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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Polybenzimidazole-derived carbon molecular sieve hollow fiber membranes with tailored oxygen selective transport

Polymer membrane carbonization is a promising strategy to obtain carbon molecular sieve (CMS) membrane materials with tailorable cavity size distributions for high gas selectivities beyond that attained from traditional polymer membrane materials. Despite their already demonstrated exceptional separation performance characteristics for several gas separation applications (e.g. CO 2 /CH 4 and H 2 /CO 2 ), further development of CMS membranes having high O 2 /N 2 perm-selectivity for energy-efficient high-purity O 2 production has proven challenging. Herein, we explore CMS hollow fiber membranes (HFMs) derived from highly rigid and tightly-packed polybenzimidazole (PBI) materials. Nearly defect-free PBI-derived CMS HFMs were fabricated and evaluated for O 2 /N 2 separation performance for the first time. The micro-structural and O 2 selective gas separation characteristics of PBI-CMS HFMs pyrolyzed at different pyrolysis conditions were intensively studied. With rigorous carbonization protocol optimization, we obtained highly O 2 permselective PBI-CMS HFMs having O 2 /N 2 selectivities approaching 14, enabling high purity O 2 production. The PBI-CMS HFM O 2 /N 2 separation performance dependence on operating conditions (e.g. temperature and feed pressure) are reported.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Symposium: Quantum Theory, Quantum Materials, Quantum Computing (Final Report, DE-SC0022551)

Quantum mechanics is fundamental to understanding, predicting, and controlling many physical processes in a vast range of scientific and technological areas. In molecules and materials, the quantum mechanics of Coulombic many-body systems determines far more than the ground state and bulk properties. Quantum mechanics governs magnetism, electron and spin transport, chemical reactions and catalysis, superconductivity, photosynthesis, etc. Each plays a vital role in modern society. As digital technologies push both temporal and length-scale limits, fundamental quantum principles become the current focus for a new class of technologies: quantum computing, quantum sensing, quantum encryption, etc. This oncoming quantum information sciences wave is manifest recently in frontier foci of all six Department of Energy Office of Science programs. The Sanibel Symposium offers a proven, influential platform for facilitating and advancing cross-fertilization among theoretical and computational chemists and physicists, computer scientists, and materials engineers. The Symposia have a long, successful record of driving progress on theory and computation of materials, nanostructures, and their molecular constituents. The Symposia thus are well-suited for advancing the quantum information science thrust in the Office of Basic Energy Sciences (BES). With that QIS thrust as the focus, we propose five sessions of the 61st Sanibel Symposium on the theme Quantum Theory, Quantum Materials, Quantum Computing. From a longer perspective, this thematic program for 2022 is the second year of a five year plan of program segments addressed at challenges in quantum information sciences and quantum materials. The rest of the Symposium program will be of considerable relevance, with, for example, sessions on quantum molecular and material dynamics, and new directions in coupled cluster theory. New ideas for methods and applications can be expected to emerge from the stimulus of the formal presentations and informal discussions. The proposed award is targeted at students, post-docs, and junior scientists. Conscious effort, characteristic of the Sanibel Symposia, to stimulate the participation of women and under-represented minorities will continue.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optically Induced Anisotropy in Time-Resolved Scattering: Imaging Molecular-Scale Structure and Dynamics in Disordered Media with Experiment and Theory

Time-resolved scattering experiments enable imaging of materials at the molecular scale with femtosecond time resolution. However, in disordered media they provide access to just one radial dimension thus limiting the study of orientational structure and dynamics. Here we introduce a rigorous and practical theoretical framework for predicting and interpreting experiments combining optically induced anisotropy and time-resolved scattering. Using impulsive nuclear Raman and ultrafast x-ray scattering experiments of chloroform and simulations, we demonstrate that this framework can accurately predict and elucidate both the spatial and temporal features of these experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Smart Scattering Scanning Near-Field Optical Microscopy

Scattering scanning near-field optical microscopy (s-SNOM) provides spectroscopic imaging from molecular to quantum materials with few nanometer deep subdiffraction limited spatial resolution. However, in its conventional implementation s-SNOM is slow to effectively acquire a series of spatio-spectral images, especially with large fields of view. This problem is further exacerbated for weak resonance contrast or when using light sources with limited spectral irradiance. Indeed, the generally limited signal-to-noise ratio prevents sampling a weak signal at the Nyquist sampling rate. Here, we demonstrate how acquisition time and sampling rate can be significantly reduced by using compressed sampling, matrix completion, and adaptive random sampling, while maintaining or even enhancing the physical or chemical image content. We use fully sampled real data sets of molecular, biological, and quantum materials as ground-truth physical data and show how deep under-sampling with a corresponding reduction of acquisition time by 1 order of magnitude or more retains the core s-SNOM image information. We demonstrate that a sampling rate of up to 6× smaller than the Nyquist criterion can be applied, which would provide a 30-fold reduction in the data required under typical experimental conditions. Furthermore, our smart s-SNOM approach is generally applicable and provides systematic full spatio-spectral s-SNOM imaging with a large field of view at high spectral resolution and reduced acquisition time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Establishing substitution rules of functional groups for high-capacity organic anode materials in Na-ion batteries

Tailoring molecular structures of organic electrode materials (OEMs) can enhance their performance in Na-ion batteries, however, the substitution rules and the consequent effect on the specific capacity and working potential remain elusive. Herein, by examining three sodium carboxylates with selective N substitution or extended conjugation structure, we exploited the correlation between structure and performance to establish substitution rules for high-capacity OEMs. Our results show that substitution position and types of functional groups are essential to create active centers for uptake/removal of Na+ and thermodynamically stabilize organic structures. Furthermore, rational host design and electrolytes modulation were performed to extend the cycle life to 500 cycles. A full cell based on the optimal 2,2’-bipyridine-4,4’-dicarboxylic acid disodium salt anode and the polyaniline cathode is demonstrated to confirm the feasibility of achieving all-organic batteries. Lastly, this work provides a valuable guideline for the design principle of high-capacity and stable OEMs for sustainable energy storage.

25 ENERGY STORAGE↗
DOE OSTI2025

Optimizing microfluidic flow cell geometry for in situ resonant soft X-ray characterization of molecular nanostructures

Liquid-phase resonant soft X-ray scattering (LP-RSoXS) is an emerging label-free technique to probe chemically resolved nanostructures of molecular or hybrid materials in liquid environments. Still, quantitative analysis is hindered by the pressure-induced deformation of thin silicon nitride (SiN) membranes used as windows in microfluidic flow cells, which attenuates the signal in nonlinear ways, making experimental optimization difficult. Here, in this work, we directly characterize this deformation under experimental conditions for a variety of cell configurations. We use this to develop a predictive model that combines transmission effects of SiN bowing, incident X-ray beam profiles, and material-dependent resonant scattering cross sections to simulate the effective scattering intensity at the detector across the carbon K-edge. Maps of the total signal across the flow cell window reveal that increasing the window width and polymer concentration shifts the anisotropic intensity distributions from the center toward the edges of the window. It was determined that an optimal SiN thickness of 50 nm, with a window aperture of 104 μm, maximizes the total signal for typical solute concentrations and energies across the carbon K-edge. Our results overturn the assumption that corner regions dominate the scattering signal, offering explicit design guidelines for maximizing LP-RSoXS signals and significantly advancing the quantitative application of this technique to the characterization of molecular and hybrid nanostructured materials in liquids.

Grabner, Devin [Washington State Univ., Pullman, W↗
DOE OSTI2024

Designing a Dynamic Material via Interlocking Kraft Lignin with Ultrahigh Molecular Weight Poly(ethylene oxide)

The environmental issues stemming from plastic waste and the excessive use of petroleum-based chemicals are both concerning and urgent. To effectively address this problem, we need to adopt a comprehensive approach involving developing more sustainable and renewable materials. These materials should be capable of demonstrating similar or even better performance than functional polymers synthesized from petroleum-based chemicals. Our research aims to develop more sustainable materials by leveraging the intrinsic characteristics of a natural polymer, lignin, a byproduct of the biorefinery industries. We utilized the three-dimensional branching structure of lignin as a material framework. We employed an approach to co-reactive melt processing of kraft lignin with aliphatic flexible chains of soft cross-linkers through the reaction of the cross-linker epoxy chain ends with lignin functional groups. Our study demonstrates that the interlocked structure formed from the co-blending of kraft lignin with ultrahigh molecular weight poly(ethylene oxide) and the cross-linking of lignin chains through a solvent-free process can manipulate the macromolecular interactions and relaxation. This manipulation results in materials that exhibit a wide range of thermomechanical properties and self-healing and shape memory effects, with drastically improved stiffness in a single material. We have explored the fundamental understanding of the macromolecular chain relaxation dynamics originating from the interlocking structure formation. In conclusion, this investigation utilized various techniques, including thermal, mechanical, rheology, and quasi-elastic neutron scattering.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Rapid Access to Diverse Multicomponent Hierarchical Nanostructures from Mixed–Graft Block Copolymers

Multicomponent nanostructured materials assembled from molecular building blocks received wide attention due to their precisely integrated multifunctionalities. However, discovery of these materials with desirable composition and morphology was limited by their low synthetic scalability and narrow structural tuning window with given building blocks. Here, we report a scalable and diversity-oriented synthetic approach to hierarchically structured nanomaterials based on a few readily accessible building blocks. Mixed-graft block copolymers containing sequence-defined side chains were prepared through ring-opening metathesis copolymerization of three or four types of macromonomers. Intramolecularly defined interfaces promoted the formation of ordered hierarchical structures with lattice sizes tunable across multiple length scales. Finally, the same set of macromonomers were arranged and combined in different ways, providing access to diverse morphologies in the resultant structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation of spin and magnetism in two dimensional materials with atomic-scale spatial resolution (Final Technical Report)

Spintronics is an approach to energy-efficient electronics beyond silicon CMOS that utilizes the electron’s spin degree of freedom for memory and logic. The record spin diffusion length in graphene has generated considerable interest in two dimensional (2D) materials (i.e. graphene and beyond) as a platform for spintronics. Magnetism in 2D van der Waals materials may offer additional opportunities for tunability via strain, external fields, and layer-dependent quantum effects. The inherently atomic-scale nature of exchange interactions and the inherently all-surface nature of 2D sheets motivate an integrated approach combining atomic-scale magnetic characterization, epitaxial growth, and nanodevice fabrication. The mission of the research is to develop and utilize atomic-scale imaging of spin and magnetism via spin-polarized scanning tunneling microscopy (STM) in conjunction with atom-by-atom materials growth via molecular beam epitaxy (MBE) and nanoscale device fabrication to explore new frontiers of spintronics and quantum science in 2D materials. The PIs are particularly motivated by understanding how the magnetic and spin-dependent properties at the atomic scale lead to interesting and potentially useful phenomena in spintronic devices at the macroscopic scale.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Active causal learning for decoding chemical complexities with targeted interventions

Abstract Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.

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

Metallic and ferromagnetic carbon allotrope discovered using molecular precursors

Although carbon materials are known for their versatile structures and properties, a crystalline phase of carbon being both metallic and ferromagnetic is yet to be found. Here, using an organic molecular precursor 3,3-dimethyl-1-butene ( C 6 H 12 ) and a comprehensive theoretical study, we have discovered a metastable crystalline carbon phase that is both metallic and ferromagnetic under ambient conditions. The new carbon structures, produced by stacking puckered layers of 4,6-membered rings, are found to exhibit exotic electronic, magnetic, and mechanical properties originating from a special s p 2 − s p 3 bonding topology. These findings open the prospect of realizing the metallic and ferromagnetic carbon allotrope in practice. Published by the American Physical Society 2025

Fang, Hong (ORCID:0000000209688687)↗
DOE OSTI2023

Tailoring Molecular-Scale Contact at Perovskite/Polymeric Hole Transporting Material Interface for Efficient Solar Cells

Perovskite solar cells (PSCs) have delivered more than 25% of power conversion efficiency (PCE) and incorporating polymers as hole transporting layers (HTLs) can further enhance the stability of devices towards the goal of commercialization. Among various polymeric hole transporting materials, poly(triaryl amine) (PTAA) is one of the promising HTL candidates with good stability; however, the hydrophobicity of PTAA causes problematic interfacial contact with perovskite, limiting the device performance. Using molecular side-chain engineering, we successfully constructed a uniform two-dimensional (2D) perovskite interlayer with conjugated ligands, between three-dimensional (3D) perovskites and PTAA. Further, employing conjugated ligands as cohesive elements, perovskite/PTAA interfacial adhesion was significantly improved. As a result, the thin and lateral extended 2D/3D heterostructure enabled the as-fabricated PTAA-based PSCs to achieve a PCE of 23.7%, improved from the 18% of reference devices. Owing to the increased ion migration energy barrier and conformal 2D coating, unencapsulated devices with the new ligands exhibited both superior thermal stability under 60°C heating and moisture stability in ambient conditions.

14 SOLAR ENERGY↗
DOE OSTI2020

Characterizing electronic and atomic structures for amorphous and molecular metal oxide catalysts at functional interfaces by combining soft X-ray spectroscopy and high-energy X-ray scattering

Amorphous thin film materials and heterogenized molecular catalysts supported on electrode and other functional interfaces are widely investigated as promising catalyst formats for applications in solar and electrochemical fuels catalysis. However the amorphous character of these catalysts and the complexity of the interfacial architectures that merge charge transport properties of electrode and semiconductor supports with discrete sites for multi-step catalysis poses challenges for probing mechanisms that activate and tune sites for catalysis. This minireview discusses advances in soft X-ray spectroscopy and high-energy X-ray scattering that provide opportunities to resolve interfacial electronic and atomic structures, respectively, that are linked to catalysis. This review discusses how these techniques can be partnered with advances in nanostructured interface synthesis for combined soft X-ray spectroscopy and high-energy X-ray scattering analyses of thin film and heterogenized molecular catalysts. Further, these combined approaches enable opportunities for the characterization of both electronic and atomic structures underlying fundamental catalytic function, and that can be applied under conditions relevant to device applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Side-chain ionization enables ultrafast intramolecular singlet fission in the azaquinodimethane skeleton

Singlet fission (SF) could significantly alleviate thermalization losses of high-energy photons, thus holding great potential for improving the power conversion efficiency of solar cells. Conventional SF materials require an intricate control of molecular packing motifs in the solid state to achieve efficient multiexciton generation. Small molecule intramolecular singlet fission (iSF) materials have emerged as promising alternatives and show great potential for practical device applications. However, the scope of such iSF materials remains rather limited, necessitating innovative molecular design strategies. Herein, we present how a side-chain ionization strategy leads to an iSF chromophore based on the azaquinodimethane (AQM) ring system. Systematic theoretical and spectroscopic analyses reveal that the direct attachment of electron-withdrawing ionic groups to the conjugated AQM core renders the originally fluorescent AQM nonemissive, leading to ionic AQM (iAQM) derivatives capable of ultrafast iSF to populate triplet-like species. Further fine-tuning of the iAQM skeleton imparts subtle intermolecular interactions that are indispensable for the efficient separation of triplet pairs following iSF in the aggregated state. Our findings offer unprecedented insights into molecular design and triplet exciton dynamics, laying the foundation for the discovery of rare molecular iSF materials.

Wu, Zixiang↗
DOE OSTI2020

Solvent–Solvent Correlations across Graphene: The Effect of Image Charges

Wetting experiments show pure graphene to be weakly hydrophilic, but its contact angle (CA) also reflects the character of the supporting material. Measurements and Molecular Dynamics simulations on suspended and supported graphene often reveal a CA reduction due to the presence of the supporting substrate. A similar reduction is consistently observed when graphene is wetted from both sides. The effect has been attributed to transparency to molecular interactions across the graphene sheet, however, the possibility of substrate-induced graphene polarization has also been considered. Computer simulations of CA on graphene have so far been determined by ignoring the material’s conducting properties. We improve the graphene model by incorporating its conductivity according to the Constant Applied Potential Molecular Dynamics. Using this method, we compare the wettabilities of suspended graphene and graphene supported by water by measuring the CA of cylindrical water drops on the sheets. The inclusion of graphene conductivity and concomitant polarization effects lead to a lower CA on suspended graphene but the CA reduction is significantly bigger when the sheets are also wetted from the opposite side. The stronger adhesion is accompanied by a profound change in the correlations among water molecules across the sheet. While partial charges on water molecules interacting across an insulator sheet attract charges of the opposite sign, apparent attraction among like charges is manifested across the conducting graphene. The change is associated with graphene polarization, as the image charges inside the conductor attract equally signed partial charges of water molecules on both sides of the sheet. Additionally, by using a non-polar liquid (diiodomethane), we affirm a detectable wetting translucency when liquid-liquid forces are dominated by dispersive interactions. Furthermore, our findings are important for predictive modeling toward a variety of applications including sensors, fuel cell membranes, water filtration, and graphene-based electrode materials in high-performance supercapacitors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Horizons of modern molecular dynamics simulation in digitalized solid freeform fabrication with advanced materials

Our ability to shape and finish a component by combined methods of fabrication including (but not limited to) subtractive, additive and/or no theoretical mass-loss/addition during the fabrication is now popularly known as solid free form fabrication. Fabrication of a telescope mirror is a typical example where grinding and polishing processes are first applied to shape the mirror and thereafter an optical coating is usually applied to enhance its optical performance. The area of nanomanufacturing cannot grow without a deep knowledge of the fundamentals of materials and consequently, the use of computer simulations is becoming ubiquitous. This article is intended to introduce the most recent advances in the computation benefit specific to the area of solid free form fabrication as these systems are traversing through the journey of digitalisation and Industry-4.0. Specifically, this article demonstrates that the application of the latest materials modelling approaches, based on techniques such as molecular dynamics, are enabling breakthroughs in applied precision manufacturing techniques.

36 MATERIALS SCIENCE↗