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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Chlorophyllase from Arabidopsis thaliana Reveals an Emerging Model for Controlling Chlorophyll Hydrolysis

Chlorophyll (Chl) is one of Nature’s most complex pigments to biosynthesize and derivatize. This pigment is vital for survival and also paradoxically toxic if overproduced or released from a protective protein scaffold. Therefore, along with the mass production of Chl, organisms also invest in mechanisms to control its degradation and recycling. One important enzyme that is involved in these latter processes is chlorophyllase. This enzyme is employed by numerous photosynthetic organisms to hydrolyze the phytol tail of Chl. Although traditionally thought to catalyze the first step of Chl degradation, recent work suggests that chlorophyllase is instead employed during times of abiotic stress or conditions that produce reactive oxygen species. However, the molecular details regarding how chlorophyllases are regulated to function under such conditions remain enigmatic. Here, we investigate the Arabidopsis thaliana chlorophyllase isoform AtCLH2 using site-directed mutagenesis, mass spectrometry, dynamic light scattering, size-exclusion multiangle light scattering, and both steady-state enzyme kinetic and thermal stability measurements. Through these experiments, we show that AtCLH2 exists as a monomer in solution and contains two disulfide bonds. One disulfide bond putatively maps to the active site, whereas the other links two N-terminal Cys residues together. These disulfide bonds are cleaved by chemical or chemical and protein-based reductants, respectively, and are integral to maintaining the activity, stability, and substrate scope of the enzyme. This work suggests that Cys residue oxidation in chlorophyllases is an emerging regulatory strategy for controlling the hydrolysis of Chl pigments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance

Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discovery of aqueous soluble organic (ASO) redox-active materials necessitates efficient machine learning surrogates for predicting battery performance. The physics-guided continual learning (PGCL) method proposed in this study can incrementally learn data from new ASO electrolytes while addressing catastrophic forgetting issues in conventional machine learning. Using a AORFB database with a thousand potential materials generated by a 780 $\text{cm}^2$ interdigitated cell model, PGCL incorporates AORFB physics to optimize the continual learning task formation and training strategies to retain previously learned battery material knowledge. Finally, the trained PGCL demonstrates its capability in assessing emerging ASO materials within the established parameter space when evaluated with the dihydroxyphenazine isomers.

25 ENERGY STORAGE↗
DOE OSTI2025

Sulfide-Based Anode-Free Solid-State Batteries: Key Challenges and Emerging Solutions

Sulfide-based anode-free solid-state batteries (AFSSBs) have emerged as a transformative technology for next-generation energy storage, offering compelling advantages in energy density, safety, and manufacturing scalability. However, these batteries face significant challenges, particularly rapid capacity degradation that currently limits their practical implementation. This comprehensive review critically examines three fundamental issues affecting AFSSBs: nonuniform lithium nucleation on bare current collectors, unstable interfaces between plated lithium and sulfide electrolytes, and formation of interfacial voids during cycling. We systematically evaluate recent strategic advances in addressing these challenges, including metal seed coatings, conversion reaction-based compounds, and carbon-based interlayers. The review also analyzes the crucial role of advanced characterization techniques, from cryo-FIB-SEM to operando methods, in understanding failure mechanisms and validating improvement strategies. Finally, we present a forward-looking perspective on research directions necessary for commercialization. This work provides a thorough framework for understanding and advancing sulfide-based AFSSBs toward practical applications in next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2024

A Novel Emergent Constraint Approach for Refining Regional Climate Model Projections of Peak Flow Timing

Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Impact of Extreme Heat on Emergency Department Admissions for Childhood and Adult Asthma: An Evaluation of Earth Observations and Heat Wave Definitions

Extreme heat has been associated with adverse health outcomes, yet its impact on asthma exacerbations remains understudied. This is, in part, due to data limitations: research that relies on weather station records and aggregated health statistics cannot resolve fine-scale differences in heat impacts. This study investigates the association between heat wave definitions and summertime asthma-related emergency department visits in Baltimore, Maryland from 2016 to 2022, including 819 adult and 695 pediatric exacerbations. Using geocoded electronic health records and air temperature measurements at several spatial resolutions, we applied a case-crossover design with conditional logistic regressions at the census block group and tract levels. We found strong associations between asthma exacerbations and nighttime heat wave definitions based on relative thresholds of minimum temperatures when census block group or tract level temperature estimates were used. These relationships were significant for both age groups and showed elevated risks in socially vulnerable areas. In contrast, heat wave definitions derived from the city's primary National Weather Service synoptic weather station show associations between asthma and daytime heat extremes, suggesting that the character of the heat hazard depends on the scale at which it is defined. The extreme heat event definition used by Baltimore City's Code Red system showed no significant association with exacerbations. These findings highlight the importance of data resolution in shaping health inferences related to extreme heat in urban environments. Further, this study demonstrates that, regardless of spatial scale, extreme heat is associated with asthma exacerbations in both age groups.

Corpuz, B. [Johns Hopkins University, Baltimore, M↗
DOE OSTI2026

Emergence of Diverse Failure Patterns in Weathering‐Induced Landslides: Insights From Particle Finite Element Simulations

Weathering is a fundamental driver of landslide evolution over geological timescales. Despite its ubiquity and importance, quantifying how weathering drives the progressive destabilization of rock slopes remains challenging. In this work, we develop a unified computational framework based on the particle finite element method to investigate the evolution of weathering‐induced landslides, from long‐term weathering to short‐term slope failure and runout dynamics. The framework integrates key processes, including weathering front propagation, time‐dependent strength degradation, rupture surface development, and post‐failure runout dynamics. Through numerical simulation experiments, we elucidate how interactions among weathering characteristics (type, intensity, and rate law), bedrock strength, fracture distribution, and slope geometry govern the failure modes and kinematics of weathering‐induced landslides. Simulations show that matrix‐dominated weathering leads to shallow translational failures, whereas fracture‐dominated weathering produces deep‐seated rotational and compound landslides. Pre‐existing fractures and slope morphology also strongly influence the movement of destabilized landmasses, affecting the failure pattern (e.g., kinematic mode and rupture surface geometry) and post‐failure behavior (e.g., runout velocity). We further demonstrate that the failure time and volume of weathered slopes are governed by the competition between gravitational driving forces and cohesive resisting forces during progressive destabilization. These findings provide new insights into the fundamental mechanisms that drive the emergence of diverse failure patterns of weathering‐induced landslides with important implications for landslide hazard assessment.

Wang, Liang [Eidgenoessische Technische Hochschule↗
DOE OSTI2024

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Emergent flat band and topological Kondo semimetal driven by orbital-selective correlations

Flat electronic bands are expected to show proportionally enhanced electron correlations, which may generate a plethora of novel quantum phases and unusual low-energy excitations. They are increasingly being pursued in d-electron-based systems with crystalline lattices that feature destructive electronic interference, where they are often topological. Such flat bands, though, are generically located far away from the Fermi energy, which limits their capacity to partake in the low-energy physics. Here we show that electron correlations produce emergent flat bands that are pinned to the Fermi energy. We demonstrate this effect within a Hubbard model, in the regime described by Wannier orbitals where an effective Kondo description arises through orbital-selective Mott correlations. Moreover, the correlation effect cooperates with symmetry constraints to produce a topological Kondo semimetal. Our results motivate a novel design principle for Weyl Kondo semimetals in a new setting, viz.d-electron-based materials on suitable crystal lattices, and uncover interconnections among seemingly disparate systems that may inspire fresh understandings and realizations of correlated topological effects in quantum materials and beyond.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Spatiotemporal development of expanding bacterial colonies driven by emergent mechanical constraints and nutrient gradients

Abstract Bacterial colonies growing on solid surfaces can exhibit robust expansion kinetics, with constant radial growth and saturating vertical expansion, suggesting a common developmental program. Here, we study this process forEscherichia colicells using a combination of modeling and experiments. We show that linear radial colony expansion is set by the verticalization of interior cells due to mechanical constraints rather than radial nutrient gradients as commonly assumed. In contrast, vertical expansion slows down from an initial linear regime even while radial expansion continues linearly. This vertical slowdown is due to limitation of cell growth caused by vertical nutrient gradients, exacerbated by concurrent oxygen depletion. Starvation in the colony interior results in a distinct death zone which sets in as vertical expansion slows down, with the death zone increasing in size along with the expanding colony. Thus, our study reveals complex heterogeneity within simple monoclonal bacterial colonies, especially along the vertical dimension. The intricate dynamics of such emergent behavior can be understood quantitatively from an interplay of mechanical constraints and nutrient gradients arising from obligatory metabolic processes.

Science & Technology - Other Topics↗
DOE OSTI2025

Dynamic realization of emergent high-dimensional optical vortices

The dimensionality of vortical structures has recently been extended beyond two dimensions, providing additional topological complexity and robustness for high-capacity information processing and turbulence control. The generation of high-dimensional vortical structures has mostly been demonstrated in classical systems through the complex interference of fluidic, acoustic, or electromagnetic waves. However, natural materials rarely support three- or higher-dimensional vortical structures and their physical interactions. Here, we experimentally demonstrate a high-dimensional gradient thickness optical cavity (GTOC) in which the optical coupling of planar metal-dielectric multilayers implements topological interactions across multiple dimensions. At non-trivial topological phases, high-dimensional GTOC induces high-dimensional vortical structures in generalized parameter space in three, four dimensions, and beyond. These emergent high-dimensional vortical structures are observed under electro-optic tomography as optical vortex dynamics in two-dimensional real-space, employing the optical thicknesses of dielectric layers as synthetic dimensions. Our findings hold significant promise for emulating high-dimensional physics and developing active topological photonic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Emergent constraints on future methane emissions from global wetlands

Future methane (CH 4 ) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH 4 emissions (eCH 4 ) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH 4 yr −1 increase in eCH 4 . We also identify an emergent relationship between contemporary temperature dependence and projected eCH 4 . When constrained by 163 site-year eddy-covariance measurements of eCH 4 , we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH 4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic eCH 4 at the 2020 level, comparable to the reductions committed under the Global Methane Pledge. However, the constraint is dominated by mid- and high-latitude observations, with limited tropical coverage, and uncertainties in projected wetland inundation contribute substantially to uncertainty in eCH 4 . Our findings reduce the uncertainty in projected wetland methane–climate feedback and highlight its potential impacts on methane mitigation efforts to slow global warming.

Zhang, Zhen [Chinese Academy of Sciences (CAS), Be↗
DOE OSTI2025

Enhancing spectroscopy and microscopy with emerging methods in photon correlation and quantum illumination

Quantum optics has led to important advancements in our ability to prepare and detect correlations between individual photons. Its principles are increasingly translated into nanoscale characterization tools, furthering methods in spectroscopy, microscopy and metrology. Here, in this Review, we discuss the rapid progress in this field driven by advanced technologies of single-photon detectors and quantum-light sources, including time-resolved single-photon counting cameras, superconducting nanowire single-photon detectors and entangled photon sources of increasing brightness. We emphasize emerging applications in super-resolution microscopy, measurements below classical noise limits and photon-number-resolved spectroscopy—a powerful paradigm for the characterization of nanoscale electronic materials. We conclude by discussing key technological challenges and future opportunities in materials science and bionanophotonics alike.

Tsao, Chieh [University of California, Berkeley, C↗
DOE OSTI2025

An electronic microemulsion phase emerging from a quantum crystal-to-liquid transition

Strongly interacting electronic systems often exhibit a complicated phase diagram that results from the competition between different quantum ground states. One feature of these phase diagrams is the emergence of microemulsion phases, where regions of different phases self-organize across multiple length scales. The experimental characterization of these microemulsions can pose considerable challenges, as the long-range Coulomb interaction microscopically mingles with the competing states. Here we observe the signatures of the microemulsion between an electronic Wigner crystal and an electron liquid in a MoSe 2 monolayer using cryogenic reflectance and magneto-optical spectroscopy. We find that the transition into this microemulsion state is marked by anomalies in exciton reflectance, spin susceptibility and umklapp scattering, establishing it as a distinct phase of electronic matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Emergence of exchange bias in van der Waals magnetic alloy CrxPt1−xTe2

Abstract Cr x Pt 1− x Te 2 is a recently developed van der Waals magnetic alloy noted for its stability under ambient conditions. Here, we report the emergence of an exchange bias effect in Cr x Pt 1− x Te 2 , without typical exchange bias sources such as an adjacent antiferromagnetic layer. We find that the exchange bias is present for x = 0.45 and absent for x = 0.35, which is correlated to the presence of a Cr modulation where the Cr concentration alternates each vdW layer (modulation period of 2 layers) for x ≥ 0.4. We perform Monte Carlo simulations utilizing exchange parameters from first-principles calculations, which recreate the exchange bias in hysteresis loops of Cr 0.45 Pt 0.55 Te 2 . From our simulations, we infer the source of exchange bias to be magnetic moments locked into free energy minima that resist magnetization reversal. This work presents a way to introduce desirable magnetic properties to van der Waals magnets.

Bailey-Crandell, Ryan↗
DOE OSTI2025

Quantum sensing for emerging energy technologies

The ability to exploit quantum phenomena has enabled sensing technologies with detection limits below the classical limit. Sensors with applications in energy discovery, production, transportation, and consumption can be enhanced through quantum or hybrid quantum-classical sensors. Here, in this Review, we provide an overview of commercial and emerging quantum sensor platforms and their opportunity areas specific to advanced energy technologies. Key examples include: power grid-enhancing-technologies, where quantum magnetometers can detect powerline and transformer faults; electric vehicle-to-grid applications, where chip-scale atomic clocks can enable grid synchronization; and carbon capture and storage, where quantum gravimeters and single-photo LiDAR can detect microscopic leaks. Quantum sensor deployment requires further research into miniaturization and ruggedization for field deployment, cost-reduction, and workforce development. The maturation of clean energy technologies and quantum sensors provide opportunities for synergy, with the integration of quantum sensors into advanced energy technologies maximizing their security, reliability, and efficiency.

critical metals↗
DOE OSTI2026

Performance measurement of emerging 3- and 4-terminal tandem solar cells

Tandem solar cells are not limited to the conventional two-terminal (2-T) configuration. Multi-terminal designs like three-terminal (3-T) and four-terminal (4-T) devices have gained increasing attention in the PV community due to their relaxed current-matching requirement between subcells and their potential for enhanced energy yield. However, reliable and standardized methods for evaluating the performance of multi-terminal tandems remain underdeveloped. This work addresses this gap by providing comprehensive measurement guidelines tailored to these advanced configurations. We examine key coupling mechanisms between subcells, including the shared electrical load in 3-T devices and optical luminescent coupling in both 3-T and 4-T devices, to enable accurate and consistent performance evaluation. Furthermore, we propose two stabilized measurement methods for emerging 3-T tandem cells incorporating perovskite subcells: (1) a two-dimensional maximum-power-point tracking (MPPT) approach that continuously tracks both subcells' maximum power points (P MAX ) until convergence to stabilized outputs, and (2) a hybrid approach that combines MPPT for one subcell with stabilized current recording under fixed voltage biases near the P MAX of the other, allowing robust extraction of the overall stabilized P MAX (termed “MPPT + asymptotic P MA X scan” method). These methods directly address the dynamic current responses inherent to perovskite-containing tandems, providing a foundation for meaningful and reproducible performance comparisons.

14 SOLAR ENERGY↗