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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 145 records · Page 8

EXPERIMENTAL AND MODELING STUDY OF MOLECULAR TRANSPORT PHENOMENA IN COMPLEX LIQUID MIXTURES USING COVALENT ORGANIC FRAMEWORK MEMBRANES

Currently, 10-15% of the world’s energy is consumed by chemical separations, and more than 80% of that is used to purify organic liquids and recover rare earth elements and critical minerals. Membrane nanofiltration presents an energy-efficient, cost-effective, and eco-friendly alternative to current separation technologies. These complex liquid environments require high- performance, chemically-resistant membrane materials. Recently discovered Covalent Organic Frameworks (COFs) possess desirable properties as membrane materials for complex liquid separations. COFs are highly crystalline, chemically and thermally stable, with tunable size and charge. COFs, especially two-dimensional highly crystalline COFs, possess narrow pore-size distribution and controlled porous structures. Two-dimensional COFs are also resistant to swelling, another feature beneficial in complex liquid separations. Molecular interactions in complex liquid systems often dictate final membrane performance, resulting in a discrepancy between designed and apparent COF properties. Understanding and resolving this discrepancy is critical in utilizing COF membranes as a viable alternative to energy-intensive separations. The primary objective of this thesis was to use a commercially available COF TpPa-1 as a platform to investigate how mixed solvent environment affects COF membrane performance via experimental and molecular modeling studies. Specifically, the effects of solution pH, solvent- solvent-solute interactions in mixed solvents, and COF chemistry were carefully examined on apparent TpPa-1 pore size and permeability and targeted solute rejection of COF membranes for neat and mixed solvents. Experimental COF filtration performance was compared and corroborated with modeling predication. Findings from this study will provide guidance for future COF design, synthesis, and desired functional COF membrane performance.

Barnes, Anastasia↗

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗

Design, Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES) v0.1.0

The DISPATCHES software will enable the design and optimization of Integrated Energy Systems (IES). The platform will support hybridizing existing generation facilities (such as nuclear and coal plants) as well as greenfield hybrid designs that incorporate advanced technologies (such as Advanced Modular Reactors and Coal FIRST), and it will enable the consideration of multiple technology options with different time constants. The design of the IES will be optimized for operation within the bulk power system via energy market signals (day ahead, real-time, and ancillary services) obtained from a production cost model. The goal of DISPATCHES is to identify flexible, dynamic designs that are responsive to grid market signals resulting in highly efficient, cost effective tightly coupled hybrid energy systems that can act as a "black box" to the grid to provide increased flexibility and resiliency.

Gunter, Daniel↗

Design Principles for the Synthesis of Self-Pillared ZSM-5 Zeolite Nanosheets

The design of next-generation materials for emerging energy and environmental applications heavily relies on empirical approaches to direct nonclassical nucleation and crystal growth pathways, polymorphism, intercrystalline transformations, and seed-assisted growth processes. A long-standing obstacle to nanoporous materials design is the complexity of their crystallization, which hinders the development of predictive models and/or physical descriptors that can guide their synthesis. In this study, we use a combination of state-of-the-art synthesis, characterization, and computational design to prepare hierarchical MFI-type zeolites, which we couple with benchmark catalytic testing to assess structure-property-performance relationships. These hierarchical materials are intergrowths of two commercially relevant zeolite frameworks, MFI and MEL, prepared as self-pillared pentasil (SPP) zeolites through seed-assisted, organic-free syntheses for which little theoretical guidance existed. Here, by comparing a large library of zeolite seeds with different pore sizes, dimensions, and structural composite building units, we determined the relative impact of seed and silica source selection, among other synthesis variables. Combined experimental and computational studies are used to test several hypotheses in literature to rationalize the choice of seed structure and establish a more robust selection criteria for seed-assisted synthesis of zeolites. Specifically, we show that a data-driven approach to develop structural descriptors correlates to new, facile routes to rationally design SPP zeolites, addressing knowledge gaps in the fundamental understanding of (non)classical crystal growth mechanisms that are characteristic of nanoporous aluminosilicates.

36 MATERIALS SCIENCE↗

Thioester synthesis by a designed nickel enzyme models prebiotic energy conversion

The formation of carbon–carbon bonds from prebiotic precursors such as carbon dioxide represents the foundation of all primordial life processes. In extant organisms, this reaction is carried out by the carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS) enzyme, which performs the cornerstone reaction in the ancient Wood–Ljungdahl metabolic pathway to synthesize the key biological metabolite, acetyl-CoA. Despite its significance, a fundamental understanding of this transformation is lacking, hampering efforts to harness analogous chemistry. To address these knowledge gaps, we have designed an artificial metalloenzyme within the azurin protein scaffold as a structural, functional, and mechanistic model of ACS. We demonstrate the intermediacy of the Ni I species and requirement for ordered substrate binding in the bioorganometallic carbon–carbon bond-forming reaction from the one-carbon ACS substrates. The electronic and geometric structures of the nickel-acetyl intermediate have been characterized using time-resolved optical, electron paramagnetic resonance, and X-ray absorption spectroscopy in conjunction with quantum chemical calculations. Moreover, we demonstrate that the nickel-acetyl species is chemically competent for selective acyl transfer upon thiol addition to biosynthesize an activated thioester. Drawing an analogy to the native enzyme, a mechanism for thioester generation by this ACS model has been proposed. The fundamental insight into the enzymatic process provided by this rudimentary ACS model has implications for the evolution of primitive ACS-like proteins. Ultimately, these findings offer strategies for development of highly active catalysts for sustainable generation of liquid fuels from one-carbon substrates, with potential for broad applications across diverse fields ranging from energy storage to environmental remediation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis

Domain-specific designs offer greater energy efficiency and performance gain than general-purpose processors. For this reason, modern system-on-chips have a significant portion of their silicon area with custom accelerators. However, designing hardware by hand is laborious and time-consuming, given the large design space and the performance, power, and area constraints that are not realized in the software. Moreover, domain-specific algorithms (e.g., machine learning models) are evolving quickly, challenging the accelerator design further. To address these issues, this paper presents SODA Synthesizer, an automated open-source high-level ML framework to Verilog modular compiler targeting AI/ML Application-Specific Integrated Circuits (ASICs) accelerators. SODA tightly couples the Multi- Level Intermediate Representation (MLIR) compiler infrastructure [24] and open-source HLS approaches. Thus, SODA can support various ML frameworks and algorithms and can perform optimizations that combine specialized architecture templates and conventional HLS to generate the hardware modules. In addition, SODA’s closed-loop design space exploration (DSE) engine allows developers to perform end-to-end design space explorations on different metrics and technology nodes.

Zhang, Jeff↗

Interfacing DNA nanotechnology and biomimetic photonic complexes: advances and prospects in energy and biomedicine

Abstract Self-assembled photonic systems with well-organized spatial arrangement and engineered optical properties can be used as efficient energy materials and as effective biomedical agents. The lessons learned from natural light-harvesting antennas have inspired the design and synthesis of a series of biomimetic photonic complexes, including those containing strongly coupled dye aggregates with dense molecular packing and unique spectroscopic features. These photoactive components provide excellent features that could be coupled to multiple applications including light-harvesting, energy transfer, biosensing, bioimaging, and cancer therapy. Meanwhile, nanoscale DNA assemblies have been employed as programmable and addressable templates to guide the formation of DNA-directed multi-pigment complexes, which can be used to enhance the complexity and precision of artificial photonic systems and show the potential for energy and biomedical applications. This review focuses on the interface of DNA nanotechnology and biomimetic photonic systems. We summarized the recent progress in the design, synthesis, and applications of bioinspired photonic systems, highlighted the advantages of the utilization of DNA nanostructures, and discussed the challenges and opportunities they provide. Graphical Abstract

59 BASIC BIOLOGICAL SCIENCES↗

Synthesis and Processing by Design of High-Nickel Cathode Materials

The high demand of lightweight, high energy density batteries for energy storage promotes new materials discovery and development. Despite the large number of battery materials being discovered, very few of them have been commercially deployed, mostly bottlenecked by synthesis and processing – namely, making certain phases with the desired structure and properties to meet the multifaceted performance requirements. Alternative to the traditional trial and error, we present here an in situ study aided synthesis- and processing-by-design approach. With specific examples, we illustrate how to use the approach to identify reaction pathways in synthesis and processing of high-Nickel (Ni) cathode materials for next-generation lithium-ion batteries, thereby ensuring precise control of their structure, morphology, and surface properties. Furthermore, perspectives are provided on the wide applicability of the approach to solving critical issues inherent to high-Ni cathodes and the new directions and opportunities in the area.

36 MATERIALS SCIENCE↗

Structurally Defined Water‐Soluble Metallofullerene Derivatives towards Biomedical Applications

Abstract Endohedral metallofullerenes (EMFs) are excellent carriers of rare‐earth element (REE) ions in biomedical applications because they preclude the release of toxic metal ions. However, existing approaches to synthesize water‐soluble EMF derivatives yield mixtures that inhibit precise drug design. Here we report the synthesis of metallobuckytrio (MBT), a three‐buckyball system, as a modular platform to develop structurally defined water‐soluble EMF derivatives with ligands by choice. Demonstrated with PEG ligands, the resulting water‐soluble MBTs show superb biocompatibility. The Gd MBTs exhibit superior T 1 relaxivity than typical Gd complexes, potentially superseding current clinical MRI contrast agents in both safety and efficiency. The Lu MBTs generated reactive oxygen species upon light irradiation, showing promise as photosensitizers. With their modular nature to incorporate other ligands, we anticipate the MBT platform to open new paths towards bio‐specific REE drugs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computationally aided, entropy-driven synthesis of highly efficient and durable multi-elemental alloy catalysts

Multi-elemental alloy nanoparticles (MEA-NPs) hold great promise for catalyst discovery in a virtually unlimited compositional space. However, rational and controllable synthesize of these intrinsically complex structures remains a challenge. Here, we report the computationally aided, entropy-driven design and synthesis of highly efficient and durable catalyst MEA-NPs. The computational strategy includes prescreening of millions of compositions, prediction of alloy formation by density functional theory calculations, and examination of structural stability by a hybrid Monte Carlo and molecular dynamics method. Selected compositions can be efficiently and rapidly synthesized at high temperature (e.g., 1500 K, 0.5 s) with excellent thermal stability. We applied these MEA-NPs for catalytic NH 3 decomposition and observed outstanding performance due to the synergistic effect of multi-elemental mixing, their small size, and the alloy phase. We anticipate that the computationally aided rational design and rapid synthesis of MEA-NPs are broadly applicable for various catalytic reactions and will accelerate material discovery.

36 MATERIALS SCIENCE↗

Low temperature, ambient pressure electrochemical ammonia synthesis in alkaline media — Mechanistic studies and catalyst design. Final Report

Ammonia synthesis via the Haber-Bosch process is a pillar of modern agriculture, which converts the abundant but inert dinitrogen in the atmosphere to nitrogen-based fertilizers. Despite more than a century of optimization, the Haber-Bosch process remains energy intensive and reliant on fossil fuels and produces large amounts of CO 2 . Distributed and modular ammonia synthesis via the electrochemical nitrogen reduction reaction (ENRR) at or close to ambient conditions, powered by renewable electricity is an attractive alternative because it allows as needed production of ammonia, and in turn fertilizers. However, selective ENRR catalysts remain lacking. In this project, we systematically investigated two categories of catalytic materials, i.e., precious metals and transition metal nitrides, in the ENRR. Precious metals exhibit low activity and selectivity in the ENRR, which is in agreement with recent computational studies. Transition metal nitrides, especially VN, has been demonstrated as active and selective ENRR catalysts. We developed the first quantitative method to determine the amount of ammonia produced in the ENRR on N-containing containing catalysts in the membrane electrode assembly configuration. An initial ammonia production rate of 6.6 × 10 -10 mol s -1 mg -1 and a Faradaic efficiency of 6.0% at -0.1 V were reached on VN. After the initial deactivation, VN was shown to be stable in the ENRR for 116 hours with a steady state ammonia production rate of 1.1 × 10 -10 mol s -1 cm -2 . A vanadium oxynitride species was identified as the active phase in the ENRR via a combination of operando and ex situ characterization techniques. In addition, we established that the ENRR proceeded on transition metal nitrides via the Mars van Krevelen mechanism and determined the initial and steady state active site densities by developing a quantitative isotopic exchange method.

42 ENGINEERING↗

Revealing Deformation Mechanisms in Polymer-Grafted Thermoplastic Elastomers via In Situ Small-Angle X-ray Scattering

The tunable properties of thermoplastic elastomers (TPEs), through polymer chemistry manipulations, enable these technologically critical materials to be employed in a broad range of applications. The need to “dial-in” the mechanical properties and responses of TPEs generally requires the design and synthesis of new macromolecules. In these designs, TPEs with nonlinear macromolecular architectures outperform the mechanical properties of their linear copolymer counterparts, but the differences in the deformation mechanism providing enhanced performance are unknown. Here, in situ small-angle X-ray scattering (SAXS) measurements during uniaxial extension reveal distinct deformation mechanisms between a commercially available linear poly(styrene)–poly(butadiene)–poly(styrene) (SBS) triblock copolymer and the grafted SBS version containing grafted poly(styrene) (PS) chains from the poly(butadiene) (PBD) midblock. The neat SBS (φ SBS = 100%) sample deforms congruently with the macroscopic dimensions, with the domain spacing between spheres increasing and decreasing along and transverse to the stretch direction, respectively. At high extensions, end segment pullout from the PS-rich domains is detected, which is indicated by a disordering of SBS. Conversely, the PS-grafted SBS that is 30 vol % SBS and 70% styrene (φ SBS = 30%) exhibits a lamellar morphology, and in situ SAXS measurements reveal an unexpected deformation mechanism. During deformation, there are two simultaneous processes: significant lamellar domain rearrangement to preferentially orient the lamellae planes parallel to the stretch direction and crazing. The samples whiten at high strains as expected for crazing, which corresponds with the emergence of features in the 2D SAXS pattern during stretching consistent with fibril-like structures that bridge the voids in crazes. The significant domain rearrangement in the grafted copolymers is attributed to the new junctions formed across multiple PS domains by the grafting of a single chain. In conclusion, the in situ SAXS measurements provide insights into the enhanced mechanical properties of grafted copolymers that arise through improved physical cross-linking that leads to nanostructure domain reorientation for self-reinforcement and craze formation where fibrils help to strengthen the polymer.

36 MATERIALS SCIENCE↗

Multi-scale computer-aided design and photo-controlled macromolecular synthesis boosting uranium harvesting from seawater

By integrating multi-scale computational simulation with photo-regulated macromolecular synthesis, this study presents a new paradigm for smart design while customizing polymeric adsorbents for uranium harvesting from seawater. A dissipative particle dynamics (DPD) approach, combined with a molecular dynamics (MD) study, is performed to simulate the conformational dynamics and adsorption process of a model uranium grabber, i.e., PAO m -b-PPEGMA n , suggesting that the maximum adsorption capacity with atomic economy can be achieved with a preferred block ratio of 0.18. The designed polymers are synthesized using the PET-RAFT polymerization in a microfluidic platform, exhibiting a record high adsorption capacity of uranium (11.4 ± 1.2 mg/g) in real seawater within 28 days. This study offers an integrated perspective to quantitatively assess adsorption phenomena of polymers, bridging metal-ligand interactions at the molecular level with their spatial conformations at the mesoscopic level. The established protocol is generally adaptable for target-oriented development of more advanced polymers for broadened applications.

97 MATHEMATICS AND COMPUTING↗

Eutectic Synthesis of the P2-Type Na x Fe 1/2 Mn 1/2 O 2 Cathode with Improved Cell Design for Sodium-Ion Batteries

An engaging area of research in sodium-ion batteries (SIBs) has been focusing on discovery, design, and synthesis of high-capacity cathode materials in order to boost energy density to levels close enough to that of state-of-the-art lithium-ion batteries. Of particular interest, P2-type layered oxide, Na 2/3 Fe 1/2 Mn 1/2 O 2 , has been researched as a potential cathode in SIBs based on its high theoretical capacity of 260 mA h/g and use of noncritical materials. However, the reported synthesis methods are not only complex and energy-demanding but also often yield inhomogeneous and impure materials with capacities less than 200 mA h/g under impractical test conditions. Here, we report a novel synthesis route using low-temperature eutectic reaction to produce highly homogeneous, crystalline, and impurity-free P2-Na x Fe 1/2 Mn 1/2 O 2 with enhanced Na-ion diffusivity and kinetics. The overall electrochemical performances of the Na-ion cells have been improved by pairing the P2-cathode with presodiated hard carbon anodes, leading to reversible capacities in the range of 180 mA h/g. This new approach is a contribution toward the simplification of synthesis and scalability of sodium-based cathodes with high crystallinity and fine-tuned morphology and the realization of a sodium-ion battery system with lower cost and improved electrochemical performance.

25 ENERGY STORAGE↗

A technoeconomic analysis of poly- and single-crystalline NMCxyz from material synthesis to battery pack design

A process model was developed for estimating the cost of manufacturing lithium nickel manganese cobalt oxide (LiNi x Mn y Co z O 2 , NMCxyz), the main cathode active material in lithium-ion batteries used for electric vehicles in the United States. The model was used to estimate the prices of NMC622, NMC811, and NMC955 with poly- and single-crystalline morphologies. The Battery Performance and Cost Model (BatPaC) was used to translate the NMC prices into battery pack prices. A decrease in cobalt content from NMC622 (20% Co) to NMC955 (5% Ni) decreases the material price by $\$$0.85/kg (−3%) due to a decrease in the cost of battery materials, which account for >60% of the total price. NMC622 only produce cheaper packs if the nickel sulfate cost is > 4 × its baseline, indicating higher nickel materials will lower pack cost under normal market conditions. Single-crystalline materials are $\$$2/kg (+8%) more expensive than their polycrystalline counterparts due to higher manufacturing costs from longer, hotter calcinations in less densely packed saggars. This increases the pack price by ∼$\$$3/kWh, assuming identical electrochemical properties. In conclusion, the single-crystalline materials could yield cheaper packs if cycled to higher upper cutoff voltages (i.e., 4.35 to 4.43 V for the single-crystalline material vs. 4.25 V for their polycrystalline counterparts).

Cost modeling↗

The SODA Approach: Leveraging High-Level Synthesis for Hardware/Software Co-design and Hardware Specialization: Invited

Novel "converged" applications combine phases of scientific simulation with data analysis and machine learning. Each computational phase can benefit from specialized accelerators. However, algorithms evolve so quickly that mapping them on existing accelerators is suboptimal or even impossible. This paper presents the SODA (Software Defined Accelerators) framework, a modular, multi-level, open-source, no-human-in-the-loop, hardware synthesizer that enables end-to-end generation of specialized accelerators. SODA is composed of SODA-Opt, a high-level frontend developed in MLIR that interfaces with domain-specific programming frameworks and allows performing system level design, and Bambu, a state-of-the-art high-level synthesis engine that can target different device technologies. The framework implements design space exploration as compiler optimization passes. We show how the modular, yet tight, integration of the high-level optimizer and lower-level HLS tools enables the generation of accelerators optimized for the computational patterns of converged applications. We then discuss some of the research opportunities that such a framework allows, including system-level design, profile driven optimization, and supporting new optimization metrics.

Bohm Agostini, Nicolas↗

A Review on Challenges and Successes in Atomic-Scale Design of Catalysts for Electrochemical Synthesis of Hydrogen Peroxide

Hydrogen peroxide is a valuable chemical oxidant with a wide range of applications in a variety of industrial processes, especially in water sanitization. Electrochemical synthesis of hydrogen peroxide (H 2 O 2 ) through a two-electron oxygen reduction reaction (2e-ORR) or a two-electron water oxidation reaction (2e-WOR) has emerged as an appealing process for onsite production of this chemically valuable oxidant. On-site produced H 2 O 2 can be applied for wastewater treatment in remote locations or any applications where H 2 O 2 is needed as an oxidizing agent. Overall, this Review studies the theoretical efforts in understanding the challenges in catalysis for electrochemical synthesis of H 2 O 2 as well as providing design principles for more efficient catalyst materials.

36 MATERIALS SCIENCE↗