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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

ECAR-7428 Rev 0 MARVEL Upper Confinement Structure Airflow Analysis

This ECAR documents airflow values calculated for the Upper Confinement Structure (UCS) design, which is a subsystem of the Microreactor Applications Research Validation and Evaluation (MARVEL) reactor. These airflow values are calculated based on current design parameters and heat removal requirements and are needed to verify the UCS can adequately maintain a target design temperature.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Kinetics of short-range order formation in GeSn alloy: MBE vs CVD

Recently, short-range order (SRO) has attracted significant attention, challenging the conventional view of the atomic positions in alloys being random. Furthermore, the presence of SRO has been predicted to have profound effects on the electronic and topological properties of group-IV alloys, offering a different direction in designing group-IV materials for photoelectronic and quantum devices. However, due to the limited understanding of the formation mechanisms, developing effective methods to manipulate SRO in epitaxy is still challenging. To address this, we propose a mechanism for the GeSn alloy, revealing that surface diffusion plays a key role in SRO formation. Building on this mechanism, we show that the distinct surface conditions in MBE and CVD lead to the formation of SRO with enhanced Sn–Sn pairing in MBE-grown samples, while CVD-grown samples remain random alloys. Furthermore, our findings provide an initial understanding of the kinetic process of SRO formation, providing guidance for the design of experiments to manipulate SRO.

Alloys↗

Spatiotemporal control of laser intensity using differentiable programming

Optical techniques for spatiotemporal control can produce laser pulses with custom amplitude, phase, or polarization structure. In nonlinear optics and plasma physics, the use of structured pulses typically follows a forward design approach, in which the efficacy of a known structure is analyzed for a particular application. Inverse approaches, in contrast, enable the discovery of new structures with the potential for superior performance. Here, an implementation of the unidirectional pulse propagation equation that supports automatic differentiation is combined with gradient-based optimization to design structured pulses with features that are advantageous for a range of nonlinear optical and plasma-based applications: (1) a longitudinally uniform intensity over an extended region, (2) a superluminal intensity peak that travels many Rayleigh ranges with constant duration, spot size, and amplitude, and (3) a laser pulse that ionizes a gas to form a uniform column of plasma. In the final case, optimizing the full spatiotemporal structure improves the performance by a factor of 15 compared to optimizing only spatial or only temporal structure, highlighting the advantage of spatiotemporal control.

automatic differentiation↗

Ultrapotent influenza hemagglutinin fusion inhibitors developed through SuFEx-enabled high-throughput medicinal chemistry

Seasonal and pandemic-associated influenza strains cause highly contagious viral respiratory infections that can lead to severe illness and excess mortality. Here, we report on the optimization of our small-molecule inhibitor F0045(S) targeting the influenza hemagglutinin (HA) stem with our Sulfur-Fluoride Exchange (SuFEx) click chemistry–based high-throughput medicinal chemistry (HTMC) strategy. A combination of SuFEx- and amide-based lead molecule diversification and structure-guided design led to identification and validation of ultrapotent influenza fusion inhibitors with subnanomolar EC 50 cellular antiviral activity against several influenza A group 1 strains. X-ray structures of six of these compounds with HA indicate that the appended moieties occupy additional pockets on the HA surface and increase the binding interaction, where the accumulation of several polar interactions also contributes to the improved affinity. The compounds here represent the most potent HA small-molecule inhibitors to date. Our divergent HTMC platform is therefore a powerful, rapid, and cost-effective approach to develop bioactive chemical probes and drug-like candidates against viral targets.

Science & Technology - Other Topics↗

Microstructure‐Informed Analysis Framework for Lattice Structures: Guiding Topology‐Material Synergy in Titanium Alloys

In this work we discuss a microstructure‐informed analysis framework for lattice structures that maps the material's microstructural response to guide topology selection and mechanical performance optimization. By coupling geometrical topology with intrinsic material behavior, we demonstrate how anisotropic microstructural response can inform the design of optimized lattice structures. To illustrate this concept, we focus on two distinct classes of titanium alloys: Ti5553 (Ti‐5Al‐5Mo‐5V‐3Cr wt%), which exhibits a predominantly ‐phase microstructure, and Ti64 (Ti‐6Al‐4V wt%), which features a dual‐phase structure. These alloys exhibit markedly different mechanical responses under multiaxial loading in “fully dense” solid form. The strut‐level stress analysis of these alloys reveals how specific microstructural characteristics can guide the selection of appropriate lattice topologies. Two representative lattice configurations, one stretching‐dominated and one bending‐dominated, are evaluated under identical loading conditions to explore how microstructure‐driven design can lead to topology choices that are better suited to accommodate shear or other critical local stress states, thereby enhancing mechanical performance. A strut‐level mechanics‐based analysis is performed to evaluate shear stress distribution and highlight the role of topology‐microstructure synergy and compatibility in determining overall lattice behavior. The findings emphasize the importance of designing structures that are both load‐aware and microstructure‐responsive, enabling more effective material utilization in advanced engineering applications.

36 MATERIALS SCIENCE↗

Magneto-Mechanical Optimization of Cross-Sections for $ \text{cos}(\theta)$Accelerator Magnets

The cross-section design of cos (θ) superconducting magnets is historically developed in a two-step process: initially, the coil geometry is defined on the basis of magnetic optimizations; then, the structure is designed around the coil. The first step searches for the best coil cross-section maximizing the magnetic field, margin, field quality and conductor efficiency. The latter step aims at limiting the coil stresses and deformations. However, the coil design, defined with the initial magnetic optimization, can influence the mechanical behaviour of the magnet, altering, for example, the peak stress during operation. As the critical current is a function of the applied strain, the mechanical implications of the coil cross-section design can limit the achievable performance. In this paper we propose an integrated optimization process that targets the peak stress on the conductor in addition to the magnetic objectives. Here the results are presented for a sample high-field Nb 3 Sn dipole: a 4-layer design aiming at ultimate conductor performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications. First, a TO problem often involves a large number of design variables to guarantee sufficient expressive power. Second, many TO problems require a large number of expensive physical model simulations, and those simulations cannot be parallelized. To address these issues, we propose a general scalable deep-learning (DL) based TO framework, referred to as SDL-TO, which utilizes parallel schemes in high performance computing (HPC) to accelerate the TO process for designing additively manufactured (AM) materials. Unlike the existing studies of DL for TO, our framework accelerates TO by learning the iterative history data and simultaneously training on the mapping between the given design and its gradient. The surrogate gradient is learned by utilizing parallel computing on multiple CPUs incorporated with a distributed DL training on multiple GPUs. The learned TO gradient enables a fast online update scheme instead of an expensive update based on the physical simulator or solver. Using a local sampling strategy, we achieve to reduce the intrinsic high dimensionality of the design space and improve the training accuracy and the scalability of the SDL-TO framework. The method is demonstrated by benchmark examples and AM materials design for heat conduction. The proposed SDL-TO framework shows competitive performance compared to the baseline methods but significantly reduces the computational cost by a speed up of around 8.6x over the standard TO implementation.

Bi, Sirui↗

Near-physiological-temperature serial crystallography reveals conformations of SARS-CoV-2 main protease active site for improved drug repurposing

The COVID-19 pandemic has resulted in 198 million reported infections and more than 4 million deaths as of July 2021 (covid19.who.int). Research to identify effective therapies for COVID-19 includes: (1) designing a vaccine as future protection; (2) de novo drug discovery; and (3) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determine two apo structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease at ambient temperature by serial femtosecond X-ray crystallography. We employ detailed molecular simulations of selected known main protease inhibitors with the structures and compare binding modes and energies. The combined structural and molecular modeling studies not only reveal the dynamics of small molecules targeting the main protease but also provide invaluable opportunities for drug repurposing and structure-based drug design strategies against SARS-CoV-2.

59 BASIC BIOLOGICAL SCIENCES↗

JOBRUNNER

SF-23-071 Jobrunner is a command line tool to manage and deploy computing jobs, organize complex workloads, and enforce a directory based hierarchy to enable reuse of files and bash scripts within a project. Organization details of a directory tree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or setting up a job. It is a flexible tool that allows users to design 16 their own directory structure, perserve their design, and maintain 17 consistency with increase in complexity of the project.

DHRUV, AKASH VIJAYKUMAR↗

Metals and Quantum Materials with Spin-orbit Interactions by Quantum Monte Carlo methods

The key goals of this project were as follows: 1) Analysis and benchmarks of electron correlation effects recovered in the fixed-node approximation that is inherent to quantum Monte Carlo (QMC) method as applied to metallic states; 2) development of new algorithms for electron spin-degrees of freedom to be treated as explicit quantum variables; 3) designing electronic structure QMC algorithm for efficient evaluation of spin-orbit effects in systems with heavy atoms; 4) adapting the algorithm to complex wave functions and developing corresponding fixed-phase approximation; 5) design and testing of algorithm for valence-only non-local spin-orbit operators; 6) analysis of fixed-node vs fixed-phase errors and their comparisons. The key accomplishments: i) We carried out a systematic study of Li systems by the fixed-node diffusion Monte Carlo method. This involved Li atom, molecule, cluster and solid calculated by the full range of QMC methods including fixed-node QMC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrated linker-regulation and ring-fusion engineering for efficient additive-free non-fullerene organic solar cells

The rational molecular design and structural modification of quasi-two-dimensional fused perylene diimide (quasi-2D FPDI) acceptors have received growing attention for application in non-fullerene organic solar cells (NF-OSCs). Herein, we designed and synthesized two pairs of FPDI acceptors, one in the form of FPDI–π-bridge–FPDI with the π-bridge being either an axisymmetric thiophene (T) or a centrosymmetric thienothiophene (TT) unit, and the other being the corresponding ring-fusion counterpart. Additionally, four small molecule acceptors, namely T-FPDI, TT-FPDI, FT-FPDI and FTT-FPDI, were paired with a common PTB7-Th polymeric electron donor as active materials for a comparative study of the effects of linkers and ring fusion on their photovoltaic performances. The T-FPDI-based NF-OSC exhibited a decent power conversion efficiency (PCE) of 5.50%, while a higher PCE of 7.17% with a simultaneous enhancement in the open circuit voltage ( V oc ), the short-circuit current density ( J sc ) and the fill factor (FF) was achieved for the TT-FPDI-based solar cells. The solar cells based on the ring-fused FT-FPDI and FTT-FPDI acceptors displayed PCEs of 6.75% and 7.66%, respectively, both higher than those of the corresponding non-fused counterparts. Notably, the trade-off between the J sc and V oc , commonly observed in fullerene OSCs, is alleviated in these systems. It is also worth noting that the NF-OSCs based on these FPDI acceptors do not need any solvent additives. Overall, this successful molecular engineering based on novel quasi-2D FPDI building blocks may inspire the development of emergent electron acceptors for high performance additive-free NF-OSCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energetic robustness to large scale structural fluctuations in a photosynthetic supercomplex

Abstract Photosynthetic organisms transport and convert solar energy with near-unity quantum efficiency using large protein supercomplexes held in flexible membranes. The individual proteins position chlorophylls to tight tolerances considered critical for fast and efficient energy transfer. The variability in protein organization within the supercomplexes, and how efficiency is maintained despite variability, had been unresolved. Here, we report on structural heterogeneity in the 2-MDa cyanobacterial PSI-IsiA photosynthetic supercomplex observed using Cryo-EM, revealing large-scale variances in the positions of IsiA relative to PSI. Single-molecule measurements found efficient IsiA-to-PSI energy transfer across all conformations, along with signatures of transiently decoupled IsiA. Structure based calculations showed that rapid IsiA-to-PSI energy transfer is always maintained, and even increases by three-fold in rare conformations via IsiA-specific chls. We postulate that antennae design mitigates structural fluctuations, providing a mechanism for robust energy transfer in the flexible membrane.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of laser melt schedule on the microstructure of additively manufactured IN718 Superalloy

Laser powder bed fusion (L-PBF) has enabled the fabrication of geometrically complex metallic structures and components that are challenging to producing using conventional manufacturing approaches. The site-specific and far from equilibrium thermal conditions of L-PBF offer the potential to facilitate multi-length scale design of structure and properties across the atomic-through macro-levels. However, L-PBF systems face scalability challenges due to throughput constraints. Laser rotary powder bed fusion (L-RPBF) systems are being investigated as a solution to enhance the deposition rates compared to conventional L-PBF. Rotary systems also offer additional flexibility for controlling the time structure of melting through laser interleaving on alternating layers. Here, in this study, IN718 test samples were printed using single-laser or interleaved dual-laser configuration in a L-RPBF system to investigates the effect of process settings and melt-interleaving on as-fabricated microstructure. The microstructural evolution, such as grain size and crystallographic texture, was assessed by determining variations in the melt-pool shapes. Laser interleaving leads to a reduction in average grain size compared to single laser by ∼ 40 % at high power (400 W) and by ∼36 % at medium power (370 W). Results presented here identify key challenge for obtaining uniform microstructures and barriers for the broader adoption of high-deposition rate L-RPBF.

Dual-laser↗

Low-dimensional metal–organic frameworks: a pathway to design, explore and tune magnetic structures

Here, the magnetic structure adopted by a material relies on symmetry, the hierarchy of exchange interactions between magnetic ions and local anisotropy. A direct pathway to control the magnetic interactions is to enforce dimensionality within the material, from zero-dimensional isolated magnetic ions, one-dimensional (1D) spin-chains, two-dimensional (2D) layers to three-dimensional (3D) order. Being able to design a material with a specific dimensionality for the phenomena of interest is non-trivial. While many advances have been made in the area of inorganic magnetic materials, organic compounds offer distinct and potentially more fertile ground for material design. In particular magnetic metal–organic frameworks (mMOFs) combine magnetism with non-magnetic property functionality on the organic linkers within the structural framework, which can further be tuned with mild perturbations of pressure and field to induce phase transitions. Here, it is examined how neutron scattering measurements on mMOFs can be used to directly determine the magnetic structure when the magnetic ions are in a 2D layered environment within the wider 3D crystalline framework. The hydrated formate, in deuterated form, Co(DCOO) 2 ·2D 2 O, which was one of the first magnetic MOFs to be investigated with neutron diffraction, is reinvestigated as an exemplar case.

magnetism↗

Edgewise Structural Damping of a 2.8-MW Land-Based Wind Turbine Rotor Blade

Modern wind turbines push the predictive capabilities of state-of-the-art aero-servo-elastic tools. The existing limitations hide across the numerical tool chain and can result in serious issues, such as missing aeroelastic instabilities during the design phase. Structural damping is an input that is usually hard to estimate, but also has a major impact on the turbine behavior. In this paper, we discuss an experiment that aims to accurately quantify the structural damping characterizing the edgewise modes of modern wind turbine blades. The experiment is carried out on a 2.8-MW land-based wind turbine and features a fast yaw actuation that induces an edgewise motion on one of the three blades. The Covariant-subspace system identification (Cov-SSI) method is then used to post-process the blade root moment to estimate the short-term edgewise structural damping. Despite limitations of the Cov-SSI method, which consistently under-predicts the absolute values of damping, we observe that structural damping decreases across the first three blade edgewise modes, which is different from the stiffness-proportional damping model that assumes that structural damping increases with the modes. This paper argues that a stiffness-proportional damping model, which is implemented in most aeroelastic tools, is therefore not conservative and might hide aeroelastic instabilities that can instead appear in the field.

17 WIND ENERGY↗

High-entropy halide perovskite single crystals stabilized by mild chemistry

High entropy materials are excellent candidates for a range of functional materials but traditionally require high-temperature synthetic procedures over 1000°C and complex processing techniques such as hot rolling to form. One route to address the extreme synthetic requirements for high entropy materials should involve designing crystal structures with ionic bonding networks and low cohesive energies. Here, we develop room-temperature (20°C) and low temperature (80°C) solution synthesis procedures for a new class of metal-halide perovskite high entropy semiconductor (HES) single crystals. Due to the soft, ionic lattice nature of the class of metal-halide perovskites, these HES single crystals are designed on the cubic Cs 2 MCl 6 (M = Zr 4+ , Sn 4+ , Te 4+ , Hf 4+ , Re 4+ , Os 4+ , Ir 4+ , or Pt 4+ ) vacancy-ordered double perovskite structure from the self-assembly of stabilized complexes in multielement inks, namely free Cs + cations and five or six different isolated [MCl6] 2- anionic octahedral molecules well-mixed in strong hydrochloric acid. The resulting single-phase single crystals span two HES families of five- and six-elements occupying the M-site as a random alloy in near-equimolar ratios, with the overall Cs 2 MCl 6 crystal structure and stoichiometry maintained. In conclusion, the incorporation of various [MCl 6 ] 2- octahedral molecular orbitals disordered across the high entropy five- and six-element Cs 2 MCl 6 single crystals produces complex vibrational and electronic structures with energy transfer interactions between the confined exciton states of the five or six different isolated octahedral molecules.

36 MATERIALS SCIENCE↗

Three-dimensional printing of wood

Natural wood has served as a foundational material for buildings, furniture, and architectural structures for millennia, typically shaped through subtractive manufacturing techniques. However, this process often generates substantial wood waste, leading to material inefficiency and increased production costs. A potential opportunity arises if complex wood structures can be created through additive processes. Here, we demonstrate an additive-free, water-based ink made of lignin and cellulose, the primary building blocks of natural wood, that can be used to three-dimensional (3D) print architecturally designed wood structures via direct ink writing. The resulting printed structures, after heat treatment, closely resemble the visual, textural, olfactory, and macro-anisotropic properties, including mechanical properties, of natural wood. Our results pave the way for 3D-printed wooden construction with a sustainable pathway to upcycle/recycle natural wood.

36 MATERIALS SCIENCE↗

Enhancing the solubility of SARS-CoV-2 inhibitors to increase future prospects for clinical development

SARS-CoV-2 poses an ongoing threat to human health as variants continue to emerge. Several effective vaccines are available, but a diminishing number of Americans receive the updated vaccines (only 22% received the 2023 update). Public hesitancy towards vaccines and common occurrence of “breakthrough” infections (i.e., infections of vaccinated individuals) highlight the need for alternative methods to reduce viral transmission. SARS-CoV-2 enters cells by fusing its envelope with the target cell membrane in a process mediated by the viral spike protein, S. The S protein operates via a Class I fusion mechanism in which fusion between the viral envelope and host cell membrane is mediated by structural rearrangements of the S trimer. We previously reported lipopeptides derived from the C-terminal heptad repeat (HRC) domain of SARS-CoV-2 S that potently inhibit fusion by SARS-CoV-2, both in vitro and in vivo. These lipopeptides bear an attached cholesterol unit to anchor them in the membrane. Here, to improve prospects for experimental development and future clinical utility, we employed structure-guided design to incorporate charged residues at specific sites in the peptide to enhance aqueous solubility. This effort resulted in two new, potent lipopeptide inhibitors.

36 MATERIALS SCIENCE↗