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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 343 records · Page 19

Iodine Removal from Carbonate-Containing Alkaline Liquids Using Strong Base Resins, Hybrid Resins, and Silver Precipitation

The ability of several material types to remove aqueous iodine from a mildly alkaline, carbonate-rich nuclear waste stream was evaluated: strong base anion exchange resins (SBAR), hybrid resins, Ag-containing materials and Bi-containing hybrid resins. A combination of batch testing and flow through column testing were used in the evaluation. In batch testing, hybrid resins CHM-20, SIR-110-CE and RTBI were shown to have high efficiency for the removal of both iodide and iodate simultaneously, while Ag-containing materials and SBAR demonstrated high capacity for iodide removal. One example of each material type (CHM-20, A532E and Ionex 400) were further evaluated for their sorption isotherms and column performance. The Langmuir isotherm, or a Langmuir-Freundlich hybrid isotherm, best described the sorption of iodide to the CHM-20 hybrid resin and Purolite A532E. The Freundlich isotherm best described the uptake of iodate to CHM-20 and A532E and for both iodide and iodate to the Ag-containing Ionex-400. In column testing the Purolite A532E had exceptional performance for overall iodide removal. With the capacity demonstrated the A532E resin would exceed Class C waste classification before breakthrough initiated, and column change outs in processing would be dictated by eventual waste classification, not breakthrough. The Ionex 400, a Ag-zeolite, was observed to degrade over time in the column in the mild alkaline conditions whereas the hybrid CHM-20 was limited in the single pass through design and would be best suited for applications where iodide and iodate are present and recirculation of the column effluent is feasible. Here this work highlights the feasibility of commercially available materials to separate radioiodine from liquid environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Si-Substituted Spirobifluorene Hole-Transporting Material for Perovskite Solar Cells

Hybrid organic-inorganic perovskite solar cells (PSCs) have shown promise for next-generation photovoltaics. Here, this study presents a simple approach for enhancing the performance and stability of PSCs by substituting the center carbon atom of the common hole transport material (HTM) Spiro-MeOTAD with a silicon atom. This modification, termed Si-Spiro, results in an increased hole mobility. A density functional theory simulation indicates that the enhanced hole mobility is due to the structural change of Si-Spiro. Electron beam-induced current microscopy measurements indicate improved charged extraction at the Si-Spiro/perovskite interface. A power conversion efficiency of 22.5% is achieved in Si-Spiro-based PSCs, outperforming standard Spiro-MeOTAD. Additionally, Si-Spiro-based PSCs demonstrate enhanced stability, maintaining over 90% of performance over 120 h of one-sun operation. Depth-profiling X-ray photoelectron spectroscopy revealed that Si-Spiro effectively blocks metal ion migration, which contributes to its enhanced stability. The findings suggest that Si-Spiro could be promising a HTM for high-performing, stable PSCs.

14 SOLAR ENERGY↗

Biopolymer-supramolecular polymer hybrids for photocatalytic hydrogen production

Solar generation of H 2 is a promising strategy for dense energy storage. Supramolecular polymers composed of chromophore amphiphile monomers containing perylene monoimide (PMI) have been reported as crystalline light-harvesting assemblies for aqueous H 2 -evolving catalysts. Gelation of these supramolecular polymers with multivalent ions creates hydrogels with high diffusivity but insufficient mechanical stability and catalyst retention for reusability. We report here on using sodium alginate (SA) biopolymer to both induce supramolecular polymerization of PMI and co-immobilize them with catalysts in a robust hydrogel with high diffusivity that can also be 3D-printed. Faster mass transfer was achieved by controlling the material macrostructure by reducing gel diameter and microstructure by reducing biopolymer loading. Optimized gels produce H 2 at rates rivaling solution-based PMI and generate H 2 for up to 6 days. The PMI assemblies in the SA matrix create a percolation network capable of bulk-electron transfer under illumination. These PMI–SA materials were then 3D-printed on conductive substrates to create 3D hydrogel photoelectrodes with optimized porosity. The design of these versatile hybrid materials was bioinspired by the soft matter environment of natural photosynthetic systems and opens the opportunity to carry out light-to-fuel conversion within soft matter with arbitrary shapes and particular local environments.

36 MATERIALS SCIENCE↗

Quantum effects on the dynamics and properties of soft materials

The quantum effects of nuclear and electronic motion play an important role in the structure, dynamics, and function of soft materials, yet they are difficult to capture with conventional classical simulations or static electronic–structure methods. In this work several complementary approaches for treating quantum effects in polymeric and soft–matter systems are demonstrated, with a focus being on the hydrogen-bonded networks, ion and charge transport, and photoactive chromophores. The proton transfer, tunneling, and isotope effects are captured within the reduced-dimensionality models by implementing grid-based nuclear quantum dynamics in terms of the discrete variable and Fourier bases. The nuclear quantum dynamics is extended to larger systems by employing the quantum trajectories and quantum–thermal bath schemes combined with on-the-fly electronic structure, enabling the description of high-dimensional polymeric environments at feasible cost. The dynamics in the electronic degrees of freedom, simulating the optical response in large chromophores such as chlorophylls, is performed using the real-time time-dependent density functional theory implemented in the real-space multigrid (RMG) code. These approaches are demonstrated on case studies of the proton and hydroxide transport in hydrated polymer membranes, charge transfer in conjugated polymers, and the optical spectra of chlorophyll chromophores relevant to polymerized chlorophyll materials and chlorophyll–polymer hybrids. The reviewed methods and applications highlight practical routes of including quantum effects in simulations of soft functional materials.

Garashchuk, Sophya [Univ. of South Carolina, Colum↗

Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

Cuillier, Paul↗

Hydrostatic pressure mapping of barium titanate phase transitions with quenched FeRh

We report a pressure study of the metamagnetic/ferroelectric hybrid heterostructure of a quenched FeRh thin film (25nm) grown on single crystal barium titanate (BTO). It has been previously reported that when the BTO undergoes a crystal transition a massive magnetization and coercivity change is triggered in the highly strain sensitive quenched FeRh thin film. Therefore quenched FeRh makes for an ideal probe for mapping a materials structural phase transitions. In this work we demonstrate this effect as a function of both temperature and hydrostatic pressure. As a result, we present the pressure dependence of the hybrid material which aligns identically with the BTO substrates pressure dependence reported in literature. The concept of combining a structural phase transitional (SPT) material with a magnetostrictive magnetic metal has been shown with vanadium oxides and our findings here prove that this methodology can be extended to strain sensitive metamagnetic materials systems in thin film, and possibly in bulk, heterostructures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗

Final Technical Report for "Cloud-based Low-Scaling Quantum Chemistry Simulations for Materials"

The objective of phase I was to develop the basic infrastructure for performing efficient hybrid DFT calculations on solid materials with a turnaround time amenable to the use in large-scale data-driven approaches. To fulfill the goal we have developed a novel algorithm that significantly reduces the cost of exchange matrix formation. The algorithm does so by making use of three ingredients (a) interpolative decomposition of the electron integrals (b) robust pseudospectral method and (c) occ-RI approach. Our published work demonstrates that the algorithm is orders of magnitude faster than any other hybrid-DFT method and is on the order of only 3-4 times slower than pure DFT. All steps of the algorithm developed during phase I can be accelerated to the point that, for large enough systems, the diagonalization of the Fock matrix will become the most expensive step. To treat such large systems we have created an interface to the ASCR-funded PEXSI library. The PEXSI method is used to compute the density matrix directly from the Fock matrix in a manner that preserves the sparsity of the local representation.

Shiozaki, Toru↗

Perspective: Magnon-magnon coupling in hybrid magnonics

The internal coupling of magnetic excitations (magnons) with themselves has created a new research sub-field in hybrid magnonics, i.e., magnon-magnon coupling, which focuses on materials discovery and engineering for probing and controlling magnons in a coherent manner. This is enabled by, one, the abundant mechanisms of introducing magnetic interactions, with examples of exchange coupling, dipolar coupling, Ruderman–Kittel–Kasuya–Yosida (RKKY) coupling, and Dzyaloshinskii–Moriya interaction (DMI) coupling, and two, the vast knowledge of how to control magnon band structure, including field and wavelength dependences of frequencies, for determining the degeneracy of magnon modes with different symmetries. In particular, we discuss how magnon-magnon coupling is implemented in various materials systems, with examples of magnetic bilayers, synthetic antiferromagnets, nanomagnetic arrays, layered van der Waals magnets, and (DMI spin-orbit torque materials) in magnetic multilayers. Here, we then introduce new concept of applications for these hybrid magnonic materials systems, with examples of frequency up/down conversion and magnon-exciton coupling, and discuss what properties are desired for achieving those applications.

Materials science↗

Material extrusion with integrated compression molding of NdFeB/SmFeN nylon bonded magnets using small- and large-scale pellet-based 3D-printers

High-density bonded rare-earth magnets are manufactured using pellet-fed additive manufacturing (AM)/material extrusion and an integrated additive manufacturing-compression molding (AM-CM) process. Neodymium iron boron – samarium iron nitride in polyamide 12 (NdFeB-SmFeN/PA12) of 93 % weight fraction (65 % volume fraction) are used for the study. The mechanical properties (tensile strength and modulus), magnetic properties (maximum energy density, coercivity, remanence) are reported. Manufacturing parameters such as layer height, barrel temperatures, screw speed and gantry feed rate are optimized to obtain the highest possible density of the magnets using a small-scale desktop material extrusion printer. Large scale integrated additive manufacturing-compression molding (AM-CM) is then utilized to increase the density of the magnets by reducing porosity defects common in the material extrusion process. The density of as-printed magnets was 5.2 g/cm 3 with a BH max value of 124.14 kJ/m 3 , tensile strength of 20 MPa and a modulus of 2 GPa. AM-CM increased the density of the compound by 5.5 % (5.49 g/cm 3 ). The reduction in porosity was confirmed using X-ray tomography (XCT). Improvement in mechanical strength of the material was also observed, with an increase in tensile strength of 25 % (25.09 MPa) and increase in tensile modulus of 275 % (5.49 GPa). Scanning electron microscopy showed increased particle-matrix adhesion with the integrated AM-CM process.

36 MATERIALS SCIENCE↗

A chemical perspective on the chiral induced spin selectivity effect

ABSTRACT This review discusses opportunities in chemistry that are enabled by the chiral induced spin selectivity (CISS) effect. First, the review begins with a brief overview of the seminal studies on CISS. Next, we discuss different chiral material systems whose properties can be tailored through chemical means, with a special emphasis on hybrid organic-inorganic layered materials that exhibit some of the largest spin filtering properties to date. Then, we discuss the promise of CISS for chemical reactions and enantioseparation before concluding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of Hybrid K-Edge Densitometry in Reprocessing Facilities

During reprocessing operations, accurately determining the elemental concentrations of uranium and plutonium is critical for nuclear security. Reprocessing facilities processes hundreds of tons of nuclear material annually, requiring accurate measurements to ensure effective nuclear material control and accountability. Hybrid K-edge densitometry (HKED) system combines K-edge absorption densitometry with x-ray fluorescence to measure actinide elemental concentrations with a low uncertainty. This system uses high-purity germanium gamma-ray detectors and advanced signal processing equipment to detect x-ray accurately. This document provides guidance on how to achieve effective performance from an HKED system for measuring uranium and plutonium concentrations in reprocessing facilities. It includes best practices for the setup and operation of an HKED system, while highlighting factors influencing uncertainties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Impact of solvent forces and broken symmetry on the assembly of designed proteins at a liquid-solid interface

The era of protein design has enabled the creation of hybrid protein-inorganic interfaces, leading to both surface-directed self-assembly of de novo protein architectures and protein-directed formation of inorganic materials. However, the resulting patterns of protein assembly are often unexpected, implying that essential interactions are not accounted for in current design platforms. Here, we use high-speed atomic force microscopy (AFM) analyzed through machine learning to follow the assembly of protein nanorods in aqueous electrolytes on two types of mica exhibiting disparate symmetry elements, which are imprinted on the overlying hydration structure. Using Monte Carlo simulations, we reproduce the observed phases and show that an observed smectic phase, previously thought to be unstable for non-interacting rods in two dimensions, emerges when crystal symmetry introduces a directional bias. The findings demonstrate the importance of incorporating solvent forces as modulated by the hydration structure inherent to interfacial systems when designing protein assemblies at liquid-crystal interfaces. Coupling physics-based simulations that can account for these factors to de novo protein design algorithms can lead to improved design platforms for bio-inspired, hybrid materials.

bioinspired materials↗

Hybrid Sorbents for 129 I Capture from Contaminated Groundwater

Radioiodine ( 129 I) poses a risk to the environment due to its long half-life, toxicity, and mobility. It is found at the U.S. Department of Energy Hanford Site due to legacy releases of nuclear wastes to the subsurface where 129 I is predominantly present as iodate (IO 3 – ). To date, a cost-effective and scalable cleanup technology for 129 I has not been identified, with hydraulic containment implemented as the remedial approach. Here, novel high-performing sorbents for 129 I remediation with the capacity to reduce 129 I concentrations to or below the US Environmental Protection Agency (EPA) drinking water standard and procedures to deploy them in an ex-situ pump and treat (P&T) system are introduced. Furthermore, this includes implementation of hybridized polyacrylonitrile (PAN) beads for ex-situ remediation of IO 3 – -contaminated groundwater for the first time. Iron (Fe) oxyhydroxide and bismuth (Bi) oxyhydroxide sorbents were deployed on silica substrates or encapsulated in porous PAN beads. In addition, Fe–, cerium (Ce)–, and Bi–oxyhydroxides were encapsulated with anion-exchange resins. The PAN–bismuth oxyhydroxide and PAN–ferrihydrite composites along with Fe- and Ce-based hybrid anion-exchange resins performed well in batch sorption experiments with distribution coefficients for IO 3 – of >1000 mL/g and rapid removal kinetics. Of the tested materials, the Ce-based hybrid anion-exchange resin was the most efficient for removal of IO 3 – from Hanford groundwater in a column system, with 50% breakthrough occurring at 324 pore volumes. The functional amine groups on the parent resin and amount of active sorbent in the resin can be customized to improve the iodine loading capacity. These results highlight the potential for IO 3 – remediation by hybrid sorbents and represent a benchmark for the implementation of commercially available materials to meet EPA standards for cleanup of 129 I in a large-scale P&T system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗

“Breathing” organic cation to stabilize multiple structures in low-dimensional Ge-, Sn-, and Pb-based hybrid iodide perovskites

Low-dimensional hybrid inorganic–organic perovskites are excellent candidates for stable optoelectronic devices. The dimensionality of these perovskites depends largely on the organic and inorganic compositions, as well as the synthetic conditions. We report five new hybrid iodides, (ETU) 4 Ge 5 I 18 , (ETU)GeI 4 , (ETU)SnI 4 , (ETU)PbI 4 , and (ETU) 3 Pb 2 I 10 using only one type of organic cation, namely, S-(2-aminoethyl)isothiouronium (ETU). (ETU)GeI 4 and (ETU)SnI 4 belong to the (110)-oriented structure-type with “3 × 3” sawtooth corrugated layers and crystallize in a structure with the orthorhombic space group Pbca. (ETU) 4 Ge 5 I 18 crystallizes in a structure with the triclinic space group P$\bar{1}$with combining macron], featuring a 2D layered structure with combinations of corner, edge, and face-sharing [GeI 6 ] octahedra. For the Pb-based series, (ETU)PbI 4 has the conventional (100) – oriented 2D type whereas (ETU) 3 Pb 2 I 10 has a unique 0D structure. Remarkably, the unstable 2D orange-phase (ETU)PbI 4 transforms to a stable 0D yellow phase (ETU) 3 Pb 2 I 10 , accompanied by the reduction of the C–S–C angle of the organic cation ETU. The optical band gaps are largely regulated by the diverse types of structure and are in the range of 1.8 eV to 2.8 eV. (ETU)SnI 4 is the only material showing notable photoluminescence at room-temperature. Our work showcases the flexibility of the organic cation in determining the structural dimensionality and provides a new strategy in generating new hybrid materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymer-Grafted Nanoparticles as All-in-One Nanoplatforms

Polymer-grafted nanoparticles (PGNPs) represent a versatile class of hybrid nanomaterials, in which nanoparticle cores and tethered polymer coronas are integrated into structurally programmable building blocks. Rapid advances in nanoparticle surface functionalization and surface-initiated polymerization have enabled increasingly precise control over the nanoparticle core composition and brush architecture, greatly expanding the accessible structural and functional landscape of PGNPs. This review summarizes recent progress in the modular design and structural regulation of PGNPs, with an emphasis on nanoparticle platforms and associated surface functionalization strategies, polymer brush synthesis and architectural control, and the structure−property relationships that govern PGNP behavior. Emerging applications are further highlighted, including additive manufacturing, self-healing materials, membrane-based gas separations, and battery-related systems, where PGNPs provide unique opportunities to couple nanoscale interfacial design with macroscopic performance. Finally, future opportunities are discussed for extending PGNP concepts to increasingly complex, multifunctional, and application-oriented hybrid materials.

functional nanocomposites↗

Inverse design of two-dimensional graphene/h-BN hybrids by a regressional and conditional GAN

Design of materials with desired properties is currently laborious and heavily relies on intuition of researchers through a trial-and-error process. To tackle this challenge, in this work we propose a novel regressional and conditional generative adversarial network (RCGAN) for inverse design of representative two-dimensional materials, the graphene and boron-nitride (BN) hybrids. RCGAN incorporates a supervised regressor network, thus overcoming the common technical barrier in the traditional unsupervised GANs, which cannot generate data when fed with continuous and quantitative labels. RCGAN can autonomously generate graphene/BN hybrids given any target bandgap values. These structures are distinguished from the ones used for training and exhibit high diversity for a given bandgap. Moreover, they exhibit high fidelity, yielding bandgaps within ~10% MAE F of the desired bandgaps as validated by density functional theory (DFT) calculations. Analysis by the principle component analysis (PCA) and modified locally linear embedding (MLLE) reveals that the generator has successfully generated structures following the statistical distribution of the real structures. It implies the possibility of the RCGAN in recognizing physical rules hidden in the high-dimensional data. The novel strategy for designing regressional GAN architecture together with the successful application to inverse design of materials would inspire further exploration in research fields beyond materials.

36 MATERIALS SCIENCE↗