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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Engineering Self-Assembled Domain Asymmetry in Solvent Vapor Annealed Block Copolymer–Homopolymer Blend Films

Thin-film block copolymer (BCP) self-assembly is a powerful approach to generate highly uniform nanopatterns across large areas, yet the symmetries of these nanopatterns are constrained by the relative volume occupied by each polymer block. Here, we present a conceptually new approach to circumvent this limitation by combining homopolymer (HP) blending with solvent vapor annealing (SVA), demonstrated here for ternary blends of a near-symmetric BCP with athermal, low molar mass HPs. Screening of BCP–HP interactions by a weakly selective solvent promotes entropically driven delocalization of HP throughout both blocks and enables assembly of metastable lamellae for volume fractions as high as 0.78. Subsequent brief thermal annealing induces HPs to withdraw to their enthalpically favored domains, sharpening domain interfaces on a time scale much shorter than pattern coarsening. This renders lamellar nanopatterns with tunable widths that can be transferred to other materials with high fidelity. Furthermore, the persistence of the metastable asymmetric lamellae upon thermal annealing is sensitive to film confinement, as they are preserved in submonolayer films but transition to horizontal cylinders in films more than one monolayer thick. SVA using a strongly selective solvent results in assembled morphologies aligned closely with expectations based on the total polymer blend composition, underscoring the key role of BCP–HP interactions in dictating domain asymmetry. Overall, this work details important principles for using SVA to mediate BCP–HP interactions in thin films, thereby presenting opportunities to engineer pathways for the assembly of well-ordered nanopatterns with designer feature asymmetry for lithographic or nanotexturing applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Nanobodies against the metal binding domains of ATP7B as tools to study copper transport in the cell

Abstract Nanobodies are genetically engineered single domain antibodies derived from the unusual heavy-chain only antibodies found in llamas and camels. The small size of the nanobodies and flexible selection schemes make them uniquely versatile tools for protein biochemistry and cell biology. We have developed a panel of nanobodies against the metal binding domains of the human copper transporter ATP7B, a multidomain membrane protein with a complex regulation of enzymatic activity and intracellular localization. To enable the use of the nanobodies as tools to investigate copper transport in the cell, we characterized their binding sites and affinity by isothermal titration calorimetry and NMR. We have identified nanobodies against each of the first four metal binding domains of ATP7B, with a wide affinity range, as evidenced by dissociation constants from below 10−9 to 10−6 M. We found both the inhibitory and activating nanobodies among those tested. The diverse properties of the nanobodies make the panel useful for the structural studies of ATP7B, immunoaffinity purification of the protein, modulation of its activity in the cell, protein dynamics studies, and as mimics of copper chaperone ATOX1, the natural interaction partner of ATP7B.

Uhlemann, Eva-Maria E.↗
DOE OSTI2023

Engineered immunogens to elicit antibodies against conserved coronavirus epitopes

Immune responses to SARS-CoV-2 primarily target the receptor binding domain of the spike protein, which continually mutates to escape acquired immunity. Other regions in the spike S2 subunit, such as the stem helix and the segment encompassing residues 815-823 adjacent to the fusion peptide, are highly conserved across sarbecoviruses and are recognized by broadly reactive antibodies, providing hope that vaccines targeting these epitopes could offer protection against both current and emergent viruses. Here we employ computational modeling to design scaffolded immunogens that display the spike 815-823 peptide and the stem helix epitopes without the distracting and immunodominant receptor binding domain. These engineered proteins bind with high affinity and specificity to the mature and germline versions of previously identified broadly protective human antibodies. Epitope scaffolds interact with both sera and isolated monoclonal antibodies with broadly reactivity from individuals with pre-existing SARS-CoV-2 immunity. When used as immunogens, epitope scaffolds elicit sera with broad betacoronavirus reactivity and protect as “boosts” against live virus challenge in mice, illustrating their potential as components of a future pancoronavirus vaccine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Engineering Polyketide Stereocenters with Ketoreductase Domain Exchanges

Polyketide synthases (PKSs) are versatile biosynthetic megasynthases capable of producing a diverse range of natural products with many applications, including in pharmaceuticals. The stereochemical precision of PKSs makes them a powerful tool for engineering tailored, unnatural polyketides; however, modifying the stereocenters of a PKS product while maintaining production levels remains a significant challenge. In this study, we systematically tested and evaluated strategies for ketoreductase (KR) domain exchanges, the domain responsible for setting stereocenters of polyketide products. After first optimizing the method for KR exchanges, we then performed 44 KR domain exchanges on three different PKSs to obtain high production of all four stereoisomers in vivo. By testing both one- and two-module PKS systems, we investigated how downstream modules process intermediates with altered stereochemistry and found that the configuration of the α-substituents was critical for gatekeeping by the ketosynthase (KS). To overcome this constraint, we investigated two different strategies for altering the KS domain, including introducing targeted mutations in the downstream KS, and exploring boundaries in exchanging the entire functional unit from the donor PKS. Both strategies successfully modified the KS stereocontrol with distinct trade-offs; the functional unit exchange resulted in higher titer improvements, though it was more likely to break the entire PKS. This study demonstrates a comprehensive approach to successfully engineering all four stereochemical configurations in multiple PKS systems, advancing our understanding of and ability to rationally modify polyketide stereochemistry through multiple engineering strategies.

Keiser, Leah S. [Joint BioEnergy Institute (JBEI),↗
DOE OSTI2021

Structural basis for antibody binding to adenylate cyclase toxin reveals RTX linkers as neutralization-sensitive epitopes

RTX leukotoxins are a diverse family of prokaryotic virulence factors that are secreted by the type 1 secretion system (T1SS) and target leukocytes to subvert host defenses. T1SS substrates all contain a C-terminal RTX domain that mediates recruitment to the T1SS and drives secretion via a Brownian ratchet mechanism. Neutralizing antibodies against the Bordetella pertussis adenylate cyclase toxin, an RTX leukotoxin essential for B . pertussis colonization, have been shown to target the RTX domain and prevent binding to the α M β 2 integrin receptor. Knowledge of the mechanisms by which antibodies bind and neutralize RTX leukotoxins is required to inform structure-based design of bacterial vaccines, however, no structural data are available for antibody binding to any T1SS substrate. Here, we determine the crystal structure of an engineered RTX domain fragment containing the α M β 2 -binding site bound to two neutralizing antibodies. Notably, the receptor-blocking antibodies bind to the linker regions of RTX blocks I–III, suggesting they are key neutralization-sensitive sites within the RTX domain and are likely involved in binding the α M β 2 receptor. As the engineered RTX fragment contained these key epitopes, we assessed its immunogenicity in mice and showed that it elicits similar neutralizing antibody titers to the full RTX domain. The results from these studies will support the development of bacterial vaccines targeting RTX leukotoxins, as well as next-generation B . pertussis vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

AI-Driven Crack Detection for Remanufacturing Cylinder Heads Using Deep Learning and Engineering-Informed Data Augmentation

Detecting cracks in cylinder heads traditionally relies on manual inspection, which is time-consuming and susceptible to human error. As an alternative, automated object detection utilizing computer vision and machine learning models has been explored. However, these methods often face challenges due to a lack of sufficiently annotated training data, limited image diversity, and the inherently small size of cracks. Addressing these constraints, this paper introduces a novel automated crack-detection method that enhances data availability through a synthetic data generation technique. Unlike general data augmentation practices, our method involves copying cracks from one location to another, guided by both random and informed engineering decisions about likely crack formations due to cyclic thermomechanical loads. The innovative aspect of our approach lies in the integration of domain-specific engineering knowledge into the synthetic generation process, which substantially improves detection accuracy. We evaluate our method’s effectiveness using two metrics: the F2 score, which emphasizes recall to prioritize detecting all potential cracks, and mean average precision (MAP), a standard measure in object detection. Experimental results demonstrate that, without engineering insights, our method increases the F2 score from 0.40 to 0.65, while maintaining a stable MAP. Incorporating detailed engineering knowledge further enhances the F2 score to 0.70 and improves MAP to 0.57, representing increases of 63% and 43%, respectively. These results confirm that our approach not only mitigates the limitations of traditional data augmentation but also significantly advances the reliability and precision of crack detection in industrial settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Needle-Like Ferroelastic Domains in Individual Ferroelectric Nanoparticles

Superior structural, physical and electronic properties make ferroelectric nanocrystals essential in enabling a range of next-generation devices. Ferroelectric responses are determined by crystal structure and domain morphology. The ability to reversibly displace, create and annihilate elastic domains is critical to device applications. Whereas electric-field control has been demonstrated for ferroelectric 180° surface domain walls and vortices, similar control of ferroelastic domains and domain boundaries within individual nanocrystals remains challenging. Using controlled external compressive and tensile axial stress, deterministic and reversible control of highly mobile ferroelastic domains and axial polarization in three dimensions is demonstrated in this study. While many studies exist on ferroelastic domains in thin films and bulk, little is known about ferroelastic interactions at the single nanoparticle level, especially involving domain boundaries. Through combining Bragg coherent X-ray diffractive imaging and Landau theory, strain gradients in individual BaTiO3 nanocrystals are shown to stabilize needle-like ferroelastic twin domains. These domains are highly labile under applied axial stress, producing a locally enhanced electric polarization mediated by a ferroelectric phase transition. The efficacy of Bragg coherent X-ray diffractive imaging in studying in operando domains in three-dimensions is demonstrated, while synergy with theory provides a paradigm for domain boundary engineering and potential for nanoscale functional devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A FETI approach to domain decomposition for meshfree discretizations of nonlocal problems

We propose a domain decomposition method for the efficient simulation of nonlocal problems. Our approach is based on a multi-domain formulation of a nonlocal diffusion problem where the subdomains share “nonlocal” interfaces of the size of the nonlocal horizon. This system of nonlocal equations is first rewritten in terms of minimization of a nonlocal energy, then discretized with a meshfree approximation and finally solved via a Lagrange multiplier approach in a way that resembles the finite element tearing and interconnect method. Specifically, we propose a distributed projected gradient algorithm for the solution of the Lagrange multiplier system, whose unknowns determine the nonlocal interface conditions between subdomains. Several two-dimensional numerical tests on problems as large as 191 million unknowns illustrate the strong and the weak scalability of our algorithm, which outperforms the standard approach to the distributed numerical solution of the problem. Finally, this work is the first rigorous numerical study in a two-dimensional multi-domain setting for nonlocal operators with finite horizon and, as such, it is a fundamental step towards increasing the use of nonlocal models in large scale simulations.

42 ENGINEERING↗
DOE OSTI2020

Light-Induced Currents at Domain Walls in Multiferroic BiFeO3.

Multiferroic BiFeO3 (BFO) films with spontaneously formed periodic stripe domains can generate above-gap open circuit voltages under visible light illumination; nevertheless the underlying mechanism behind this intriguing optoelectronic response has not been understood to date. Here, we make contact-free measurements of light-induced currents in epitaxial BFO films via detecting terahertz radiation emanated by these currents, enabling a direct probe of the intrinsic charge separation mechanisms along with quantitative measurements of the current amplitudes and their directions. In the periodic stripe samples, we find that the net photocurrent is dominated by the charge separation across the domain walls, whereas in the monodomain samples the photovoltaic response arises from a bulk shift current associated with the non-centrosymmetry of the crystal. The peak current amplitude driven by the charge separation at the domain walls is found to be 2 orders of magnitude higher than the bulk shift current response, indicating the prominent role of domain walls acting as nanoscale junctions to efficiently separate photogenerated charges in the stripe domain BFO films. These findings show that domain-wall-engineered BFO thin films offer exciting prospects for ferroelectric-based optoelectronics, as well as bias-free strong terahertz emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High Velocity, Low‐Voltage Collective In‐Plane Switching in (100) BaTiO 3 Thin Films

Abstract Ferroelectrics are being increasingly called upon for electronic devices in extreme environments. Device performance and energy efficiency is highly correlated to clock frequency, operational voltage, and resistive loss. To increase performance it is common to engineer ferroelectric domain structure with highly‐correlated electrical and elastic coupling that elicit fast and efficient collective switching. Designing domain structures with advantageous properties is difficult because the mechanisms involved in collective switching are poorly understood and difficult to investigate. Collective switching is a hierarchical process where the nano‐ and mesoscale responses control the macroscopic properties. Using chemical solution synthesis, epitaxially nearly‐relaxed (100) BaTiO 3 films are synthesized. Thermal strain induces a strongly‐correlated domain structure with alternating domains of polarization along the [010] and [001] in‐plane axes and 90° domain walls along the [011] or [01] directions. Simultaneous capacitance–voltage measurements and band‐excitation piezoresponse force microscopy revealed strong collective switching behavior. Using a deep convolutional autoencoder, hierarchical switching is automatically tracked and the switching pathway is identified. The collective switching velocities are calculated to be ≈500 cm s −1 at 5 V (7 kV cm −1 ), orders‐of‐magnitude faster than expected. These combinations of properties are promising for high‐speed tunable dielectrics and low‐voltage ferroelectric memories and logic.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Grey-box and ANN-based building models for multistep-ahead prediction of indoor temperature to implement model predictive control

Model-based predictive control (MPC) strategies for heating, ventilation, and air-conditioning (HVAC) systems present an opportunity to lower building energy consumption and operational costs. Such approaches rely on the development of a model to precisely forecast building thermal dynamics, such as room air temperature or heating/cooling rate, and make control-related decisions. The control-oriented modeling of building energy systems should be accurate in predicting indoor conditions and present low computational complexity. These features are the key challenge of implementing advanced control methods such as MPC. Extant studies on building modeling for MPC have focused on step-ahead forecasting techniques to forecast building thermal dynamics, while multistep-ahead forecasting is essential. Moreover, machine learning model suitable in case of the domain-based engineering expertise are also not available. To this aim, we perform a comparative analysis of the grey-box model based on a resistance-capacitance (RC) thermal network and a machine learning model composed of an artificial neural network (ANN) for multistep-ahead prediction of building thermal dynamics using current and historical data. Actual experimental data obtained from the Flexible Research Platform (FRP) in Oak Ridge National Laboratory (US) are used for estimation and validation purposes. The average root mean squared error (RMSE) of the grey-box and ANN models are 0.89 °C and 1.02°C, respectively. Finally, the results indicate that the grey-box model outperforms the ANN model in the considered validation periods in terms of accuracy and prediction stability.

42 ENGINEERING↗
DOE OSTI2025

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗
DOE OSTI2020

Optogenetic control of protein binding using light-switchable nanobodies

A growing number of optogenetic tools have been developed to reversibly control binding between two engineered protein domains. In contrast, relatively few tools confer lightswitchable binding to a generic target protein of interest. Such a capability would offer substantial advantages, enabling photoswitchable binding to endogenous target proteins in cells or light-based protein purification in vitro. Here, we report the development of optonanobodies (OptoNBs), a versatile class of chimeric photoswitchable proteins whose binding to proteins of interest can be enhanced or inhibited upon blue light illumination. We find that OptoNBs are suitable for a range of applications including reversibly binding to endogenous intracellular targets, modulating signaling pathway activity, and controlling binding to purified protein targets in vitro. This work represents a step towards programmable photoswitchable regulation of a wide variety of target proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Domain-dependent strain and stacking in two-dimensional van der Waals ferroelectrics

Van der Waals (vdW) ferroelectrics have attracted significant attention for their potential in next-generation nano-electronics. Two-dimensional (2D) group-IV monochalcogenides have emerged as a promising candidate due to their strong room temperature in-plane polarization down to a monolayer limit. However, their polarization is strongly coupled with the lattice strain and stacking orders, which impact their electronic properties. Here, we utilize four-dimensional scanning transmission electron microscopy (4D-STEM) to simultaneously probe the in-plane strain and out-of-plane stacking in vdW SnSe. Specifically, we observe large lattice strain up to 4% with a gradient across ~50 nm to compensate lattice mismatch at domain walls, mitigating defects initiation. Additionally, we discover the unusual ferroelectric-to-antiferroelectric domain walls stabilized by vdW force and may lead to anisotropic nonlinear optical responses. Our findings provide a comprehensive understanding of in-plane and out-of-plane structures affecting domain properties in vdW SnSe, laying the foundation for domain wall engineering in vdW ferroelectrics.

42 ENGINEERING↗
DOE OSTI2025

Epitaxial strain tuning of Er 3+ in ferroelectric thin films

Er 3+ color centers are promising candidates for quantum science and technology due to their long electron and nuclear spin coherence times, as well as their desirable emission wavelength. By selecting host materials with suitable, controllable properties, we introduce new parameters that can be used to tailor the Er 3+ emission spectrum. PbTiO 3 is a well-studied ferroelectric material with known methods of engineering different domain configurations through epitaxial strain. By distorting the structure of Er 3+ -doped PbTiO 3 thin films, we can manipulate the crystal fields around the Er 3+ dopant. This is resolved through changes in the Er 3+ resonant fluorescence spectra, tying the optical properties of the defect directly to the domain configurations of the ferroelectic matrix. Additionally, we are able to resolve a second set of peaks for films with in-plane ferroelectric polarization. We hypothesize these results to be due to either the Er 3+ substituting different sites of the PbTiO 3 crystal, differences in charges between the Er 3+ dopant and the original substituent ion, or selection rules. Systematically studying the relationship between the Er 3+ emission and the epitaxial strain of the ferroelectric matrix lays the pathway for future optical studies of spin manipulation by altering ferroelectric order parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Imaging of Electrothermal Filament Formation in a Mott Insulator

Resistive switching—the current- and voltage-induced change of electrical resistance—is at the core of memristive devices, which play an essential role in the emerging field of neuromorphic computing. This study is about resistive switching in a Mott insulator, which undergoes a thermally driven metal-to-insulator transition. Two distinct switching mechanisms are reported for such a system: electric-field-driven resistive switching and electrothermal resistive switching. The latter results from an instability caused by Joule heating. Here, we present the visualization of the reversible resistive switching in a planar V 2 O 3 thin-film device using high-resolution wide-field microscopy in combination with electric transport measurements. We investigate the interaction of the electrothermal instability with the strain-induced spontaneous phase separation in the V 2 O 3 thin film at the Mott transition. The photomicrographs show the formation of a narrow metallic filament with a minimum width ≲500 nm. Although the filament formation and the overall shape of the current-voltage characteristics (IVCs) are typical of an electrothermal breakdown, we also observe atypical effects such as oblique filaments, filament splitting, and hysteretic IVCs with sawtoothlike jumps at high currents in the low-resistance regime. We are able to reproduce the experimental results in a numerical model based on a two-dimensional resistor network. This model demonstrates that resistive switching in this case is indeed electrothermal and that the intrinsic heterogeneity is responsible for the atypical effects. This heterogeneity is strongly influenced by strain, thereby establishing a link between switching dynamics and structural properties.

42 ENGINEERING↗
DOE OSTI2024

AutoCheck: Automatically Identifying Variables for Checkpointing by Data Dependency Analysis

Checkpoint/Restart (C/R) has been widely deployed in numerous HPC systems, Clouds, and industrial data centers, which are typically operated by system engineers. Nevertheless, there is no existing approach that helps system engineers without domain expertise and domain scientists without system fault tolerance knowledge identify those critical variables accounted for correct application execution restoration in a failure for C/R. To address this problem, we propose an analytical model and a tool (AutoCheck) that can automatically identify critical variables to checkpoint for C/R. AutoCheck relies on first, analytically tracking and optimizing data dependency between variables and other application execution state, and second, a set of heuristics that identify critical variables for checkpointing from the refined data dependency graph (DDG). AutoCheck allows programmers to pinpoint critical variables to checkpoint quickly within a few minutes. We evaluate AutoCheck on 13 representative HPC benchmarks, demonstrating that AutoCheck can efficiently identify correct critical variables to checkpoint.

HPC↗