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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermodynamic stability versus kinetic accessibility: Pareto fronts for programmable self-assembly

A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. Additionally, the tradeoff disappears when the number of particle types reaches a value m *, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic–kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Label-free affinity screening, design and synthesis of inhibitors targeting the Mycobacterium tuberculosis L-alanine dehydrogenase

The ability of Mycobacterium tuberculosis (Mtb) to persist in its host may enable an evolutionary advantage for drug resistant variants to emerge. A potential strategy to prevent persistence and gain drug efficacy is to directly target the activity of enzymes that are crucial for persistence. We present a method for expedited discovery and structure-based design of lead compounds by targeting the hypoxia-associated enzyme L-alanine dehydrogenase (AlaDH). Biochemical and structural analyses of AlaDH confirmed binding of nucleoside derivatives and showed a site adjacent to the nucleoside binding pocket that can confer specificity to putative inhibitors. Using a combination of dye-ligand affinity chromatography, enzyme kinetics and protein crystallographic studies, we show the development and validation of drug prototypes. Crystal structures of AlaDH-inhibitor complexes with variations at the N6 position of the adenyl-moiety of the inhibitor provide insight into the molecular basis for the specificity of these compounds. We describe a drug-designing pipeline that aims to block Mtb to proliferate upon re-oxygenation by specifically blocking NAD accessibility to AlaDH. The collective approach to drug discovery was further evaluated through in silico analyses providing additional insight into an efficient drug development strategy that can be further assessed with the incorporation of in vivo studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Reinforcement learning for block decomposition of planar CAD models

Abstract The problem of hexahedral mesh generation of general CAD models has vexed researchers for over 3 decades and analysts often spend more than 50% of the design-analysis cycle time decomposing complex models into simpler blocks meshable by existing techniques. The decomposed blocks are required for generating good quality meshes (tilings of quadrilaterals or hexahedra) suitable for numerical simulations of physical systems governed by conservation laws. We present a novel AI-assisted method for decomposing (segmenting) planar CAD (computer-aided design) models into well shaped rectangular blocks. Even though the simple examples presented here can also be meshed using many conventional methods, we believe this work is proof-of-principle of a AI-based decomposition method that can eventually be generalized to complex 2D and 3D CAD models. Our method uses reinforcement learning to train an agent to perform a series of optimal cuts on the CAD model that result in a good quality block decomposition. We show that the agent quickly learns an effective strategy for picking the location and direction of the cuts and maximizing its rewards. This paper is the first successful demonstration of an agent autonomously learning how to perform this block decomposition task effectively, thereby holding the promise of a viable method to automate this challenging process for more complex cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Peptoid-based hierarchically-structured biomimetic nanomaterials: Synthesis, characterization and applications

Peptoids (or poly-N-substituted glycines) is a promising class of bioinspired sequence-defined polymers due to their highly efficient synthesis, high chemical stability, enzyme hydrolysis resistance, and biocompatibility. By tuning the side chain chemistry of peptoids, it allows for a precise control over sequences and achieving a large side-chain diversity. Due to these unique features, in the last several years, many amphiphilic peptoids were designed as highly tunable building blocks for the preparation of biomimetic nanomaterials with well-defined hierarchical structures and desired functionalities. In this paper, we provide an overview of the recent achievements in this area by dividing them into the following three aspects. First, mica- and silica-templated peptoid self-assembly was summarized. Here, the presence of inorganic substrates provides the guarantee of investigating their self-assembly mechanisms and interactions between peptoids and substrates using nanoscale characterization techniques, particularly in situ atomic force spectroscopy (AFM) and AFM-based dynamic force spectroscopy (AFM-DFS). Second, solution-phase self-assembly of peptoids into nanotubes and nanosheets was presented, as well as their self-repair properties. Third, the applications of peptoid based nanomaterials were outlined, including the construction of catalytic nanomaterials as a template and cytosolic delivery as cargoes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spontaneous Reorganization of DNA-Based Polymers in Higher Ordered Structures Fueled by RNA

We demonstrate a strategy that allows for the spontaneous reconfiguration of self-assembled DNA polymers exploiting RNA as chemical fuel. To do this, we have rationally designed orthogonally addressable DNA building blocks that can be transiently deactivated by RNA fuels and subtracted temporarily from participation in the self-assembly process. Through a fine modulation of the rate at which the building blocks are reactivated we can carefully control the final composition of the polymer and convert a disordered polymer in a higher order polymer, which is disfavored from a thermodynamic point of view. We measure the dynamic reconfiguration via fluorescent signals and confocal microscopy, and we derive a kinetic model that captures the experimental results. Our approach suggests a novel route toward the development of biomolecular materials in which engineered chemical reactions support the autonomous spatial reorganization of multiple components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗
DOE OSTI2020

Low cost, flexible, and distribution level universal grid analyser platform: designs and implementations

This study presents the designs and implementations of a distribution level open-universal grid analyser (Open-UGA) platform. The proposed Open-UGA platform consists of distribution-level phasor measurement units (PMUs), a standard signal generator, a router, and a server. Firstly, an overall introduction for the software, hardware, and server architectures of the Open-UGA platform is given. To give a detailed design, the software, hardware, server block diagrams, flowcharts, and printed circuit board photo of the Open-UGA platform are presented in detail. Then, four different types of distribution level PMU algorithms are introduced and implemented in the Open-UGA platform to verify the flexibility and reconfigurability. The flowcharts and functionalities of these four UGAs with different PMU algorithms are given as example implementations. Lastly, a performance comparison is conducted with both quantitative and illustrative results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Strategies for on-chip digital data compression for X-ray pixel detectors

Here, the continued desire for X-ray pixel detectors with higher frame rates will stress the ability of application-specific integrated circuit (ASIC) designers to provide sufficient off-chip bandwidth to reach continuous frame rates in the 1 MHz regime. To move from the current 10 kHz to the 1 MHz frame rate regime, ASIC designers will continue to pack as many power-hungry high-speed transceivers at the periphery of the ASIC as possible. In this paper, however, we present new strategies to make the most efficient use of the off-chip bandwidth by utilizing data compression schemes for X-ray photon-counting and charge-integrating pixel detectors. In particular, we describe a novel in-pixel compression scheme that converts from analog to digital converter units to encoded photon counts near the photon Poisson noise level and achieves a compression ratio of >1.5x independent of the dataset. In addition, we describe a simple yet efficient zero-suppression compression scheme called "zeromask" (ZM) located at the ASIC's edge before streaming data off the ASIC chip. ZM achieves average compression ratios of >4x, >7x, and >8x for high-energy X-ray diffraction, ptychography, and X-ray photon correlation spectroscopy datasets, respectively. We present the conceptual designs, register-transfer level block diagrams, and the physical ASIC implementation of these compression schemes in 65 nm CMOS. When combined, these two digital compression schemes could increase the effective off-chip bandwidth by a factor of 6-12x.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Design of Auxiliary Power Supply for Medium Voltage Applications

Typical voltage levels from medium-voltage (MV) applications introduce additional challenges to designing the auxiliary power supply (APS) necessary to provide power to the secondary circuits of the main converter. This paper aims to present the design of a 100 W APS for 0.6–2 kV input DC voltage and 24 V output. The selected architecture addresses the medium voltage to low voltage challenge by adopting two stage approach – a simple robust DC transformer (DCX) stage and a low voltage regulation stage. The design of the main building blocks of the APS are described followed by simulation results.

Magri Kimpara, Marcio↗
DOE OSTI2020

AMR-Wind [SWR-20-85]

AMR-Wind is a massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations. The solver is built on top of the AMReX library. AMReX is developed at LBNL , NREL , and ANL as part of the Block-Structured AMR Co-Design Center in DOE's Exascale Computing Project. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. The primary applications for AMR-Wind are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm.

Ananthan, Shreyas↗
DOE OSTI2025

Frontal Slice Approaches for Tensor Linear Systems

Inspired by the row and column action methods for solving large-scale linear systems, in this work, we explore the use of frontal slices for solving tensor linear systems. In particular, this paper presents a novel approach for using frontal slices of a tensor $\mathcal{A}$ to solve tensor linear systems $\mathcal{A} ∗\mathcal{X} = \mathcal{B}$ where ∗ denotes the $t$-product. In addition, we consider variations of this method, including cyclic, block, and randomized approaches, each designed to optimize performance in different operational contexts. Our primary contribution lies in the development and convergence analysis of these methods. Experimental results on synthetically generated and real-world data, including applications such as image and video deblurring, demonstrate the efficacy of our proposed approaches and validate our theoretical findings.

Luo, Hengrui↗
DOE OSTI2022

Proof-of-Principle Design of a High-Field Overpass/Underpass Nb 3 Sn Dipole

A block coil geometry is appealing in the body of particle accelerator dipole or quadrupole magnets, but less so in the ends of conventional designs, because conductors near the midplane of the beam tube must be bent in the hard direction to cross over to the other side of the tube. In order to avoid damage to brittle conductors such as Nb 3 Sn or HTS, the bend must be very gradual, resulting in undesirably long magnet ends. An alternative design -"overpass/underpass" or "cloverleaf" - can ramp the conductor within a short length with bending only in the easy direction. Described here is a proof-of-principle design and analysis of an "overpass/underpass" coil geometry for a block coil dipole of 11 Tor more.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Fundamental Processes and Practical Considerations of Lead Chalcogenide Mesocrystals Formed via Self-Assembly and Directed Attachment of Nanocrystals at a Fluid Interface

Significant advances in the synthesis and processing of colloidal nanocrystals have given scientists and engineers access to a vast library of building blocks with precisely defined size, shape, and composition. These materials have inspired exciting prospects to enable bottom-up fabrication of programmable materials with properties by design. Successfully assembling and connecting the building blocks into superstructures in which constituent nanocrystals can purposefully interact requires robust understanding of and control over a complex interplay of dynamic physicochemical processes. Fluid interfaces provide an advantageous experimental workbench to both probe and control these processes. Despite the ostensible simplicity of fabricating nanocrystal assemblies at a fluid interface, sensitivity to processing conditions and limited reproducibility have underscored the complexity of this process. In situ studies have provided mechanistic insights into the competing dynamics of key subprocesses including solvent spreading and evaporation, superlattice formation, ligand detachment kinetics, and nanocrystal attachment. Understanding how these subprocesses influence the complex choreography of self-assembly, structure transformation, and oriented attachment processes presents a rich research challenge. In this context, we present a detailed methodology for self-assembly and attachment of lead chalcogenide nanocrystals at a liquid–gas interface as a model system for the fabrication of mono- and multilayer cubic connected superlattices. We discuss key experimental parameters such as the characteristics of the building blocks and processing conditions and detailed steps from colloidal nanocrystal injection to superlattice transfer. Furthermore, we hope that this Methods/Protocols paper will provide guidance for future advances in the exciting path toward bringing the prospect of nanocrystal-based programmable materials to fruition.

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

De novo design of obligate ABC-type heterotrimeric proteins

The de novo design of three protein chains that associate to form a heterotrimer (but not any of the possible two-chain heterodimers) and that can drive the assembly of higher-order branching structures is an important challenge for protein design. We designed helical heterotrimers with specificity conferred by buried hydrogen bond networks and large aromatic residues to enhance shape complementary packing. We obtained ten designs for which all three chains cooperatively assembled into heterotrimers with few or no other species present. Crystal structures of a helical bundle heterotrimer and extended versions, with helical repeat proteins fused to individual subunits, showed all three chains assembling in the designed orientation. We used these heterotrimers as building blocks to construct larger cyclic oligomers, which were structurally validated by electron microscopy. Our three-way junction designs provide new routes to complex protein nanostructures and enable the scaffolding of three distinct ligands for modulation of cell signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Block Island Survey and Deployment Operations Data

This dataset contains survey, navigation, and platform-design data supporting instrument deployment and positioning during the 2016-2017 RODEO field operations at Block Island. It includes an acoustic localization software toolkit and its Block Island position solutions, R/V Tioga ship navigation and underway data, CTD casts, ship-track charts, and engineering designs for the deployed moorings and arrays.

17 WIND ENERGY↗
DOE OSTI2024

A molecular view of peptoid-induced acceleration of calcite growth

The extensive deposits of calcium carbonate (CaCO 3 ) generated by marine organisms constitute the largest and oldest carbon dioxide (CO 2 ) reservoir. These organisms utilize macromolecules like peptides and proteins to facilitate the nucleation and growth of carbonate minerals, serving as an effective method for CO 2 sequestration. However, the precise mechanisms behind this process remain elusive. In this study, we report the use of sequence-defined peptoids, a class of peptidomimetics, to achieve the accelerated calcite step growth kinetics with the molecular level mechanistic understanding. By designing peptoids with hydrophilic and hydrophobic blocks, we systematically investigated the acceleration in step growth rate of calcite crystals using in situ atomic force microscopy (AFM), varying peptoid sequences and concentrations, CaCO 3 supersaturations, and the ratio of Ca 2+ / HCO 3 − . Mechanistic studies using NMR, three-dimensional fast force mapping (3D FFM), and isothermal titration calorimetry (ITC) were conducted to reveal the interactions of peptoids with Ca 2+ and HCO 3 − ions in solution, as well as the effect of peptoids on solvation and energetics of calcite crystal surface. Our results indicate the multiple roles of peptoid in facilitating HCO 3 − deprotonation, Ca 2+ desolvation, and the disruption of interfacial hydration layers of the calcite surface, which collectively contribute to a peptoid-induced acceleration of calcite growth. These findings provide guidelines for future design of sequence-specific biomimetic polymers as crystallization promoters, offering potential applications in environmental remediation (such as CO 2 sequestration), biomedical engineering, and energy storage where fast crystallization is preferred.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Highly potent, naturally acquired human monoclonal antibodies against Pfs48/45 block Plasmodium falciparum transmission to mosquitoes

Malaria transmission-blocking vaccines (TBVs) aim to induce antibodies that interrupt malaria parasite development in the mosquito, thereby blocking onward transmission, and provide a much-needed tool for malaria control and elimination. The parasite surface protein Pfs48/45 is a leading TBV candidate. Here, we isolated and characterized a panel of 81 human Pfs48/45-specific monoclonal antibodies (mAbs) from donors naturally exposed to Plasmodium parasites. Genetically diverse mAbs against each of the three domains (D1–D3) of Pfs48/45 were identified. The most potent mAbs targeted D1 and D3 and achieved >80% transmission-reducing activity in standard membrane-feeding assays, at 10 and 2 μg/mL, respectively. Co-crystal structures of D3 in complex with four different mAbs delineated two conserved protective epitopes. Altogether, these Pfs48/45-specific human mAbs provide important insight into protective and non-protective epitopes that can further our understanding of transmission and inform the design of refined malaria transmission-blocking vaccine candidates.

60 APPLIED LIFE SCIENCES↗