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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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An underutilized, but highly advantageous, method of growing functional-single-crystals, the gel-growth technique, is highlighted. Large nonlinear optical crystals, BCHT, were grown and their dehydration phase-transformation to β-BTC were studied.
The design, synthesis, and fabrication of functional nanomaterials with specific properties remain a long-standing goal for many scientific fields. The self-assembly of sequence-defined biomimetic synthetic polymers presents a fundamental strategy to explore the chemical space beyond biological systems to create advanced nanomaterials. Moreover, subsequent chemical modification of existing nanostructures is a unique approach for accessing increasingly complex nanostructures and introducing functionalities. Of these modifications, covalent conjugation chemistries, such as the click reactions, have been the cornerstone for chemists and materials scientists. Herein, we highlight some recent advances that have successfully employed click chemistries for the postmodification of assembled one-dimensional (1D) and two-dimensional (2D) nanostructures to achieve applications in molecular recognition, mineralization, and optoelectronics. Specifically, biomimetic nanomaterials assembled from sequence-defined macromolecules such as peptides and peptoids are described.
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As lead halide perovskites (LHPs) continue to achieve success as a light-harvesting material in perovskite solar cells (PSCs), exploring and understanding other materials in the device stack become increasingly important. Particularly, selection of suitable hole transport materials (HTMs) that demonstrate high performance and stability is imperative in the design of P-I-N PSCs. Presented here are a family of 12 structurally related polymers based on either fluorene or carbazole main chains with select aromatic side groups that introduce tunable properties for use in PSCs. How properties such as the highest occupied molecular orbital energy level, conductivity, glass-transition temperature, and wettability of the HTM affect the PSC performance is explored. Devices that incorporate the polymer HTMs perform well relative to PTAA in benchmark P-I-N PSC architectures while exhibiting similar or superior stability under accelerated aging studies. The relative synthetic simplicity and resultant performance of the HTMs in PSCs coupled with the ability to customize properties with different functional groups demonstrates the potential of this family of HTMs for a variety of LHP materials.
Metal-Organic Frameworks have shown great promise for memristive synaptic devices because of their adaptable electrical properties and inherent porosity, which help in efficient ion transport and storage of functional molecules. However, the limited conductivity and sensitivity to moisture associated with most MOF materials hinder their use in electronic applications. In this study, MOFs derived from metabolites have been synthesized, using ZnO as a self-sacrificial metallic source to grow Zeolitic Imidazolate Framework-8 (ZIF-8), forming ZnO@ZIF-8 heteronanostructures for neuromorphic applications. These hybrids ZnO@ZIF-8 act as promising candidates for advanced electronic applications. Through systematic investigations, including a comparison of ZnO@ZIF-8 bilayer devices with ZnO single-layer counterparts, a significant discovery emerged. The bilayer synaptic devices outperformed their single layer counterparts in electrical characteristics, as evidenced by Current-Voltage curve analysis and Long-Term Potentiation/Long Term Depression (LTP/LTD) measurements. Additionally, the ZnO layer thickness (10, 30, 50 nm) has been emphasized and the effects of annealing at 300°C in a vacuum were carefully studied for Neuromorphic Synaptic Devices. Remarkably, the 10 nm ZnO layer exhibited the lowest set voltage and a consistent On/Off ratio. This work marks a significant advancement in understanding bilayer synaptic devices, highlighting the crucial role of ZIF-8 in shaping the future of neuromorphic systems
Disorder is present to some extent in every material. The disorder can be sparse and localized – individual defects – or globally such as in a glass. Normally disorder is considered to be detrimental to function. However, this is not necessarily always the case. This project addressed the question: How does disorder provide new potentialities for the behavior of a material that would be absent in a crystalline material of the same composition? We have discovered a new principle for disordered matter: Independence of bond-level response. This work has introduced the possibility of creating new classes of mechanical meta-materials with applications everywhere from microscopic biological molecules (allostery) to large scale architectural disordered networks. During the course of this grant, we have subsequently elaborated on these novel ideas about bond-level independence of properties in disordered materials. In particular, this study has required that we understand the limits of disorder. That is, if crystals are perfect order, is there another diametrically opposed pole which is the most disordered state? We have shown that, in a well-defined way, jamming is one extreme disordered pole of rigid matter. Jamming is a far-from-equilibrium way of creating a rigid solid by rapidly quenching a random distribution of particles to a mechanically stable system at zero temperature. To understand the jammed state of matter, we have elucidated the low-frequency excitation of these systems. This has allowed a new way of understanding materials that cannot be easily classified as crystals or glasses. These ideas can be extended to address the mechanical properties of polycrystalline matter. Memory formation in matter can take inspiration from memory that occurs in a biological context. The issue of memory formation raises another set of questions at the heart of how the energy landscape is organized and how it can be manipulated to store information in a solid. This project has explored how to understand the degree to which multiple memories can be stored in a single system and has created a holistic understanding of how inputs can be used to create a desired response.
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Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.
High optical and electric contrast between the SET (crystalline) and RESET (amorphous) logic states is related to the different short and intermediate range order in orthorhombic and vitreous Sb 2 S 3 .
Confluence of extreme-scale quantum dynamics simulations (i.e. quantum@scale) and cutting-edge x-ray free-electron laser experiments are revolutionizing materials science. An archetypal example is the exciting concept of using picosecond light pulses to control emergent material properties on demand in atomically-thin layered materials. This paper describes efforts to scale our quantum molecular dynamics engine toward the United States' first exaflop/s computer, under an Aurora Early Science Program project named "Metascalable layered material genome". Key algorithmic and computing techniques incorporated are: (1) globally-scalable and locally-fast solvers within a linear-scaling divide-conquer-recombine algorithmic framework; (2) algebraic `BLASification' of computational kernels; and (3) data alignment and loop restructuring, along with register and cache blocking, for enhanced vectorization and efficient memory access. The resulting weak-scaling parallel efficiency was 0.93 on 131,072 Intel Xeon Phi cores for a 56.6 million atom (or 169 million valence-electron) system, whereas the various code transformations achieved 5-fold speedup. The optimized simulation engine allowed us for the first time to establish a significant effect of substrate on the dynamics of layered material upon electronic excitation.
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