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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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526 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Transforming Windows from Energy Liabilities to Zero-Energy Assets: Next-Generation Solutions for Buildings

Windows have traditionally contributed to a building's HVAC load, but they can also become a source of net energy gain or even operate as zero-energy components. For heating applications, highly insulating windows can harness more solar heat than the energy lost through them, transforming windows from energy liabilities to assets. Dynamic glazings provide further benefits by regulating solar heat gain, reducing cooling loads in summer and heating demands in winter. This simulation study focuses on developing the next generation of zero-energy windows (ZEW) for residential new construction. Through annual energy simulations across climate zones 1-8, ZEW performance benchmarks were established based on current code-level buildings, and we've identified the regions where meeting ZEW standards are most achievable. This work evaluates both static and dynamic window technologies, assessing their effects on annual energy use and cost. Key findings demonstrate that ZEW performance is achievable across diverse climate zones, with specific regional requirements. Most climate zones from 3-8 can achieve ZEW with specific configurations, while some warm climates (1-2) appear challenging for ZEW implementation. Climate zones 4-6 consistently allow for zero energy window implementation, offering multiple pathways through either static or dynamic window technologies. Colder climate zones (7-8) ZEW products allow for higher SHGC values while requiring low U-values.

Yu, Lili↗
DOE OSTI2026

Tunable magnetic excitations in the honeycomb antiferromagnet (Co,Ni)⁢TiO3

The solid solution of the honeycomb antiferromagnet (AFM) Co0.5⁢Ni0.5⁢TiO3 (CNTO) was synthesized by mixing a 1:1 molar ratio of CoTiO3 (CTO) and NiTiO3 (NTO). Powder neutron scattering was used to determine the structure and magnetic spectrum, where the nuclear and magnetic structures resemble those of the end members. The Néel temperature (T𝑁 = 27 ± 1 K), the ordered magnetic moment (M = 2.29 ± 0.03 𝜇𝐵 per magnetic ion), and lattice parameters are intermediate between those of the two. From inelastic neutron scattering, it is observed that the magnon density of states (MDOS) extends up to 13 meV, and the interaction can be described by an XXZ-type magnetic Hamiltonian. Above 15 meV, spin-orbit excitons (SOEs) are observed similarly to those in CTO, but with modified spin-orbit crystal-field splitting because of the substitution of Ni at Co sites, and the disorder induced by the Ni substitution modifies the spin-orbit crystal field. Thus, the magnetic dynamics of the CNTO cannot be described as a simple average of the two parent compounds.

Rathnayaka, Srimal [University of Virginia, Charlo↗
DOE OSTI2026

Valorization of consolidated bioprocessing residues for bioplastics

This study demonstrates an organic solvent-free processing strategy to valorize consolidated bioprocessing (CBP) residues, from switchgrass and poplar biomass, into functional poly(butylene succinate) (PBS)-based biocomposites using high-shear homogenization (HSH). HSH transformed the switchgrass and poplar CBP residues (CBP-R) into fine, uniformly distributed particles and microfibers. The composites of PBS with homogenized switchgrass residues (H-CBP-R-SG) or homogenized poplar residues (H-CBP-R-P) at a 70/30 weight ratio exhibited improved processability and mechanical integrity, with the Young's modulus for the PBS/H-CBP-R-SG and PBS/H-CBP-R-P nearly doubling to 0.66 ± 0.07 GPa and 0.65 ± 0.04 GPa, respectively, compared to neat PBS (0.36 ± 0.02 GPa). Dynamic Mechanical Analysis (DMA) reveals a significant suppression of the tan δ peak magnitude, indicating that HSH-mediated physical activation facilitates stress transfer in composites typical of covalent chemical grafting systems. While the transition to a stiffness-dominated profile reduces ductility, the resulting composites exhibit the dimensional stability and resistance to thermal warping required for high-fidelity FDM 3D printing and injection molding. Beyond material performance, comprehensive techno-economic analysis (TEA) and life cycle assessment (LCA) confirmed that diverting CBP residues into composite products can improve the economic viability of the biorefinery without substantially increasing biorefinery global warming potential (GWP). At a 30 wt% blend ratio, incorporating residuals into PBS yielded a minimum selling price for the composite of $\$4.07$ per kg compared to the conventional bioplastic price of $\$5.00$ per kg. This approach aligns with circular bioeconomy principles by converting waste streams into value-added products. Furthermore, this innovative strategy addresses key challenges in bioplastic development, including cost, compatibility, and performance, while simultaneously advancing waste minimization strategies for sustainable manufacturing systems.

09 BIOMASS FUELS↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2022

Variational Quantum Circuits to Prepare Low Energy Symmetry States

We explore how to build quantum circuits that compute the lowest energy state corresponding to a given Hamiltonian within a symmetry subspace by explicitly encoding it into the circuit. We create an explicit unitary and a variationally trained unitary that maps any vector output by ansatz A(α → ) from a defined subspace to a vector in the symmetry space. The parameters are trained varitionally to minimize the energy, thus keeping the output within the labelled symmetry value. The method was tested for a spin XXZ Hamiltonian using rotation and reflection symmetry and H 2 Hamiltonian within S z = 0 subspace using S 2 symmetry. We have found the variationally trained unitary gives good results with very low depth circuits and can thus be used to prepare symmetry states within near term quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Single‐photon emitters in PECVD‐grown silicon nitride films: from material growth to photophysical properties

Abstract Silicon nitride (SiN) is a key material for quantum photonics due to its wide transparency window, high refractive index, low optical losses, and semiconductor foundry compatibility. We study the formation of single‐photon emitters in SiN films grown by plasma‐enhanced chemical vapor deposition (PECVD), exploring their photophysical properties and dependence on growth conditions. Emitters were observed across the entire range of nitrogen‐to‐silicon precursor ratios, from silicon‐rich to nitrogen‐rich conditions, enabled by the low background fluorescence. We demonstrate single‐photon emitters in SiN films with a higher refractive index (1.8–1.9) compared to our previous reports (∼1.7). Notably, nitrogen‐rich, thinner films yield particularly bright emitters with shorter emission lifetimes, likely due to more efficient annealing. Silicon‐rich SiN films exhibit red‐shifted emission, suggesting that composition may provide a mechanism for wavelength tuning. These findings establish the feasibility of emitters formation in foundry standard PECVD tools, advancing the scalability and lab‐to‐fab transition of SiN‐based quantum photonic technologies.

Materials Science↗
DOE OSTI2025

230Th/234U radiochronometry for uranium materials by alpha spectrometry for nuclear forensics analysis

We have developed an alpha spectrometry method for 230Th/234U radiochronometry to determine the model separation age for uranium materials. This method offers an alternative to the more commonly used, but significantly more resource intensive multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) while providing similar accuracy and precision. The development included radiochemical separation of uranium and thorium, calibration of the 232U tracer and the alpha spectrometry measurement. The method was validated by analyzing a certified reference material, CRM 125-A, which is a uranium oxide pellet assay, isotopic, and radiochronometric standard. The results were compared to those obtained by our routine MC-ICP-MS 230Th/234U radiochronometry analysis method to assess the performance parameters for alpha spectrometry compared to the state-of-the-art technique.

Macsik, Zsuzsanna [Los Alamos National Laboratory ↗
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

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗
DOE OSTI2024

Autonomous phototaxis of hydrogel swimmers

The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems.

Science & Technology - Other Topics↗
DOE OSTI2026

Stoichiometry dependent properties of cerium hydride: An active learning developed interatomic potential study

Cerium hydride has a variety of interesting properties, including a known lattice contraction and densification with increasing hydrogen content. However, precise stoichiometric control is not experimentally straightforward and ab initio approaches are not computationally feasible for many properties such as melting and low temperature diffusion. Therefore, we develop a machine-learned interatomic potential for cerium hydride that is valid for H to Ce ratios from 2.0 to 3.0. A query-by-committee active learning approach is used to develop the training set. Leveraging classical molecular dynamics simulations, we assess a range of properties and provide fundamental mechanisms for the trends with stoichiometry. Finally, a majority of the properties follow the trend of lattice contraction, being governed by the stronger lattice binding induced by adding octahedral atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Review of the Influence of Processing Parameters on ODS Steels Produced via Additive Manufacturing Techniques

Abstract This paper reviews current observations regarding processing conditions for oxide dispersion-strengthened steels consolidated through additive manufacturing techniques. Variations in ODS steels observed across process parameters include changes in grain size, grain texture, oxide size, density of oxides, porosity, melt pool characteristics, and mechanical properties. These properties were then compared across techniques to understand which techniques and processing conditions lead to the highest strength, ductility, and oxide density. Current literature suggests that a mix of grain types, in the form of either morphology or phase, can significantly increase the strength of printed ODS steels. Meanwhile, the most ductile samples, regardless of consolidation technique or matrix material, were made from feedstock with oxide additions located on the powder surface. Reported grain and oxide sizes were plotted against the ratio of laser power to scan speed, volumetric energy density, and normalized enthalpy. No strong correlation between these values and microstructural features was observed. The plots that were made suggest that a larger data set, more in-depth representative equations, and more defined material properties as a function of specific feedstock used are necessary to determine a value that can be correlated to the printed ODS steel microstructure.

deJong, Matthew↗
DOE OSTI2026

Insights into mixing of non-isothermal multi-polymer melts for complex plastics recycling

Catalytic recycling or upcycling of plastics is often limited not by catalyst performance, but by transport, arising from highly viscous, non-Newtonian polymer melts. In this work, we develop a reactor-scale framework that integrates rheological measurements, constitutive modeling, computational fluid dynamics (CFD), and experiments to quantify mixing, heat transfer, and dispersion in surrogate hydrocarbon melts representing mixed plastics systems. Temperature- and shear rate-dependent viscosity of low-density polyethylene (LDPE) and high-density polyethylene (HDPE) is measured to create two surrogate polymers (PLD and PHD) that capture the dominant shear-thinning flow behavior while neglecting strong elastic effects, enabling tractable simulation of non-isothermal, polymer-melt mixing using a Carreau-Arrhenius generalized Newtonian framework. Three-dimensional CFD simulations are employed to evaluate impeller performance in PLD using mixing time, cavern volume, thermal uniformity, and interfacial area for regimes in which viscoelastic effects are not dominant. We show that magnetic stir bars commonly used in lab-scale studies produce large thermal gradients (~60 °C) and poor mixing, even under idealized power delivery and polymer flow conditions. In contrast, close-clearance anchor impellers achieve near-isothermal operation, reduce mixing times by up to 5×, and provide >90% active circulation volume. We further demonstrate that, at low pseudo-Deborah number (De*), motor power requirements can be predicted directly from shear rate-dependent rheology using the Carreau-Arrhenius framework, enabling rational selection of operating conditions. Extension to surrogate immiscible multi-polymer systems based on PLD and PHD shows that interfacial area is highly sensitive to operating conditions and impeller design, with coaxial anchor-turbine configurations enhancing dispersion by up to 4 × .

Close-clearance impellers↗
DOE OSTI2024

Rapid Assessment of Sulfate Resistance in Mortar and Concrete

Extensive research has been conducted on the sulfate attack of concrete structures; however, the need to adopt the use of more sustainable materials is driving a need for a quicker test method to assess sulfate resistance. This work presents accelerated methods that can reduce the time required for assessing the sulfate resistance of mixtures by 70%. Class F fly ash has historically been used in concrete mixtures to improve sulfate resistance. However, environmental considerations and the evolving energy industry have decreased its availability, requiring the identification of economically viable and environmentally friendly alternatives to fly ash. Another challenge in addressing sulfate attack durability issues in concrete is that the standard sulfate attack test (ASTM C1012) is time-consuming and designed for only standard mortars (not concrete mixtures). To expedite the testing process, accelerated testing methods for both mortar and concrete mixtures were adopted from previous work to further the development of the accelerated tests and to assess the feasibility of testing the sulfate resistance of mortar and concrete mixtures rapidly. This study also established criteria for interpreting sulfate resistance for each of the test methods used in this work. A total of 14 mortar mixtures and four concrete mixtures using two types of Portland cement (Type I and Type I/II) and various supplementary cementitious materials (SCMs) were evaluated in this study. The accelerated testing methods significantly reduced the evaluation time from 12 months to 21 days for mortar mixtures and from 6 months to 56 days for concrete mixtures. The proposed interpretation method for mortar accelerated test results showed acceptable consistency with the ACI 318-19 interpretations for ASTM C1012 results. The interpretation methods proposed for the two concrete sulfate attack tests demonstrated excellent consistency with the ASTM C1012 results from mortar mixtures with the same cementitious materials combinations. Metakaolin was shown to improve sulfate resistance for both mortar and concrete mixtures, while silica fume and natural pozzolan had a limited impact. Using 15% metakaolin in mortar or concrete mixtures with Type I/II cement provided the best sulfate resistance.

Chemistry↗
DOE OSTI2026

Polynomial-time preparation of low-temperature Gibbs states for two-dimensional toric code

In this work, we propose a polynomial-time algorithm for preparing the Gibbs state of the two-dimensional toric code Hamiltonian at any temperature, starting from any initial state, significantly improving upon prior estimates that suggested exponential scaling with inverse temperature. We prove that fast mixing at low temperature for the two-dimensional toric code can be achieved by augmenting local jump operators with simple global jump operators, which enable efficient transitions between logical sectors. To establish tight lower bounds on the spectral gap, we introduce a new reduction method that eventually maps the problem to estimating the spectral gap of a perturbed graph Laplacian on a stair graph. Our proof also shows that the Lindblad dynamics with a digitally implemented low-temperature local Davies generator is able to efficiently drive the quantum state toward the ground state manifold.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deriving the Landauer Principle From the Quantum Shannon Entropy

We derive an expression to determine the equilibrium probability distribution of a quantum state in contact with a noisy thermal environment that formally separates contributions from quantum and classical forms of probabilistic uncertainty. A statistical mechanical interpretation of this probability distribution enables us to derive an expression for the minimum free energy costs for arbitrary (reversible or irreversible) quantum state changes. In conclusion, based on this derivation, we demonstrate that–in contrast to classical systems–the free energy required to erase or reset a qubit depends sensitively on both the fidelity of the target state and on the physical properties of the environment, such as the number of quantum bath states, due primarily to the entropic effects of system-bath entanglement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

SQUID Readout of a High-$Q$ Superconducting $LC$ Resonator

We demonstrate the readout of a superconducting $LC$ resonator, with $Q \approx 2 \times 10^{6}$ at approximately 250 kHz, using a dc SQUID followed by a SQUID series-array amplifier readout chain. We find that $Q$ depends on the SQUID flux-bias point, increasing near the shallow-slope point of the SQUID modulation curve and decreasing near the steep-slope point, consistent with the previously observed SQUID damping effects. From this variation, we infer the SQUID effective input impedance. We further infer the effective temperature of the resonator circuit from the resonance peak in the noise spectrum and show that it also depends on the SQUID flux-bias point, suggesting a possible contribution from SQUID back-action noise. This system provides a working prototype for future experiments based on lumped-element resonators with SQUID readout, in particular low-mass axion searches within the DMRadio program.

FOS: Physical sciences↗
DOE OSTI2024

Elastic Modulus Measurement at High Temperatures for Miniature Ceramic Samples Using Laser Micro-Machining and Thermal Mechanical Analyzer

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale at high temperatures. We used a picosecond laser to precisely cut microbeams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm and a length of ~1 cm. They were then tested in a thermal mechanical analyzer at room temperature, 500 °C, 800 °C, and 1100 °C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.

Chemistry↗