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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
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

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↗
DOE OSTI2025

Selectivity of tris complexation for Ni(II), Co(II), and Fe(II) and its effect on carbonate precipitation under alkaline conditions

Simultaneous critical element recovery and ex-situ carbon mineralization of low-grade ultramafic deposits have garnered increasing interest. Understanding the selectivity of metal complexing organic ligands for various divalent metals present in ultramafic rocks during carbonate mineralization is required to optimize this process. Here we evaluate 2-amino-2-(hydroxymethyl)-1,3-propanediol (i.e., Tris) as a model for bidentate ligands that bind divalent metals with both amine and alcohol groups in alkaline conditions (pH 8–10.5) at 25 °C and 80 °C in carbonate-buffered solutions. Protonated Tris forms a stronger complex with metal ions and is selective for trace metals with Ni(II) > Co(II) > Fe(II) during carbonate precipitation, with the rates decreasing but selectivity increasing at lower temperature and lower pH. At 25 °C, metastable amorphous hydrated carbonates form, regardless of the amount of Tris present or pH values. At 80 °C and pH 8, the Co and Fe carbonates that form are a mixture of rosasite-group minerals (Co 2 CO 3 (OH) 2 (H 2 O) and Fe 2 CO 3 (OH) 2 ) and pure carbonates (sphaerocobaltite: CoCO 3 and siderite: FeCO 3 ), with the latter more stabilized with increasing Tris concentration. In mixed metal solutions without Tris at 25 °C where Fe:Ni or Fe:Co is 2:1, Fe increases the rates of Ni or Co carbonate precipitation. However, with increasing Tris concentration the presence of Ni or Co inhibits Fe carbonate precipitation. At 80 °C without Tris, Ni or Co substitute into the iron chukanovite (Fe 2 CO 3 (OH) 2 ) lattice, increasing Ni or Co carbonate precipitation rates. Increasing Tris concentration only slightly inhibits Fe and Co precipitation, but slows Ni precipitation up to 10 times, with Fe progressively partitioning into more pure carbonate phases with distinct crystalline morphologies. These findings suggest bidentate amine-bearing ligands may be effective at Ni and Co recovery during carbon mineralization of Fe-bearing ultramafic deposits at relatively low temperatures and slightly alkaline pH.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

From high-entropy ceramics to compositionally complex ceramics and beyond

Over the past decade, the field of high-entropy ceramics (HECs) has expanded rapidly to encompass a broad range of oxides, borides, silicides, and other ceramic solid solutions. In 2020, we proposed extending HECs to compositionally complex ceramics (CCCs), where non-equimolar compositions and the presence of long- or short-range order, although reducing configurational entropy, create new opportunities to tailor and enhance properties, often surpassing those of higher-entropy counterparts. Along these lines, several fundamental scientific questions arise. Is the entropy in HECs truly high? Is maximizing entropy always desirable? In this perspective article, I revisit key concepts and terminologies and highlight emerging directions, including dual-phase CCCs, ultrahigh-entropy phases, and novel processing routes such as ultrafast reactive sintering. I propose that exploring compositional complexity across vast non-equimolar spaces, together with exploiting correlated disorder (coupled chemical and structural short-range order), represents a transformative strategy for designing ceramics with superior performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

From cytoplasm to lumen—mapping the free pools of protein subunits of three photosynthetic complexes using quantitative mass spectrometry

The phycobilisome (PBS) captures light energy and transfers it to photosystem I (PSI) and photosystem II (PSII). Which and how many copies of protein subunits in PBSs, PSI, and PSII remain unbound in thylakoids are unknown. Here, quantitative mass spectrometry (QMS) was used to quantify substantial pools of free extrinsic subunits of PSII and PSI. Interestingly, the membrane intrinsic PsaL is 3-fold higher than PsaA/B. This scenario complements the static structures of these complexes as revealed by X-ray crystallography and cryo-EM. Furthermore, the ratios of ApcG and photoprotective OCP over PBS indicate a pool of extra ApcG. The 2.5 ratio of CpcG-PBS over CpcL-PBS improves our understanding of these light-harvesting complexes involved in energy capture and photoprotection in cyanobacteria.

cyanobacteria↗
DOE OSTI2026

Complex-Concentrated Anion Doping Enables Ultra-Stable Lattice Oxygen and Structural Integrity in Lithium-Rich Layered Oxide Cathodes

Lithium- and manganese-rich layered oxides (LMR) stand out as next-generation lithium-ion cathode chemistries, which harness both transition-metal and lattice-oxygen redox processes to deliver exceptional capacity and energy density. However, their full potential is hindered by intrinsic oxygen instability and structural degradation, resulting in pronounced voltage fade and capacity decay. Here, we present a complex-concentrated anion-doping paradigm in which multiple anions, F, Br, and S, are incorporated into the oxygen sublattice to enhance oxygen-redox and structural stability. X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy confirm ultra-stable local oxygen coordination environments during long-term cycling, with detrimental phase transformations and oxygen-loss-induced cavitation dramatically inhibited. Notably, we show that the characteristic LiTM6 transition metal (TM) honeycomb ordering is preserved even after electrochemical cycling. Concurrently, this strategy yields an unprecedented volume change of only 0.63% upon charging to 4.8 V vs. Li+/Li, achieving the first zero-strain LMR cathode. The resulting LMR cathode delivers ultralow voltage fade (1 mV per cycle during the first 100 cycles and becomes negligible in subsequent cycles) and outstanding energy retention (93% after 200 cycles) in a pouch cell configuration. Our complex-concentrated anion-doping concept establishes a broadly applicable strategy for resolving chemo-mechanical failure mechanisms in ceramic intercalation electrodes for next-generation energy storage.

Li-ion batteries↗
DOE OSTI2024

Rapid particle generation from an STL file and related issues in the application of material point methods to complex objects

Abstract In this paper, we focus on three issues related to applications of material point methods (MPMs) to objects with complex geometries. They are material point generation, compatibility of material points with a mesh, and sensitivity to mesh orientation. An efficient method of generating material points from a stereolithography (STL) file is introduced. This material point generation method is independent of the mesh used in MPM calculations. The compatibility between the material points and the mesh is then studied. We also show that the original MPM and the dual domain material point (DDMP) method are sensitive to mesh orientation. These issues are related to the calculation of the internal force and are concerns of the MPMs. They become more prominent when MPMs are applied to complex geometries. Our numerical results show that the recently developed local stress difference (LSD) algorithm (Perez et al. in J Comp Phys 498:112681, 2024) can be used to effectively address them.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Local chemical ordering of a neutron-irradiated CrFeMnNi compositionally complex alloy

While ion-irradiation studies are a critical first step in studying compositionally complex alloys (CCAs) for nuclear applications, they do not capture all the microstructural changes occurring under the low irradiation dose rates and different particles’ scattering patterns experienced in a nuclear reactor setting. To explore these phenomena in reactor-relevant conditions for the first time in CCA, the single-phase solid-solution Cr 10 Fe 30 Mn 30 Ni 30 was neutron irradiated up to 6.61 displacements per atom at 395 and 579 °C. Irradiation-enhanced local chemical ordering (LCO) well beyond the range of short range ordering was observed, and is predicted to be the precursor to the precipitation of a coherent Ni-Mn L1 0 phase and a Cr-rich α’ phase, though TEM analysis did not indicate the presence of either in any irradiation condition. The line density of faulted dislocation loops decreased from 6.47 to 1.69 ∙ 10 15 m -2 from 3.43 to 6.61 dpa at 579 °C despite no appreciable faulted loop content in the unirradiated material. LCO is expected to increase the complexity of the energy landscape within this alloy, restricting interstitial point defect mobility and creating local regions of greater stacking fault energy. These contribute to the negative correlation between irradiation dose and faulted dislocation loop density in this study, as well as the lack of void swelling observed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accurate and rapid acoustic damage characterization in complex structures using sparse sensor networks and deep learning models

Damage diagnosis in critical components is essential for ensuring the safety and reliability of operations across industries, spanning manufacturing, aerospace, and energy. Traditional acoustic nondestructive testing methods primarily focus on detecting defects through the direct scattering of single-mode incident waves from the damage, which limit their applicability to simple structures and small inspection areas. Our earlier research demonstrated that machine learning algorithms combined with sparse sensor networks can identify critical defect signatures even from multiply scattered, multi-mode acoustic signals, indicating the potential for improved defect inspection in complex, real-world structures. In this work, we demonstrate the successful implementation of this approach in a fixed sensor configuration to rapidly and accurately detect simulated defects in a geometrically complex, real-world structure, a brake rotor hub. Three different types of defects were physically simulated on the surface of the hub, and the collected data were used to train an autoencoder-based deep learning model. Two models were tested, one using single measurements and the other using multiple measurements taking advantage of the spatial distribution of the sensor network. After training, the multi-measurement model achieved 100 % accuracy in identifying, classifying, and locating unseen, unique damages. This work illustrates the potential of the proposed method for a wide range of industrial applications.

36 MATERIALS SCIENCE↗