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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A periplasmic zinc capture protein enhances the resistance of Neisseria gonorrhoeae to nutritional immunity

During microbial infection, mammalian hosts reduce the availability of free metals such as zinc in a process known as nutritional immunity. Pathogens counteract nutritional immunity by expressing gene products that enhance growth in metal-limited conditions. One of the most transcriptionally induced genes in zinc-limited Neisseria gonorrhoeae , ngo1049, encodes a DUF4198 family protein we have named Zcp. This family of proteins is widely distributed in Gram-negative bacteria. Here, we provide the first structural, biochemical, and functional characterization of a DUF4198 protein. Zcp is a periplasmic, homodimeric substrate-binding protein (SBP), which binds one zinc ion per subunit with submicromolar affinity. We identified a zinc binding pocket in each subunit, composed of three histidine residues. Zcp enables maximal growth of N. gonorrhoeae in zinc-limited conditions but is dispensable for zinc uptake, in contrast to the cluster A-I SBP ZnuA, which is required for zinc import. The growth defect of zcp mutant N. gonorrhoeae is rescued by zinc supplementation. Zcp associates with proteins with roles in maintaining cell envelope integrity, and N. gonorrhoeae lacking zcp is more sensitive to envelope-targeting antimicrobials. Zcp enables infectivity of human epithelial cells and neutrophils by zinc-limited N. gonorrhoeae . We conclude that N. gonorrhoeae produces Zcp to buffer periplasmic zinc, which enables ZnuA to balance import of different metals and ensures the bioavailability of zinc for extracytoplasmic zinc-requiring proteins, as part of the coordinated response to host-imposed nutritional immunity.

Liyayi, Ian K. [Department of Microbiology, Immuno↗
DOE OSTI2025

Effects of carbon substitution on magnetic properties and magnetocaloric effects in Mn 65-x Ga 17 C 18+x compounds

This study involved the tuning of the magnetic, magnetocaloric, and room-temperature structural properties of Mn 65-x Ga 17 C 18+x (0 ≤ x ≤ 4) compounds prepared using a high-energy ball milling (HEBM) technique. This study indicates that the crystal structure of all the compounds can be described as an anti-perovskite cubic structure with the Pm-3m space group and the crystal cell volume decreases with increasing carbon concentration. The system shows a first-order structural phase transition at a temperature T=T M between two cubic phases having different magnetic structures. The phases are characterized by antiferromagnetic (AFM) and ferromagnetic (FM) -like behavior at low (T < T M ) and high (T M > T) temperature regions, respectively. A suppression of the AFM phase was observed with increasing C concentration. The temperature-induced first-order transitions (FOTs) were found to possess a small thermal hysteresis in the magnetization (~2-3 K) in an applied magnetic field of H = 50 kOe. Magnetic entropy changes estimated from isothermal magnetization curves indicate that the largest value of the magnetic entropy change of |ΔS M | = 2.1 J kg -1 K -1 for x = 4 with ΔH = 50 kOe, with a relative cooling power (RCP) of ~190 J kg -1 . Furthermore, high-energy ball milling (HEBM), a scalable technique, has been demonstrated as a viable method to synthesize magnetocaloric materials with substantial RCP values.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Generalization Equations for Machine Learners Based on Physical and Abstract Laws

The physical and abstract laws derived from the first principles have been recently exploited to customize and sharpen machine learning (ML) methods and also derive their generalization equations. These laws often encapsulate knowledge that complements datasets and ML models. We present a generic framework that uses these laws to provide ML codes that are transferable across multiple areas, including data transport infrastructures and thermal hydraulics analytics of nuclear reactors. By anchoring on datasets from these areas and the statistical generalization theory, we present a rigorous approach to co-develop ML solutions and the generalization equations that characterize them, by exploiting the structure and constraints from the laws. We present illustrative examples using practical problems from existing literature on the performance characterization of data transport infrastructures, and the sensor error and power level estimation in nuclear reactor systems using sensor measurements of primary and secondary coolant systems, respectively.

Rao, Nageswara↗
DOE OSTI2020

Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion

NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a “sample and select” method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls ( 1 H, 15 N, and 13 C'). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Print-and-Plate Architected Electrodes for Electrochemical Transformations Under Flow

Flow cell electrodes are typically composed of porous carbon materials, such as papers, felts, and cloths. However, their random architecture hinders the fundamental characterization of electrode structure-performance relationships during in situ operation of porous electrochemical flow systems. This work describes a “print-and-plate” method that combines direct ink writing of micro-periodic lattices with a two-step metal plating process that converts them into highly conductive (sheet resistance 40 mΩ sq -1 ) electrodes. Their operando performance is assessed in an anthraquinone disulfonic acid half-cell using widefield electrochemical fluorescence microscopy, where output current and fluorescence intensity are in excellent agreement. The pressure drop associated with flow through three electrode designs is determined via simulations from which the most efficient design is identified and manufactured via print-and-plate. Confocal fluorescence microscopy is then used to create a 3D map of the state of charge (SOC) inside this print-and-plate electrode. The experimental state of the charge map is in good agreement with computational predictions. The rapid design, simulation, and fabrication of print-and-plate electrodes enable fundamental investigations of how architected porosity affects electrochemical performance under flow.

3D-printing↗
DOE OSTI2023

The Synthescope: A Vision for Combining Synthesis with Atomic Fabrication

Here, the scanning transmission electron microscope, a workhorse instrument in materials characterization, is being transformed into an atomic-scale material-manipulation platform. With an eye on the trajectory of recent developments and the obstacles toward progress in this field, a vision for a path toward an expanded set of capabilities and applications is provided. The microscope is reconceptualized as an instrument for fabrication and synthesis with the capability to image and characterize atomic-scale structural formation as it occurs. Further development and refinement of this approach may have substantial impact on research in microelectronics, quantum information science, and catalysis, where precise control over atomic-scale structure and chemistry of a few “active sites” can have a dramatic impact on larger-scale functionality and where developing a better understanding of atomic-scale processes can help point the way to larger-scale synthesis approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improving Ionic Conformality Across Polymer Electrolyte|Electrode Interfaces

Maintaining uniform ionic transport at electrode|electrolyte interfaces, i.e., ionic conformality, remains challenging in polymer electrolyte (PE)-based solid-state batteries. Morphological conformality does not necessarily imply ionic conformality. In PEs, which typically consist of a mechanically supporting component and distinct ionically conductive components, the rearrangement or depletion of mobile ion-conductive domains at interfaces can disrupt ionic transport pathways. Such localized ionic depletion contributes to interfacial instability and capacity degradation in high-voltage lithium-metal batteries. Herein, an electrolyte design approach aimed at minimizing interfacial heterogeneities is demonstrated through compositional adjustments, characterized by spatially resolved structural and chemical X-ray techniques and NMR diffusometry to elucidate ion transport dynamics. This approach improves ionic conformality at electrode interfaces, enhancing cycling stability in Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC811) coin and pouch cells cycled at high voltages. These results contribute to understanding interfacial behaviors in multiphase PEs and inform strategies for improving stability across solid-state battery interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Novel Zwitterionic Polyurethane-in-Salt Electrolytes with High Ion Conductivity, Elasticity, and Adhesion for High-Performance Solid-State Lithium Metal Batteries

This study presents a novel polymer-in-salt (PIS) zwitterionic polyurethane-based solid polymer electrolyte (zPU-SPE) that offers high ionic conductivity, strong interaction with electrodes, and excellent mechanical and electrochemical stabilities, making it promising for high-performance all solid-state lithium batteries (ASSLBs). The zPU-SPE exhibits remarkable lithium-ion (Li+) conductivity (3.7 × 10⁻⁴ S cm−1 at 25 °C), enabled by exceptionally high salt loading of up to 90 wt.% (12.6 molar ratio of Li salt to polymer unit) without phase separation. It addresses the limitations of conventional SPEs by combining high ionic conductivity with a Li+ transference number of 0.44, achieved through the incorporation of zwitterionic groups that enhance ion dissociation and transport. The high surface energy (338.4 J m−2) and elasticity ensure excellent adhesion to Li anodes, reducing interfacial resistance and ensuring uniform Li+ flux. When tested in Li||zPU||LiFePO₄ and Li||zPU||S/C cells, the zPU-SPE demonstrated remarkable cycling stability, retaining 76% capacity after 2000 cycles with the LiFePO4 cathode, and achieving 84% capacity retention after 300 cycles with the S/C cathode. Molecular simulations and a range of experimental characterizations confirm the superior structural organization of the zPU matrix, contributing to its outstanding electrochemical performance. The findings strongly suggest that zPU-SPE is a promising candidate for next-generation ASSLBs.

Wang, Kun↗
DOE OSTI2023

The Role of Lewis Acid Sites in γ-Al 2 O 3 Oligomerization

Olefin oligomerization by γ-Al 2 O 3 has recently been reported, and it was suggested that Lewis acid sites are catalytic. The goal of this study is to determine the number of active sites per gram of alumina to confirm that Lewis acid sites are indeed catalytic. Addition of an inorganic Sr oxide base resulted in a linear decrease in the propylene oligomerization conversion at loadings up to 0.3 wt %; while, there is a >95 % loss in conversion above 1 wt % Sr. Additionally, there was a linear decrease in the intensity of the Lewis acid peaks of absorbed pyridine in the IR spectra with an increase in Sr loading, which correlates with the loss in propylene conversion, suggesting that Lewis acid sites are catalytic. Characterization of the Sr structure by XAS and STEM indicates that single Sr 2+ ions are bound to the γ-Al 2 O 3 surface and poison one catalytic site per Sr ion. The maximum loading needed to poison all catalytic sites, assuming uniform surface coverage, was ~0.4 wt % Sr, giving an acid site density of ~0.2 sites per nm2 of γ-Al 2 O 3 , or approximately 3 % of the alumina surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Identifying the mechanisms of cation inhibition of phenol oxidation by acid birnessite

Abstract Many phenolic compounds found as contaminants in natural waters are susceptible to oxidation by manganese oxides. However, there is often variability between oxidation rates reported in pristine matrices and studies using more environmentally relevant conditions. For example, the presence of cations generally results in slower phenolic oxidation rates. However, the underlying mechanism of cation interference is not well understood. In this study, cation co‐solutes inhibit the transformation of four target phenols (bisphenol A, estrone, p ‐cresol, and triclosan) by acid birnessite. Oxidation rates for these compounds by acid birnessite follow the same trend (Na + > K + > Mg 2+ > Ca 2+ ) when cations are present as co‐solutes. We further demonstrate that the same trend applies to these cations when they are absent from solution but pre‐exchanged with the mineral. We analyze valence state, surface area, crystallinity, and zeta potential to characterize changes in oxide structure. The findings of this study show that pre‐exchanged cations have a large effect on birnessite reactivity even in the absence of cation co‐solutes, indicating that the inhibition of phenolic compound oxidation is not due to competition for surface sites, as previously suggested. Instead, the reaction inhibition is attributed to changes in aggregation and the mineral microstructure.

Balgooyen, Sarah↗
DOE OSTI2023

Enhancing Crystallization in Hybrid Perovskite Solar Cells Using Thermally Conductive 2D Boron Nitride Nanosheet Additive

Controlling crystallization and grain growth is crucial for realizing highly efficient hybrid perovskite solar cells (PSCs). In this work, enhanced PSC photovoltaic performance and stability by accelerating perovskite crystallization and grain growth via 2D hexagonal boron nitride (hBN) nanosheet additives incorporated into the active perovskite layer are demonstrated. Specifically, in situ X-ray scattering and infrared thermal imaging during the perovskite annealing process revealed the highly thermally conductive hBN nanosheets promoted the phase conversion and grain growth in the perovskite layer by facilitating a more rapid and spatially uniform temperature rise within the perovskite film. Complementary structural, physicochemical, and electrical characterizations further showed that the hBN nanosheets formed a physical barrier at the perovskite grain boundaries and the interfaces with charge transport layers, passivating defects, and retarding ion migration. As a result, the power conversion efficiency of the PSC is improved from 17.4% to 19.8%, along with enhanced device stability, retaining ≈90% of the initial efficiency even after 500 h ambient air storage. Here, the results not only highlight 2D hBN as an effective additive for PSCs but also suggest enhanced thermal transport as one of the pathways for improved PSC performance by 2D material additives in general.

2D materials↗
DOE OSTI2022

Investigation of fracture in porous materials: a phase-field fracture study informed by ReaxFF

Microscopic features (e.g, pore shapes, sizes, and distribution) in porous material substantially affect the overall mechanical properties such as stiffness and strength. In turn, these material properties determine the macroscopic behaviors of fracture in the porous material. In certain cases, macroscopic properties can be derived from the porous skeleton and void ratio (i.e., porosity), but in many other cases, such derivation is a challenging task. This paper presents a numerical investigation of microporosity and micropore shapes effect on the macrofracture behavior in porous amorphous silica. For this study, we extend the recently-proposed combined molecular dynamic (MD) and phase-field (PF) fracture modeling approach by including different pore shapes in the atomistic domain. In the MD simulations, we adopt ReaxFF to evaluate the material properties, where four different micropore cases are considered. Based on the material properties derived from MD simulations, the macrofracture propagation of porous media is studied using hybrid PF simulation. In the characterization of the pore structure, the concept of pore ligament is proposed to relate the pore shape and the critical energy release rate. Two classical fracture problems were used to evaluate the effect of pore shape on the macrofracture behavior. The results of the case study show that although the micropore shapes change the macrofracture behaviors, these effects vary with the geometry and loading conditions of macroscopic boundary value problems. Furthermore, the case study also shows that the influence of micropore structure can be captured at the macroscopic level through the material properties derived from the MD simulations.

42 ENGINEERING↗
DOE OSTI2025

Influence of Initial fabric and water-wetting on particle fracture and force chain evolution in natural silica sand

Particle fracture has a significant influence on the engineering behavior of granular materials. However, the combined influence of the initial fabric and wetting on particle fracture and force chain evolution in granular materials, particularly in sands, remains insufficiently explored in the current literature. Here, in this paper, one-dimensional (1D) confined compression experiments were conducted on dry and wet specimens, and particle-level fracture was captured using three-dimensional (3D) in-situ Synchrotron Micro-Computed Tomography (SMT). A quantitative assessment of particle fracture revealed that wet specimens, which have disturbed fabric, exhibited a higher fracture percentage in comparison to dry specimens. Complementary 3D finite element (FE) simulations were performed using dry and wet (only solid fabric was considered and the influence of pore water is not considered) sand assemblies to assess interparticle contact forces and particle-scale stress distributions within the specimens. Force chain analysis was subsequently conducted, encompassing quantification of interparticle forces, characterization of force network structures, and monitoring the dynamic evolution of force chains under different strain levels. The results show that the specimens with disturbed fabric led to a more dynamic and less persistent force network, more fabric instability, and thus more reorganization of force chain structures. In addition, the frequent rearrangement of the force network in the presence of water (with reduced inter-particle contact friction) likely exacerbates localized stress concentrations, promoting failure in previously unengaged or weakly connected particles. The results reported in this paper offer a new insight into how the initial fabric and wetting cause different fracture behavior. The findings can also pave the way for more in-depth future investigations into the mechanics governing particle fracture in granular assemblies.

Finite element analysis↗
DOE OSTI2022

Mode I tensile fracture behavior of adhesively-bonded metal–metal, metal–CFRP, and CFRP–CFRP bi-material combinations analyzed by size effect method

Understanding the adhesive and interfacial fracture is important for developing and achieving better adhesive jointing in bi-materials, the location which becomes less vulnerable in engineered structure components. Still, to characterize the fracturing behavior of various adhesively-bonded materials, it was shown in this work that the Mode I fracture energies estimated from conventional methods (e.g., work-of-fracture, (modified) compliance calibration method, (modified) beam theory, etc.) can be strongly affected by adherent thickness, adhesive bond length, and material type. Consequently, this hindered the proper understanding of fracturing in adhesive jointing of bi-materials since the estimated fracture energies can exhibit unreasonable difference among various material combinations, thus leading to the confusion in the literature due to the unfair comparison on these non-objective results estimated by leveraging conventional methods on the specimens with different geometries. This work compared size effect method with conventional methods on the calculation of the Mode I fracture energies of metal-metal, metal-CFRP, and CFRP-CFRP material combinations via Double Cantilever Beam (DCB) tests. The results showed that the estimated fracture energies of various material combinations are not dependent on the specimen geometries. This aspect allowed the fair comparison particularly on the interfacial fracturing between metal/adhesive and CFRP/adhesive, and the difference was further explained and correlated with the damage morphology on the material surface after failure identified through three-dimensional profilometer.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Kernel methods for evolution of generalized parton distributions

Generalized parton distributions (GPDs) characterize the 3-dimensional structure of hadrons, combining information about their internal quark and gluon longitudinal momentum distributions and transverse position within the hadron. The dependence of GPDs on the factorization scale Q 2 allows one to connect hard exclusive processes involving GPDs at disparate energy and momentum scales, which is needed in global analyses of experimental data. Here, in this work, we explore how finite element methods can be used to construct fast and differentiable Q 2 evolution codes for GPDs in momentum space, which can be used in a machine learning framework. We show numerical benchmarks of the methods' accuracy, including a comparison to an existing evolution code from PARTONS/APFEL++, and provide a repository where the code can be accessed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Enhancing low-temperature sintering in the MgO-LiF system: Mechanistic insights

In the present article, we provide compelling evidence that minor (1 wt%) additions of micron and nanometre-sized LiF particles in MgO decompose leading to free Li diffusing into MgO surfaces enhancing vacancy production during direct current sintering. The addition of nanometre-sized LiF particles leads to a > 500 °C reduction in the sintering temperature and over 99 % theoretical density of final consolidated compacts. Correlating differential scanning calorimetry with in-situ x-ray diffraction, together with Schottky calculations, post sintering electron microscopy and laser induced breakdown spectroscopy, we uncover critical insights into this impressive reduction in sintering temperature. Our quantitative analysis reveals that MgO and LiF interact at low temperatures with the diffusion of Li into the surface of MgO particles due to the intrinsic structural disorder of the LiF and MgO crystallites. Nanometre-sized LiF particles were found to react the most at low temperatures due to their increased structural disorder. Our multimodal characterization points to a Li-promoted densification and sintering mechanism. This impressive reduction in sintering temperature can be harnessed to promote low-temperature fabrication of MgO-based composites for technological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structure and properties of the Sr 2 In 1-x Sn x SbO 6 double perovskite

A series of n -type oxide double perovskite semiconductors, Sr 2 In 1-x Sn x SbO 6 (0 ≤ x ≤ 0.3) has been synthesized; Sn 4+ partially substitutes for In 3+ . 121 Sb and 119 Sn Mössbauer spectroscopy are employed to investigate the B-site cation ordering because this issue cannot be resolved by conventional diffraction techniques alone. Rigid ordering between In 3+ /Sn 4+ and Sb 5+ sites is revealed by the spectroscopic method, and hence in combination with the structural parameters extracted from the XRD structural refinements, the crystallographic structure of this series of compounds is depicted. Furthermore, the temperature dependent magnetic susceptibilities, band gaps, and carrier type are characterized, and the calculated band structure is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Deformation behavior of annealed Cu64Zr36 metallic glass via molecular dynamics simulations

In the present work, we investigate the isothermal annealing process of Cu 64 Zr 36 metallic glass (MG) by means of molecular dynamics (MD) simulations, and characterize the compression properties under different temperatures and compressive rates. The pair distribution functions, the bond-orientational order, and the cluster-type index method are modeled and analyzed to characterize changes in the structure. Results of the modeling and analysis reveal that the MgZn 2 -type Laves, MgCu 2 -type Laves and five-fold local symmetry structures can be formed during the isothermal holding at 950 K. Study on the compression properties shows that at a fixed strain rate, the yield strength and yield drop all increase with decreasing temperature. At a fixed temperature, however, the increase of the strain rate leads to a noticeable increase in the yield strength at 600 K, but has little effect on yield strength at 10 K. Moreover, the modeling and analysis of the structure at a temperature of 10 K and strain-rate of 5 × 10 7 s -1 demonstrate that the order-disorder transformation initiates the shear band.

36 MATERIALS SCIENCE↗