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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Cost-effective valorization of 2,3-butanediol to high-value chemicals and jet fuel

Here, this work outlines an optimized process for converting 2,3-butanediol (BDO) into sustainable aviation fuel (SAF) and C4 chemicals. BDO is reactively separated from fermentation broth by forming dioxolanes, which are converted to isobutyraldehyde, methyl ethyl ketone (MEK), and 1,3-butadiene. These intermediates are reduced and dehydrated over Cu/ZSM-5 to form alkenes, which can be oligomerized and hydrotreated to jet-range alkanes. Previous BDO-dioxolane-alkene processes are limited by the requirement for a continuous aldehyde source for dioxolane formation. Brønsted acidic zeolites catalyze dioxolane deacetalization to form isobutyraldehyde and MEK in a >2:1 molar ratio, providing an internal, recyclable aldehyde source. Dioxolane formation optimization was performed to achieve >95% dioxolane yields over Amberlyst-15 and minimize isobutyraldehyde recycle. The overall BDO-dioxolane-fuel process yields an alkane mixture that enables at least a 50% v/v blend with Jet-A. Techno-economic analyses and life cycle assessments for this BDO-dioxolane-fuel process yield scenarios with <$2.50 per gallon gas equivalent and >58% reduction in CO2 emissions.

2,3-butanediol↗
DOE OSTI2026

Oceanic fronts shape hemispheric contrasts in polar stratospheric extremes

Sudden Stratospheric Warmings (SSWs) and Polar Stratospheric Clouds (PSCs) exhibit striking inter-hemispheric asymmetries: SSWs are frequent in the Arctic but rare in the Antarctic, while PSCs are more persistent in the Antarctic. Although land–sea thermal contrast and orography (LSCO) have been traditionally invoked to explain these asymmetries, here we show using semi-idealized model experiments that even though LSCO strongly impacts the mean state of SSWs and PSCs, it alone cannot fully account for the observed differences. Using model experiments, we reveal that midlatitude oceanic sea surface temperature (SST) fronts represent a crucial supporting additional driver of the hemispheric stratospheric differences. Like LSCO, SST fronts enhance stratospheric convergence of resolved waves, strengthening the Brewer–Dobson Circulation and inducing high-latitude adiabatic warming. This warming significantly enhances Arctic SSW frequency and strongly suppresses PSC formation. Sub-grid-scale non–resolved wave forcing modulates the stratospheric resolved waves effect. The oceanic impact is dominated by North Pacific SST fronts. Our results highlight the indispensable role of SST fronts in shaping Arctic–Antarctic asymmetries in stratospheric dynamics and associated extremes.

Omrani, Nour-Eddine [Univ. of Bergen (Norway)] (OR↗
DOE OSTI2026

Spectroscopic Demarcation of Emergent Photons and Spinons in a Dipolar-Octupolar Quantum Spin Liquid

The identification of fractionalized excitations in quantum spin liquids (QSLs) remains a central challenge in condensed matter physics. In dipolar-octupolar (DO) pyrochlores, such as Ce 2⁢ Zr 2 ⁢O 7 , the candidate 𝜋-flux quantum spin ice (QSI) state is predicted to host both gapless emergent photons and a continuum of spinons. However, resolving these modes at zero field is complicated by their spectral overlap and the presence of nonmagnetic scattering near zero energy. Here, in this study, we report neutron scattering experiments on Ce 2 ⁢Zr 2 ⁢O 7 under a magnetic field along the [1, 1, 1] direction. In contrast to previous unpolarized studies at zero field that relied on high-temperature subtraction, we use a same-temperature high-field subtraction protocol to isolate the photon and spinon modes. Leveraging the selective coupling of the magnetic field to the dipolar degrees of freedom, we demonstrate the spectroscopic demarcation of these excitations. We observe that weak fields (≈ 0.15 T) suppress the low-energy photon weight while leaving the high-energy spinon continuum robust, albeit hardened. Our results, supported by gauge mean-field theory and exact diagonalization calculations, provide strong evidence for the 𝜋-flux QSI state and introduce a powerful field-tuning protocol for investigating DO-QSLs.

Gao, Bin [Rice University, Houston, TX (United Sta↗
DOE OSTI2026

Insulating ground state and 2−𝑘 magnetic structure of candidate Weyl hydrogen-atom K2⁢Mn3⁢(AsO4)3

The ideal Weyl "hydrogen-atom" semimetal exhibits only a single pair of Weyl nodes and no other trivial states at the Fermi energy. Such a material would be a panacea in the study of Weyl quasi-particles, allowing direct unambiguous observation of their topological properties. The alluaudite-like K2⁢Mn3⁢(AsO4)3 compound was recently proposed as such a material. Here, we use comprehensive experimental work and first-principle calculations to assess this prediction. We find K2⁢Mn3⁢(AsO4)3 crystallizes in the 𝐶⁢2/𝑐 symmetry with a quasi-one-dimensional Mn sublattice, growing as small needle-like crystals. Bulk property measurements reveal magnetic transitions at ≈8 and ≈4 K, which neutron scattering experiments show correspond to two distinct magnetic orders, first a partially ordered ferrimagnetic 𝐤𝟏=(0,0,0) structure at 8 K and a second transition of 𝐤𝟐=(1,0,0) at 4 K to a fully ordered state. Below the second transition, both ordering vectors are necessary to describe the complex magnetic structure with modulated spin magnitudes. Both of the best-fit magnetic structures in this work are found to break the symmetry necessary for the generation of Weyl nodes, though one of the magnetic structures allowed by 𝐤𝟏 does preserve this symmetry. However, the crystals are optically transparent and ellipsometry measurements reveal a large band gap, undermining expectations of semimetallic behavior. Density functional theory calculations predict an insulating antiferromagnetic ground state, in contrast to previous reports, and suggest potential frustration on the magnetic sublattice. Given the wide tunability of the alluaudite structure, we consider ways to push the system closer to a semimetallic state.

Taddei, Keith M [Argonne National Laboratory]↗
DOE OSTI2026

A Tutorial on Bayesian analysis of linear shock compression data

Gas gun and other shock compression experiments often produce shock wave velocity measurements that are linearly associated with particle velocity. Traditionally, this empirical relationship is quantified with a single Hugoniot curve that is estimated using least squares regression. However, for downstream modeling and simulation tasks, it is often more useful to have multiple Hugoniot curves in the pressure–volume plane that are consistent with the data. We employ Bayesian uncertainty quantification methods as a framework for propagating measurement uncertainty through to model parameters and predictions. Specifically, this Tutorial shows how to sample multiple Hugoniot curves in the pressure–volume plane that are consistent with the shock wave-particle velocity measurements in a two-step Bayesian approach. First, we obtain an analytical expression for the posterior distribution of the linear model parameters using Bayesian linear regression. Second, we propagate samples from the posterior distribution through the Rankine–Hugoniot equations to yield Hugoniot curves in the pressure–volume plane. The procedure is demonstrated with publicly available data on argon, copper, and nickel, and compared against bootstrapping and linear regression. The Bayesian procedure is shown to be interpretable, computationally inexpensive, and less sensitive than an alternative bootstrapping approach to the removal of the point in the copper dataset that has the largest particle velocity. As a Tutorial on Bayesian methodology for the shock compression community, we provide several derivations and explanations that make this paper self-contained, and make all code and data available at github.com/llnl/BALSCD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Unraveling interphase-driven failure pathways in LiMn0.6Fe0.4PO4/graphite pouch cells

LiMnxFe1−xPO4 (LMFP) is a promising high-voltage, thermally stable, and earth-abundant cathode material, yet its practical application is limited by interphase instability and Mn dissolution. In this work, we systematically evaluate LiMn0.6Fe0.4PO4/graphite pouch cells using three electrolyte formulations including control carbonate electrolyte, control + 2 wt% vinylene carbonate (VC), and control + 2 wt% VC + 1 wt% 1,3,2-dioxathiolane 2,2-dioxide (DTD), to establish how electrolyte composition governs interphase chemistry and long-term degradation. Electrochemical testing shows that both additives are preferentially reduced prior to ethylene carbonate (EC) during cell formation, generating robust cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI) layers that suppress gas evolution and raise the first-cycle coulombic efficiency to 89.3%. Additionally, the dual-additive electrolyte delivers the most stable performance, retaining over 85% capacity after 600 cycles while minimizing impedance growth under long-term cycling at C/3 and 40 °C. Soft X-ray absorption spectroscopy confirms that VC + DTD effectively suppresses electrolyte oxidation at the cathode surface, and micro-X-ray fluorescence shows substantially reduced Mn dissolution and deposition on the graphite anode. Density functional theory simulations further provided insights into the structural and energetic influences of alkoxide species on the cathode surface, proposing a Mn2+ extraction mechanism. The combined experimental and computational findings establish a mechanistic link between electrolyte composition and interphase evolution, highlighting the effectiveness of electrolyte engineering for extending the operational lifetime of LMFP-based lithium-ion batteries.

Chak, Chanmonirath Michael↗
DOE OSTI2025

Tunable shear thickening, aging, and rejuvenation in suspensions of shape-memory-endowed liquid crystalline particles

The morphological features of particles, notably shape anisotropy, critically influence the rheological properties of dense suspensions, spanning both natural and engineered systems. This work explores the potential of using shape memory particles to dynamically regulate suspension fluid flow through controllable shape transformations. First, we synthesize shape-memory particles with programmable anisotropy from liquid crystal elastomers, such that the stiffness and shapes of the particles can be tuned by manipulating temperature. Our findings reveal that suspensions from such particles exhibit significant tunability in shear thickening behavior, transitioning from discontinuous shear thickening to a Newtonian-like response within a narrow temperature range of 60 ° C. This capability to modulate rheological responses in situ presents an approach for addressing processing challenges in many applications where control over flow behavior is paramount. Furthermore, we also show that suspensions composed of these anisotropic particles can undergo physical aging, and evolve into a glassy state. This state can be escaped upon activation of the shape memory effect. This reversibility underscores the potential for using such materials to engineer systems that can enter or come out of kinetic arrest by leveraging internal mechanical responses to external stimuli. The insights gained here not only broaden our understanding of the interplay between particle geometry and suspension dynamics but also pave the way for leveraging ensembles of stimuli-responsive objects to precisely control collective behaviors in many-body systems.

Science & Technology - Other Topics↗
DOE OSTI2026

Massive neutrinos and interacting dark matter look alike through the lens of lensing

Here, we demonstrate that the suppression in the lensing power spectrum of the cosmic microwave background (CMB) caused by massive neutrinos can be mimicked by dark matter-baryon interactions at the precision of next-generation CMB experiments. Thus, a determination of neutrino masses from the CMB lensing power spectrum may be compromised. We illustrate the degeneracy for a dark matter-proton cross section ∝ $v$ –4 , which arises in the t-channel exchange of an ultralight mediator in the nonrelativistic limit.

cosmological parameters↗
DOE OSTI2023

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging↗
DOE OSTI2022

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Effectively Considering the Distribution System in Integrated Resource Plans

While electricity planning practices vary by state and utility based on utility type and market structure, integrated resource planning (IRP) remains a prominent vehicle — even in states with centrally-organized wholesale electricity markets. IRP focuses on meeting forecasted long-term electricity needs. Typically, utilities have not considered impacts of design and operation of the low-voltage distribution network in IRP. With advanced capabilities of grid-edge technologies to generate and store electricity and provide load flexibility, and large utility investments in distribution systems, it's increasingly important to consider at least some distribution planning elements in IRP. This report considers the value proposition for doing so, such as reducing utility costs through resource co-optimization and strategic siting of grid-edge resources, and idenfities the most important touchpoints between planning for bulk power and distribution systems and provide a range of tactics for integrating these two processes.

Relf, Grace [Lawrence Berkeley National Laboratory↗
DOE OSTI2026

Self-Leveling Inks for Printing Ultra-uniform Perovskite Solar Modules by Flexography

The report describes the development of scalable manufacturing methods for high-performance, stable perovskite solar modules using flexographic printing. The project developed self-leveling perovskite inks that exploit Marangoni flows to reduce coating defects and improve large-area film uniformity. Bayesian optimization was integrated with high-throughput photoluminescence mapping and photovoltaic measurements to efficiently optimize ink formulations and printing conditions. The resulting printed perovskite solar cells achieved champion power conversion efficiencies above 21.6%, with median efficiencies exceeding 20% across large device batches. At the module scale, printed devices achieved active-area efficiencies up to approximately 17.3% on 25 cm² substrates. The project also demonstrated improved performance and stability using additively patterned interconnections compared with laser-scribed controls. Overall, the work establishes a data-driven, roll-compatible pathway toward high-throughput, low-capital-cost manufacturing of uniform and stable perovskite photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2026

Optimal experimental design using eigenvalue-based criteria with Pyomo.DoE

New developments in automated optimal experimental design within the PSE+ software ecosystem. Advancements in user experience (to reduce the time taken to perform optimal experiment design) and computational capabilities (allowing more diverse experimental design) are shown with an example relevant to critical minerals and materials. Also, a small tutorial on science-based optimal experimental design and novel contributions therein are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Programmable Digital Devices used in Advanced Reactors

This paper introduces the concepts of common cause failure, diversity, and defense-in-depth used by the nuclear industry to analyze resilience in reactors. A survey of publicly traded and private companies building advanced reactors and their licensing status is presented. Safety and non-safety systems found in the NuScale Power design are summarized and the likely hardware and software categories used by those systems are enumerated. The importance of industry partners is highlighted. This paper also identifies an alternate path forward without industry partners to advance the knowledge needed to use artificial intelligence to analyze HBOMs and SBOMs to better understand reactor resiliency.

cybersecurity↗
DOE OSTI2025

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional microscopy is a practical tool for diagnosis and screening ofSchistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection ofS. haematobiumthat combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. We collected BF and DF images of urine samples, many of them containingS. haematobiumeggs, during two different field studies in Côte d’Ivoire using a mobile phone-based microscope, the SchistoScope. We then trained separate egg-detection ML models and compared the patient-level performance of BF and DF models alone to combinations of BF and DF models, using annotations from trained microscopists as the gold standard. We found that models trained on DF images, and almost all BF and DF combinations, performed significantly better than models trained on BF images only. When models were trained on images from the first field study (n = 349 patients, 748 images of each contrast), patient-level classification performance on patient images from the second study (n = 375 patients, 752 images of each contrast) met the WHO Diagnostic Target Product Profile (TPP) sensitivity and specificity for the monitoring and evaluation use case (sensitivity for all models and combinations was >75% when evaluated at a confidence score threshold that resulted in specificity >96.5%). When we used images from both field studies for the training set, performance of the models was improved. Overall, this work shows that the use of DF and BF increases the performance of ML models on images from devices with low-cost optics, while retaining the portability, power, and time-to-results of the WHO’s diagnostic TPP. DF requires no additional sample preparation and does not increase the complexity of the imaging system. It thus offers a practical means to improve performance of automated diagnostics forS. haematobiumas well as other microscopy-based diagnostics.

Infectious Diseases↗
DOE OSTI2026

Electrochemical Deconstruction of Ortho-Phthalate Plasticizers and Recovery of Plasticizing Moieties

Electrochemical methods for the direct reduction of alkyl esters have been understudied but provide a potential advantage for addressing specific waste streams given that such strategies often require only a minimal chemical profile. One such waste stream that could benefit from electrochemical remediation is poly(vinyl chloride) (PVC) plastics. PVC recycling often faces challenges due to the complexity of such waste. Solvent-based recycling methods pose several advantages for addressing post-use PVC; however, such methods are complicated by the high amounts of toxic legacy plasticizers (ortho-phthalates) present in PVC. A potential solution to addressing such phthalates is to address them electrochemically, coupled with recovery of the resulting valuable products. Presented herein is an optimized electrochemical method for ester activation that is leveraged to separate and recover the aromatic and alkyl components of ortho-phthalate plasticizers. The resulting aliphatic alcohols may be reused to prepare other non-toxic plasticizers. This electro-degradation method is demonstrated on six phthalates that have been identified to pose health concerns in addition to plasticizers recovered from commercial samples of PVC.

di-(2-ethylhexyl) phthalate↗
DOE OSTI2026

Sodium-Ion Battery Cathode with Dominating Copper and Oxygen Redox Chemistry

Sodium-ion batteries offer low-cost energy storage solutions for the grid and electric vehicles, leveraging the established "rocking-chair" Li-ion design and the natural abundance of sodium. However, SIBs face challenges such as relatively lower voltage and capacity than lithium-ion batteries, as well as dependence on nickel resources. Here, in this work, a new nickel-free cathode material, Na 0.75 Li 0.08 Cu 0.25 Mn 0.66 O 2 , was designed and synthesized. This material has a capacity of ~125 mAh/g and an average discharge voltage of 3.5 V. Notably, more than one-third of the capacity arises from lithium substitution of Cu (~8 mol.%) and high voltage activation to 4.6 V. Multimodal synchrotron x-ray characterization combining spectroscopy, microscopy, and scattering reveal the capacity is primarily from the redox of copper and oxygen, with a minor contribution from the manganese redox. Lithium substitution alters the phase transition mechanism from a two-phase transition in P3-Na 2/3 Cu 1/3 Mn 2/3 O 2 to a solid-solution in Na 0.75 Li 0.08 Cu 0.25 Mn 0.66 O 2 , enhancing the reversibility of this material.

25 ENERGY STORAGE↗