrate practical nitrate selectivity over 20 versus chloride in real wastewater, while avoiding sulfate binding. This study highlights the potential of controlling solvation at electroactive polymers to enhance nitrate selectivity, offering a promising design path for redox-mediated electrochemical separations.

chemical engineering↗
DOE OSTI2026

Efficient bidirectional quantum frequency conversion between telecom and visible bands using adaptively phase-matched III-V nanophotonic waveguides

Quantum frequency conversion (QFC) is essential for interfacing quantum systems operating at different wavelengths and for realizing scalable quantum networks. Despite extensive progress, achieving QFC with simultaneous high efficiency, low pump power, minimal noise, broad bandwidth, and pump-wavelength flexibility remains challenging. Here, we demonstrate efficient, low-noise, and bidirectional QFC between the telecom (1550-nm) and visible (780-nm) bands using unpoled indium gallium phosphide (InGaP) χ (2) nanophotonic waveguides, eliminating the need for a long-wavelength pump. Leveraging the large nonlinear susceptibility of InGaP together with adaptive phase-matching control, we obtain 27% (55%) internal efficiency in a 6-mm (2.5-mm)-long waveguide with a low pump power of 20 mW (50 mW) and a noise flux spectral density of 10 −4 counts per second per hertz at signal–pump detuning of 20 nm. These results mark a significant advance in integrated nonlinear photonics for high-performance QFC, facilitating the development of versatile and scalable quantum networks.

Hu, Jierui [Univ. of Illinois at Urbana-Champaign,↗
DOE OSTI2025

Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design

Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML training. In this study, we report a data-efficient, deep-learning framework for molecular discovery that integrates a coarse-grained functional-group representation with a self-attention mechanism to capture intricate chemical interactions. Our approach exploits group-contribution concepts to create a graph-based intermediate representation of molecules, serving as a low-dimensional embedding that substantially reduces the data demands typically required for training. Using a self-attention mechanism to learn the subtle but highly relevant chemical context of functional groups, the method proposed here consistently outperforms existing approaches for predictions of multiple thermophysical properties. In a case study focused on adhesive polymer monomers, we train on a limited dataset comprising only 6,000 unlabeled and 600 labeled monomers. The resulting chemistry prediction model achieves over 92% accuracy in forecasting properties directly from SMILES strings, exceeding the performance of current state-of-the-art techniques. Furthermore, the latent molecular embedding is invertible, enabling the design pipeline to automatically generate new monomers from the learned chemical subspace. We illustrate this functionality by targeting several properties, including high and low glass transition temperatures (Tg), and demonstrate that our model can identify new candidates with values that surpass those in the training set. The ease with which the proposed framework navigates both chemical diversity and data scarcity offers a promising route to accelerate and broaden the search for functional materials.

Han, Ming [Univ. of Chicago, IL (United States)]↗
DOE OSTI2026

Towards dislocation-driven quantum interconnects

A central problem in the deployment of quantum technologies is the realization of robust architectures for quantum interconnects. We propose to engineer interconnects in semiconductors and insulators by patterning spin qubits at dislocations, thus forming quasi one-dimensional lines of entangled point defects. To gain insight into the feasibility and control of dislocation-driven interconnects, we investigate the optical cycle and coherence properties of nitrogen-vacancy (NV) centers in diamond, in proximity of dislocations, using a combination of advanced first-principles calculations. We show that one can engineer spin defects with properties similar to those of their bulk counterparts, including charge stability and a favorable optical cycle, and that NV centers close to dislocations have much improved coherence properties. Finally, we predict optically detected magnetic resonance spectra that may facilitate the experimental identification of specific defect configurations. Our results provide a theoretical foundation for the engineering of one-dimensional arrays of spin defects in the solid state.

Materials science↗
DOE OSTI2025

Climate change drives reduced biocontrol of the invasive spongy moth

The effects of climate change on forest-defoliating insects are poorly understood, but could severely reduce forest productivity, biodiversity and timber production. For decades following its introduction in 1869, the spongy moth ( Lymantria dispar ) severely defoliated North American forests, but the introduction of the fungal pathogen Entomophaga maimaiga in 1989 suppressed spongy moth defoliation for 27 years. E. maimaiga , however, needs cool, moist conditions, whereas climate change is bringing hot, dry conditions to the range of the insect. Here, in this work, we use an empirically verified eco-climate model to project that climate change will sharply reduce E. maimaiga infection rates, thereby increasing spongy moth defoliation. Recent rebounds in defoliation are consistent with our projections. Our work demonstrates that the effects of climate change on species interactions can have important consequences for natural ecosystems.

climate-change ecology↗
DOE OSTI2025

Overcoming the conversion reaction limitation at three-phase interfaces using mixed conductors towards energy-dense solid-state Li–S batteries

Lithium–sulfur (Li–S) all-solid-state batteries (ASSBs) hold great promise for next-generation safe, durable and energy-dense battery technology. However, solid-state sulfur conversion reactions are kinetically sluggish and primarily constrained to the restricted three-phase boundary area of sulfur, carbon and solid electrolytes, making it challenging to achieve high sulfur utilization. Here, in this study, we develop and implement mixed ionic–electronic conductors (MIECs) in sulfur cathodes to replace conventional solid electrolytes and invoke conversion reactions at sulfur–MIEC interfaces in addition to traditional three-phase boundaries. Microscopic and tomographic analyses reveal the emergence of mixed-conducting domains embedded in sulfur at sulfur–MIEC boundaries, helping promote the thorough conversion of active sulfur into Li 2 S. Consequently, substantially improved active sulfur ratios (up to 87.3%) and conversion degrees (>94%) are achieved in Li–S ASSBs with high discharge capacity (>1,450 mAh g –1 ) and long cycle life (>1,000 cycles). The strategy is also applied to enhance the active material utilization of other conversion cathodes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Super-resolution stimulated X-ray Raman spectroscopy

Propagation of intense X-ray pulses through dense media has led to the observation of phenomena such as atomic X-ray lasing, self-induced transparency and stimulated X-ray Raman scattering (SXRS)4. SXRS has been long predicted as a means to launch and probe valence-electron wavepackets and as a building block for nonlinear X-ray spectroscopies. However, experimental observations of SXRS to date have not provided spectroscopic information, and theoretical modelling has largely implemented hard-to-realize phase-coherent attosecond pulses. Here we demonstrate SXRS with spectroscopic precision, that is, detection of valence-excited states in neon with a near Fourier-limited joint energy–time resolution of 0.1 eV–40 fs. We used a new covariance analysis between statistically spiky broadband incident X-ray and scattered X-ray Raman pulses. Using 18,000 single shots, we beat not only the incident (about 8 eV) bandwidth but also the approximately 0.2 eV instrumental energy resolution, thus creating super-resolution conditions, in analogy to super-resolved fluorescence microscopy. Our experimental results, supported by ab initio propagation simulations, reveal the competition between lasing in the ion and stimulated Raman scattering in the neutral. We demonstrate enhanced signal collection efficiency and a broad excitation window, surpassing spontaneous Raman efficiencies by orders of magnitude. This stochastic SXRS approach represents a first step towards tracking elementary events that determine chemical outcomes.

nonlinear x-ray spectroscopy↗
DOE OSTI2025

Peatland fires in Alaska will double by the end of the century

During recent summers, warm and dry conditions have increased the occurrence of wildfires and potentially peat-fires across Alaska. Limitations in resolving the fine-scale distribution of peatlands and climate observations have constrained our ability to accurately predict peat-fire dynamics. Using a new high-resolution peatland map of Alaska, we evaluated the climate and environmental controls of past and future peat-fire activity. Ensemble machine learning models identified reduced soil moisture, higher temperatures, and evapotranspiration as key predictors of annual total burned peatland area (tenfold CV R 2 = 0.62, RMSE = 221.1 km 2 ). By the end of the twenty-first century, models forced with climate datasets from representative concentration pathways (RCPs) 4.5, 6.0, and 8.5 emission scenarios project a statewide doubling of burned peatlands (increasing 61–121%), with regional increases ranging from 25–165% in polar, 61–95% in boreal, and 102–106% in maritime ecoregions. These projections indicate that wildfires will progressively encroach further into organic-rich moist and wet peaty soils, potentially amplifying soil carbon release across Alaska.

climate-change ecology↗
DOE OSTI2025

Assessing the deployment of solar-driven hydrogen from biomass at scale in the U.S.

Solar hydrogen from biomass gasification is a promising technology to sustainably produce hydrogen, responsibly dispose biomass waste, and reduce reliance on fossil fuels. However, its large-scale deployment faces challenges due to the geospatial misalignment between biomass resources and solar intensity, which introduces additional supply chain logistics costs. We analyze the logistics cost burden imposed by this misalignment and its impact on successful large-scale deployment of solar-driven hydrogen from biomass in the United States. We also consider associated carbon emissions and explore how the mix of deployed technologies evolves under externally imposed carbon penalties. Our findings show that while economies of scale are known to apply at the processing facility level, the reverse effect occurs at the broader systems-level, driven by logistics. Also, at current technology costs, high carbon penalties would be required to favor deployment of solar based technologies over conventional and hybrid alternatives. We further illustrate strategies and system-level changes to reduce logistics costs and enable sustainable, low-cost hydrogen for decarbonizing different industrial sectors.

Iloeje, Chukwunwike O. [Argonne National Laborator↗
DOE OSTI2025

Light-induced electron spin qubit coherences in the purple bacteria reaction center protein

Photosynthetic reaction center proteins (RCs) provide ideal model systems for studying quantum entanglement between multiple spins, a quantum mechanical phenomenon wherein the properties of the entangled particles become inherently correlated. Following light-generated sequential electron transfer, RCs generate spin-correlated radical pairs (SCRPs), also referred to as entangled spin qubit (radical) pairs (SQPs). Understanding and controlling coherence mechanisms in SCRP/SQPs is important for realizing practical uses of electron spin qubits in quantum sensing applications. The bacterial RC (bRC) provides an experimental system for exploring quantum effects in the SCRP P 865 + Q A − , where P 865 , a special pair of bacteriochlorophylls, is the primary donor, and Q A is the primary quinone acceptor. In this study, we focus on understanding how local molecular environments and isotopic substitution, particularly deuteration, influence spin coherence times (T M ). Using high-frequency electron paramagnetic resonance (EPR) spectroscopy, we observed that the local environment surrounding P 865 and Q A plays a significant role in determining T M . Our findings show that while deuteration led to a modest increase in T M , particularly at low temperatures, but the effect was substantially smaller than predicted by classical nuclear spin diffusion alone. This result is in contrast to our previous study of the photosystem I (PSI) RC, where no increase in T M was observed upon deuteration. Theoretical modeling identified several methyl groups at key distances from the spin centers of both bRC and PSI, and methyl group tunneling at low temperatures has been previously suggested as a mechanism for enhanced spin decoherence. Additionally, our study revealed a strong dependence of spin coherence on the orientation of the external magnetic field, highlighting the influence of the protein microenvironment on spin dynamics. In conclusion, these results offer new insights for optimizing coherence times in quantum system design for quantum information science and sensing applications.

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

Techno-economic and life cycle analysis of bio-hydrogen production using bio-based waste streams through the integration of dark fermentation and microbial electrolysis

Hydrogen derived from bio-based sources, or biohydrogen (bioH 2 ), has the potential to reduce GHG emissions from industrial and transportation sectors, owing to the low carbon footprint and myriad applications like refinery operation, ammonia production, steel production, fuel cell, etc. To evaluate the commercialization potential of bioH 2 production, we modeled bioH 2 production and conducted techno-economic analysis (TEA) and life cycle analysis (LCA) of two facilities producing 50 metric tonnes of bioH 2 per day from cheese whey (CW) and solid food waste (SFW) through the integration of dark fermentation (DF) and microbial electrolysis cell (MEC) technologies. LCA results showed that CW and SFW can produce carbon-negative bioH 2 , with emissions of −8.6 and −8.0 kg GHG kg −1 bioH 2 with carbon sequestration and renewable electricity resources, respectively, making bioH 2 potentially eligible for a tax credit of $\$3$ kg −1 H 2 based on provision 45 V of the U.S. Inflation Reduction Act (IRA). In this study, bioH 2 production treats waste streams to generate fresh water, thus, potentially can receive waste water treatment fee that varies with regions. The MEC capital cost dominates the bioH 2 cost, which is mainly determined by current density. With a current density of 20 A m −2 , the production cost for CW input varied between $\$17$ and $\$24$ kg −1 bioH 2 , while that for SFW input ranged from $\$29$ to $\$30$ kg −1 bioH 2 under different operating conditions, considering the 45 V tax credit, waste water treatment fee and production revenue. If the current density increases to 100 A m −2 , the bioH 2 cost decreases to a range of $\$4.0$–$\$6.9$ for CW and $\$5$–$\$6$ for SFW scenarios. This study also shows that low-cost bioH 2 can be produced using CW waste stream as feedstock.

Ganguly, Arna [Argonne National Laboratory (ANL), ↗
DOE OSTI2025

Effect of rare earth size on network structure and glass forming ability in binary aluminum garnets

Rare earth aluminate glasses are potentially useful for optical, luminescence, and laser applications. As reluctant glass formers, these materials exhibit unconventional atomic structures. To better understand how their structures correlate with glass formation, we investigate two rare earth aluminum garnet melts, La 3 Al 5 O 12 (LAG) and Yb 3 Al 5 O 12 (YbAG), which represent the relative extremes of good and poor glass forming ability in rare earth aluminates. Structural models have been refined to high-energy X-ray diffraction data over 1340–2740 K. Both melts contain mixtures of AlO 4 , AlO 5 , and AlO 6 polyhedra, with larger fractions of [5] Al and [6] Al in YbAG. Extrapolation of the Al–O coordination distributions to the glass transition match closely with 27 Al nuclear magnetic resonance measurements of (La 1−z Y z ) 3 Al 5 O 12 glasses, z = 0 to 1. During cooling, the mean coordination numbers increase for La–O in LAG from 6.45(8) to 6.98(8) and for Yb–O in YbAG from 6.02(8) to 6.21(8). Linkedness among Al–O polyhedra at ∼2450 K is mostly corner-sharing, with 9% edge-sharing in LAG and 19% in YbAG. Among [4] Al units, both melts have 6% edge-sharing that convert to all corner-sharing upon cooling. Network connectivity is compared using a newly defined metric, K n , that is similar to the Q n distribution but that accounts for the edge-sharing and triply bonded oxygen present in these melts. The lower glass forming ability in YbAG as compared to LAG correlates with more edge-sharing, associated with the larger fractions of [5] Al and [6] Al, and lower connectivity among [4] Al units.

Wilke, Stephen K. [Materials Development, Inc., Ar↗
DOE OSTI2025

Direct measurements for the kinetics of C–C bond fission in the high temperature decomposition of isopropanol

The thermal decomposition of isopropanol was studied experimentally and theoretically with a view to isolate and directly measure rate coefficients for the dominant radical channel in this multi-channel process. Two complementary shock tube methods, laser schlieren densitomtery and H-atom atomic resonance absorption spectroscopy, were used to obtain rate coefficents for the C–C bond fission channel. The experimental ranges span temperatures from 1200–2100 K and pressures between 30–690 torr. These are the most direct measurements of this rate coefficent in the fall-off regime of relevance to high-temperature reacting systems. Theoretical studies also performed in this work confirm that the title reaction and a molecular elimination involving dehydration were the sole unimolecular processes at high temperatures. A master equation analysis yielded k ( T, P ) for the C–C fission and these are shown to be in good agreement with the present experimental measurements. Comparisons with prior experimental and theoretical studies in the literature indicate branching ratios as well as absolute k ( T, P ) for C–C bond-fission have been under-predicted for this decomposition reaction. Consequently, results from the present studies place an increased emphasis on radical-driven secondary processes in high-temperature pyrolysis of this simplest secondary alcohol.

Kim, John H. [Univ. of Michigan, Ann Arbor, MI (Un↗
DOE OSTI2025

Techno-economic and life cycle analyses of the synthesis of a platinum–strontium titanate catalyst

The heterogeneous platinum/strontium titanate (Pt/SrTiO 3 or Pt/STO) catalyst has garnered significant attention as a promising candidate for the hydrogenolysis of polyolefins to hydrocarbon oils. This study evaluates the cost and environmental impacts of a newly developed scalable Pt/STO catalyst production, which includes the synthesis of the STO support and the deposition of Pt onto the support. This two-step synthesis plays a significant role in assessing the commercial feasibility of the catalyst, while energy consumption during the process plays an important role in its environmental impacts. The CatCost and the Research and Development Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) models were used, respectively, to perform techno-economic analysis (TEA) and life cycle analysis (LCA) of the newly developed catalyst. The TEA showed that the raw materials, accounting for approximately 76% of the total operation cost, has a profound effect on the estimated catalyst cost, mainly due to the platinum precursor. The LCA findings indicated that the catalyst production generates greenhouse gas (GHG) emissions of 66 kg CO 2 e per kg, primarily due to the use of solvents and electricity in the process. The sensitivity analysis indicated that the total operating costs (OpEX), platinum precursor cost, and spent catalyst value (SCV) significantly impact the cost of the synthesized catalyst. Additionally, adopting solvent recovery strategies and using renewable electricity can reduce the GHG emissions of catalyst production to 29 kg CO 2 e per kg.

Heterogeneous Platinum/strontium titanate Catalyst↗
DOE OSTI2026

Optimization of pre-commercial enzyme dosage for a potential lignocellulosic biorefinery

Lignocellulolytic enzymes remain one of the primary cost constraints in second-generation (2G) ethanol biorefineries. Achieving efficient hydrolysis of structural carbohydrates with minimal enzyme dosage, maintaining slurry fermentability for industrially relevant ethanol titers, and maximizing ethanol yield per ton of biomass are among the major challenges in 2G processes. In this study, we optimized the dosages of pre-commercial cellulase (NS22257) and hemicellulase (NS22244) on pilot-scale, hydrothermally pretreated lignocellulosic substrates. Enzyme dosages were evaluated at three levels: 20 mg of cellulase with 7.25 mg of hemicellulase (ED-1), 40 mg with 14.5 mg (ED-2), and 60 mg with 21.75 mg (ED-3). As expected, the highest sugar yields were obtained with ED-3; however, for sweet sorghum, oilcane, and miscanthus, sugar yields from ED-2 and ED-3 were not significantly different ( p < 0.05). For example, sweet sorghum produced 123.78 ± 1.54 g L −1 and 125.76 ± 0.46 g L −1 of total sugars (glucose and xylose) with ED-2 and ED-3, respectively. Although energycane exhibited a statistically significant difference between ED-2 and ED-3, the incremental gain with ED-3 was modest, increasing sugar release by only 9.02 g L −1 relative to ED-2. Importantly, ED-1 resulted in sugar yields of 88.88 ± 3.64 to 106.86 ± 1.21 g L −1 , sufficient to achieve ethanol titers ≥40 g L −1 , the threshold required for industrial relevance. A semi-integrated bioprocess validated this outcome, producing 42.09 ± 2.38 g L −1 ethanol and an estimated yield of 213.38 L of ethanol per dry ton of pretreated biomass, requiring only 20.83 L of cellulase and 6.25 L of hemicellulase per ton. Remarkably, these enzyme dosages were approximately tenfold lower than those reported in prior studies.

Deshavath, Narendra Naik [Univ. of Illinois at Urb↗
DOE OSTI2025

Computational investigation of the impact of metal–organic framework topology on hydrogen storage capacity

Metal–organic frameworks (MOFs) are promising, tunable materials for hydrogen storage. For application under cryogenic operating conditions, past work has run into a ceiling on performance due to a trade-off in the volumetric deliverable capacity (VDC) versus the gravimetric deliverable capacity (GDC). In this study, we computationally constructed and screened 105 230 MOF structures based on 529 nets to explore the effect of underlying topology on the hydrogen storage performance of the resulting materials. A machine learning model was developed based on simulated hydrogen uptake to facilitate screening of the entire dataset, and it successfully identified the top 10% of materials with a root-mean-square error of approximately 1 g L −1 as validated by subsequent grand canonical Monte Carlo simulations. We identified a promising structure based on the tsx topology that exhibits both VDC and GDC higher than the current benchmark material, MOF-5. Our data-driven analysis indicates that nets with higher net density yield MOFs with enhanced volumetric and gravimetric surface areas, thereby improving maximum VDC while shifting the capacity trade-off toward higher GDC.

36 MATERIALS SCIENCE↗