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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Glassy Word Problems: Ultraslow Relaxation, Hilbert Space Jamming, and Computational Complexity

We introduce a family of local models of dynamics based on “word problems” from computer science and group theory, for which we can place rigorous lower bounds on relaxation timescales. These models can be regarded either as random circuit or local Hamiltonian dynamics and include many familiar examples of constrained dynamics as special cases. The configuration space of these models splits into dynamically disconnected sectors, and for initial states to relax, they must “work out” the other states in the sector to which they belong. When this problem has a high time complexity, relaxation is slow. In some of the cases we study, this problem also has high space complexity. When the space complexity is larger than the system size, an unconventional type of jamming transition can occur, whereby a system of a fixed size is not ergodic but can be made ergodic by appending a large reservoir of sites in a trivial product state. This finding manifests itself in a new type of Hilbert space fragmentation that we call fragile fragmentation. We present explicit examples where slow relaxation and jamming strongly modify the hydrodynamics of conserved densities. In one example, density modulations of wave vector q exhibit almost no relaxation until times O ( exp ( 1 / q ) ) , at which point they abruptly collapse. We also comment on extensions of our results to higher dimensions. Published by the American Physical Society 2024

Physics↗
DOE OSTI2025

Defect Complexes in CrSBr Revealed Through Electron Microscopy and Deep Learning

Atomic defects underpin the properties of van der Waals materials, and their understanding is essential for advancing quantum and energy technologies. Scanning transmission electron microscopy is a powerful tool for defect identification in atomically thin materials, and extending it to multilayer and beam-sensitive materials would accelerate their exploration. Here, we establish a comprehensive defect library in a bilayer of the magnetic quasi-1D semiconductor CrSBr by combining atomic-resolution imaging, deep learning, and calculations. We apply a custom-developed machine learning work flow to detect, classify, and average point vacancy defects. This classification enables us to uncover several distinct Cr interstitial defect complexes, combined Cr and Br vacancy defect complexes, and lines of vacancy defects that extend over many unit cells. We show that their occurrence is in agreement with our computed structures and binding energy densities, reflecting the intriguing layer interlocked crystal structure of CrSBr. Our ab initio calculations show that the interstitial defect complexes give rise to highly localized electronic states. These states are of particular interest due to the reduced electronic dimensionality and magnetic properties of CrSBr and are, furthermore, predicted to be optically active. Our results broaden the scope of defect studies in challenging materials and reveal new defect types in bilayer CrSBr that can be extrapolated to the bulk and to over 20 materials belonging to the same FeOCl structural family.

deep learning↗
DOE OSTI2025

Sparsity dependence of Krylov state complexity in the SYK model

We study the Krylov state complexity of the Sachdev-Ye-Kitaev (SYK) model for 𝑁 ≤28 Majorana fermions with 𝑞-body fermion interaction with 𝑞 =4, 6, 8 for a range of sparse parameter 𝑘 that controls the number of remaining terms in the original SYK model after sparsification. The critical value of 𝑘 below which the model ceases to be holographic, denoted 𝑘 𝑐 , has been subject of several recent investigations. Using Krylov complexity as a probe, we find that the peak value of complexity does not change as we increase 𝑘 beyond 𝑘 ≥ 𝑘 min at large temperatures. We argue that this behavior is related to the change in the holographic nature of the Hamiltonian in the sparse SYK-type models such that the model is holographic for all 𝑘 ≥ 𝑘 min ≈ 𝑘 𝑐 . Our results provide a novel way to determine 𝑘 𝑐 in SYK-type models.

gauge-gravity dualitites↗
DOE OSTI2025

Full complex amplitude control of second-harmonic generation via electrically tunable intersubband polaritonic metasurfaces

Nonlinear intersubband polaritonic metasurfaces based on coupling of the intersubband nonlinear optical response of quantum-engineered semiconductor heterostructures and electromagnetic modes of nanoresonators provide efficient frequency mixing with moderate pump intensities. The resonant nonlinear optical response, represented as a complex function, can be modulated via Stark tuning of intersubband transition energies under applied voltages. However, achieving full complex amplitude control (both phase and magnitude) remains challenging. In this work, we present and experimentally validate electrically tunable nonlinear intersubband polaritonic metasurfaces that achieve complete complex amplitude control for second-harmonic generation (SHG). Through a design featuring two in-plane flipped meta-atoms per unit cell, we achieve complete electrical control of both the amplitude and phase of the metasurface second-order nonlinear susceptibility, with a tuning range of 0 to 30 nm V −1 for the magnitude and 0-2π for the phase of the nonlinear optical response. Using these properties, we achieve complete on-off SHG modulation and beam diffraction tuning through electrically controlled amplitude and phase gratings.

Science & Technology - Other Topics↗
DOE OSTI2025

Unveiling phase evolution of complex oxides toward precise solid-state synthesis

The precise synthesis of high-purity materials is crucial in accelerating materials discovery. However, the lack of theoretical understanding and practical guidance poses challenges, particularly for materials with compositional and structural complexity. Here, we propose a feasible principle toward synthesizing complex inorganic solids. This principle involves the introduction of an inducer that induces crucial intermediates, which in turn guide the synthesis pathway toward the target materials through structural templating, named inducer-facilitated assembly through structural templating (i-FAST). We validate this principle with three distinct oxides: garnet Li6.5La3Zr1.5Ta0.5O12, perovskite BaCo0.8Sn0.2O3, and pyrochlore Gd1.5La0.5Zr2O7. This structural templating approach enables synthesis along predesigned pathways, forming intermediates that are thermodynamically favored for prior formation and kinetically preferred for the final product, resulting in precisely synthesizing high-purity target materials. This study not only represents a substantial advancement in comprehending the interplay between thermodynamics/kinetics and phase evolution in complex solid synthesis but also provides an effective strategy for guiding exploratory solid-state synthesis.

Yang, Lin↗
DOE OSTI2024

The ECP SICM project: Managing complex memory hierarchies for exascale applications

The Exascale Computing Project (ECP)’s Simplified Interface to Complex Memories (SICM) effort focuses on developing universal interfaces for discovering, managing, and sharing data across complex memory hierarchies. These facilitate the exploitation of emerging memory technologies and support precise control over their various trade-offs such as high-bandwidth versus low-latency, persistent versus ephemeral, high-capacity versus low-capacity, and near-CPU versus near-GPU. SICM comprises three interrelated components: a low-level interface, a high-level interface, and a persistent-heap interface. The low-level SICM interface is intended for system and run-time developers as well as expert application developers who prefer full control of the memory objects used within their application. The high-level SICM interface builds upon the low-level interface, employing application-level profiling and analysis to optimize data management for complex memory hierarchies. The persistent-heap interface provides applications with a persistent memory allocator that can allocate custom C++ data structures in both block-storage and byte-addressable persistent memories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Nanoparticle self-assemblies with modern complexity

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigating Soil Organic Matter Complexation using Spectral Induced Polarization

Spectral induced polarization (SIP) laboratory experiments were conducted to determine the sensitivity of this method to the formation of soil organic matter (SOM) complexes, with a long-term goal of field-scale monitoring. There are few SIP experiments that have explored this topic, yet understanding the dynamic behavior and interactions of SOM at the field scale could provide insight into soil fertility and health which influences crop yields, microorganisms that degrade organic pollutants, and carbon stabilization. We present the results of three experiments where the iron oxide, ferrihydrite (Fhy), was used to coat different media, and then the OM compound pentaglycine (PG) was pulse injected to form SOM complexes. SIP data was collected during these injections to capture any surface complexation changes. These experiments were performed in 1) a fluidic cell containing a micromodel, 2) a column containing Fhy coated ceramic beads and 3) a column containing Fhy coated Accusand®. Our results show a higher frequency response (defined here as > 1 Hz) in all three experiments, with the largest amplitude response after the first PG injection (Figure S.1). The repeatability of this response is encouraging and supporting data collected on the Accusand® experiment provides preliminary insight into the mechanisms controlling the SIP signatures. Sampling of fluid conductivity $σ_w$ and pH may indicate deprotonation of SOM occurring or rapid adsorption and release of protons from the Fhy sites. However additional experiments are needed to identify and confirm the primary and secondary reactions impacting the SIP response. We are looking towards other opportunities to continue this work, particularly to repeat experiments while collecting supporting datasets.

58 GEOSCIENCES↗
DOE OSTI2025

Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity Using Phase-Field Simulations

The interactions among in situ stress, rock fabric, wellbore geometry, natural fractures, and other natural or man-made defects create highly complex fracture trajectories in the near-wellbore region, far more intricate than those in the far-field. These near-wellbore complexities are critical for the Utah FORGE project and Enhanced Geothermal Systems (EGS) in general. Frictional pressure loss in the near-wellbore region during stimulation can significantly influence the growth of far-field fractures, while pressure losses during circulation serve as a major source of energy dissipation. Near-wellbore fracture complexities are often observable through image logs, offering valuable insights into in situ stress characteristics. However, leveraging this information requires a high-fidelity model capable of capturing the interplay among the diverse factors influencing fracture behavior.

58 GEOSCIENCES↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Y-12 National Security Complex Biological Monitoring and Abatement Program—2024 Calendar Year Report

This report provides the results of the CY 2024 sampling of East Fork Poplar Creek (EFPC) as part of the Y-12 National Security Complex (Y-12) Biological Monitoring and Abatement Program (BMAP). The results are presented in the context of historical trends. The Y-12 BMAP was developed in 1985 to demonstrate that the effluent limits established for Y-12 protected the classified uses of the receiving stream, particularly the growth and propagation of aquatic life (Loar et al. 1989). Over the years, the BMAP has become an important and valuable long-term measure of stream conditions resulting from actions and activities at the Y-12 Complex. The BMAP currently consists of three tasks: (1) bioaccumulation monitoring, (2) benthic macroinvertebrate community monitoring, and (3) fish community monitoring. The benthic macroinvertebrate community monitoring task includes studies to evaluate the receiving stream’s biological integrity annually in comparison with Tennessee Water Quality Criteria following Tennessee Department of Environment and Conservation (TDEC) protocols. In addition to presenting the EFPC biological monitoring results, this report includes results from Comprehensive Environmental Response, Compensation, and Liability Act–funded BMAP programs in Bear Creek and McCoy Branch (presented in Appendixes A and B, respectively), as required in the Y-12 National Pollutant Discharge Elimination System (NPDES) permit. Additional biological testing at the Y-12 Complex includes toxicity testing of select storm drains as required in the NPDES permit. Although toxicity testing is not formally part of the BMAP, toxicity testing results from 2024 are provided in Appendix C.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Position Papers for Inverse Methods for Complex Systems under Uncertainty Workshop

The ability to solve inverse problems – inferring unknown parameters, structures, or states of a system from observed data – is essential for advancing scientific discovery and innovation capabilities for the DOE mission. Basic research needs and challenges are particularly acute in emerging areas such as the interactive, data-driven, modeling and simulation of digital twins; decision support for experiments at DOE scientific user facilities; and for other complex systems and workflows. Inverse problems are at the heart of understanding and controlling complex systems due to factors such as observational data with varying modalities and fidelities, inherent uncertainties in physical measurements and numerical models, and the computational demands of rapid and high-fidelity simulations. The convergence of recent scientific computing trends – scientific machine learning, artificial intelligence, and computing advances such as exascale computing – is creating unprecedented opportunities. These advancements offer the potential to revolutionize how we approach inverse problems to extract actionable insights with the required level of accuracy and computational efficiency. This workshop and the Call for Position Papers are vital steps in bringing together experts to collectively explore and identify the new computational and mathematical directions needed in inverse methods for complex systems under uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Screen-Printed SHJ Solar Cells with Complex Silver Inks

Metallization using complex metal inks has gained significant research interest due to its cost-effectiveness and ability to achieve performance comparable to traditional nanoparticle pastes. This study introduces the use of complex silver (Ag) inks applied via industrial screen-printing for silicon heterojunction (SHJ) solar cell metallization. The printed Ag lines exhibit a contact resistivity on SHJ tin-doped indium oxide (ITO) surfaces as low as approximately 0.2-12 mO cm2. Photoluminescence imaging reveals minimal surface passivation degradation (iVoc < 3.5 mV), while scanning electron microscopy (SEM) shows a denser structure compared to Ag layer from nanoparticle pastes. The printed Ag grid features thin (approximately 1 micrometer), continuous fingers approximately 100-120 micrometer wide, significantly thinner than conventional approximately 20-30 micrometer fingers produced with nanoparticle-based pastes. Double printing achieves SHJ device efficiencies exceeding 20%, the highest reported for industrial solar cell precursors using this technology. These findings highlight the potential of complex Ag inks as a sustainable alternative to particle-based pastes, reducing Ag consumption and processing temperatures without compromising efficiency.

14 SOLAR ENERGY↗
DOE OSTI2025

5f-Shell Covalency in Actinide Complexes

This talk will focus on the theoretical description & analysis of 5f-shell covalency in actinide complexes, as well as the manifestation of this covalency in spectroscopic parameters such as the pre-edge peak energies and intensities in X-ray absorption near-edge structure (XANES) and related types of spectra, or ligand NMR chemical shifts, according to quantum chemical calculations. We are now able to analyze 5f covalency in the context of the participating atomic orbitals, their energies and interactions in a given molecule, and their overlap. A related issue is the assignment of oxidation states. Examples that will be discussed in the talk are [AnCl6](2-) with An = U, Np, Pu, various organometallic complexes with U and Th, and a recently reported ‘berkelocene’ sandwich complex.

Autschbach, Jochen↗
DOE OSTI2026

Luminescent Zr Complexes with Long-lived Intraligand Charge Transfer Excited States

Understanding and establishing design principles to tune the excited states of earth-abundant sensitizers is crucial for identifying new photosensitizers for sustainable technological advancements. Here, we report a series of three bis Zr (IV) complexes of tridentate, dianionic ligands incorporating two phenoxide donors and aza arene acceptors of increasing electron affinity (pyridine < pyrimidine < pyrazine ) that are air and water-stable. These complexes emit via thermally assisted delayed fluorescence from an intraligand charge transfer excited state with varying metal contributions. The electronic structural changes from different acceptors vary the excited state character and the photophysical properties significantly between the complexes. The variation in photophysics that includes emission lifetime (76 μs to 265 ns), intersystem crossing (ISC) lifetime ( 390 – 290 ps), and the energy difference between the singlet and triplet excited states (∆EST. 170 -100 meV). We observe solvent-independent ISC rates when the excited state has metal contributions (acceptor = pyridine), and the ISC rates vary significantly with solvent polarity when the excited state is an intra-ligand charge transfer state (acceptor = pyrimidine and pyrazine). Transient absorption measurements provided the basis spectra and verified the metal contribution in the excited state. This work provides a basis for developing new sensitizers based on Zr (IV) by providing design principles that can be used to modulate the character of the excited state and its photophysics.

Nattikallungal, Thabassum A. [University of Southe↗
DOE OSTI2026

Photochemically Triggered Para-Hydrogen-Induced Polarization in a Diplatinum Trihydride Complex

Transition metal complexes containing platinum(II) are of substantial interest for their rich photophysics, biomedical applications, and catalytic function. Nuclear magnetic resonance (NMR) spectra of the spin-1/2 isotope, 195Pt, offer detailed insights into the molecular structures of closed-shell Pt(II) complexes, including solvent effects. However, the sensitivity of 195Pt NMR is mediocre, and its NMR spectra are typically complex. As a result, 1H NMR spectra are used as the primary characterization tool for Pt(II)-based molecules, relying on J-coupling to the 195Pt nucleus to provide structural information from the resulting satellite peaks. In efforts to significantly improve the information content from 1H NMR spectroscopy in a Pt(II)-containing molecule, we utilize [Pt2H2(μ-H)(μ-dppm)2]PF6, where dppm is bis(diphenylphosphino)methane, and leverage its established photoactivity with UV light and H2 for para-hydrogen-induced polarization (PHIP) to enhance the resultant NMR signals, revealing numerous 195Pt J-couplings. Moreover, we investigate direct solvent hyperpolarization effects, as well as the indirect effects of solvent on the various observed J-coupling constants in the Pt species, demonstrating correlations with both Lewis basicity and dielectric constant.

Brown, Emily E. [Department of Chemistry; North Ca↗
DOE OSTI2024

Simulation-based inference for parameter estimation of complex watershed simulators

High-resolution, spatially distributed process-based (PB) simulators are widely employed in the study of complex catchment processes and their responses to a changing climate. However, calibrating these PB simulators using observed data remains a significant challenge due to several persistent issues, including the following: (1) intractability stemming from the computational demands and complex responses of simulators, which renders infeasible calculation of the conditional probability of parameters and data, and (2) uncertainty stemming from the choice of simplified representations of complex natural hydrologic processes. Here, we demonstrate how simulation-based inference (SBI) can help address both of these challenges with respect to parameter estimation. SBI uses a learned mapping between the parameter space and observed data to estimate parameters for the generation of calibrated simulations. To demonstrate the potential of SBI in hydrologic modeling, we conduct a set of synthetic experiments to infer two common physical parameters – Manning's coefficient and hydraulic conductivity – using a representation of a snowmelt-dominated catchment in Colorado, USA. We introduce novel deep-learning (DL) components to the SBI approach, including an “emulator” as a surrogate for the PB simulator to rapidly explore parameter responses. We also employ a density-based neural network to represent the joint probability of parameters and data without strong assumptions about its functional form. While addressing intractability, we also show that, if the simulator does not represent the system under study well enough, SBI can yield unreliable parameter estimates. Approaches to adopting the SBI framework for cases in which multiple simulator(s) may be adequate are introduced using a performance-weighting approach. The synthetic experiments presented here test the performance of SBI, using the relationship between the surrogate and PB simulators as a proxy for the real case.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

A parametric study of the complexity of sequential decoders, volume 1

The complexity and performance of practical sequential decoders were studied. Upon comparing sequential decoders with Viterbi decoders, it was found that sequential decoders outperform Viterbi decoders at low data rates (19.2 to 76.8 kbps) for the same complexity. However, Viterbi decoders are less complex than sequential decoders at high data rates (9.1 Mbps) for the same performance.

Huth, G. K.↗