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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Platinum Graphene Catalytic Condenser for Millisecond Programmable Metal Surfaces

Accelerating catalytic chemistry and tuning surface reactions require precise control of the electron density of metal atoms. In this work, nanoclusters of platinum were supported on a graphene sheet within a catalytic condenser device that facilitated electron or hole accumulation in the platinum active sites with negative or positive applied potential, respectively. The catalytic condenser was fabricated by depositing on top of a p-type Si wafer an amorphous HfO 2 dielectric (70 nm), on which was placed the active layer of 2–4 nm platinum nanoclusters on graphene. A potential of ±6 V applied to the Pt/graphene layer relative to the silicon electrode moved electrons into or out of the active sites of Pt, attaining charge densities more than 1% of an electron or hole per surface Pt atom. At a level of charge condensation of ±10% of an electron per surface atom, the binding energy of carbon monoxide to a Pt(111) surface was computed via density functional theory to change 24 kJ mol –1 (0.25 eV), which was consistent with the range of carbon monoxide binding energies determined from temperature-programmed desorption (ΔBE CO of 20 ± 1 kJ mol –1 or 0.19 eV) and equilibrium surface coverage measurements (ΔBE CO of 14 ± 1 kJ mol –1 or 0.14 eV). Impedance spectroscopy indicated that Pt/graphene condensers with potentials oscillating at 3000 Hz exhibited negligible loss in capacitance and charge accumulation, enabling programmable surface conditions at amplitudes and frequencies necessary to achieve catalytic resonance.

Inorganic carbon compounds↗
DOE OSTI2021

Hybrid gels via bulk interfacial complexation of supramolecular polymers and polyelectrolytes

Hierarchical self-assembly leading to organized supramolecular structures across multiple length scales has been of great recent interest. Earlier work from our laboratory reported the complexation of peptide amphiphile (PA) supramolecular polymers with oppositely charged polyelectrolytes into a single solid membrane at a macroscopic interface. We report here the formation of bulk gels with many internal interfaces between the covalent and supramolecular polymer components formed by the rapid chaotic mixing of solutions, one containing negatively charged PA nanofibers and the other the positively charged biopolymer chitosan. We found that formation of a contact layer at the interface of the solutions locks the formation of hydrogels with lamellar microstructure. The nanofiber morphology of the supramolecular polymer is essential to this process since gels do not form when solutions of supramolecular assemblies form spherical micelles. Here, we found that rheological properties of the gels can be tuned by changing the relative amounts of each component. Furthermore, both positively and negatively charged proteins are easily encapsulated within the contact layer of the gel, which provides an interesting biomedical function for these systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Design of 3D Oxide–Metal Hybrid Metamaterial for Tailorable Light–Matter Interactions in Visible and Near-Infrared Region

Dielectric–metallic hybrid metamaterials exhibit extraordinary optical properties due to the light–matter interactions at the dielectric–metallic interfaces. The ability in precision control of the light–matter interactions in nanoscale is key to tailor the optical properties of hybrid metamaterials. In this work, a complex 3D framework of multilayered self-assembled BaTiO 3 (BTO)-Au hybrid thin films is demonstrated with such precision control of the light–matter interaction in nanoscale. Here, unique “bamboo-like” Au nanostructures are formed via the bilayer and trilayer stacking of BTO-Au hybrid layers with interlayers of SrTiO 3 , CeO 2 , or MgO. Different film strain states introduced by the three interlayers result in variable diameter and density of Au nanopillars. Both simulated and experimental optical data demonstrate the localized surface plasmon resonance change and hyperbolic dispersion wavelength shift in visible to near-infrared because of the effective tuning of the Au nanopillar aspect ratio and free electron density. The highly tunable optical properties along with the ferroelectric behavior and thermal robustness of the 3D hybrid film enable it to be a great candidate for multifunctional applications. This study demonstrates a unique 3D approach for precision optical property tuning and combined functionalities in oxide–metal metamaterial systems toward future integrated photonic and electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tunable noninteracting free-energy density functionals for high-energy-density physics applications

In this work, we introduce the concept of a tunable noninteracting free-energy density functional and present two examples realized: (i) via a simple one-parameter convex combination of two existing functionals and (ii) via the construction of a generalized gradient approximation (GGA) enhancement factor that contains one free parameter and is designed to satisfy a set of incorporated constraints. Functional (i), constructed as a combination of the local Thomas–Fermi and a pseudopotential-adapted GGA for the noninteracting free-energy, has already demonstrated its practical usability for establishing the high temperature end of the equation of state of deuterium [Phys. Rev. B 104, 144104 (2021)] and CHON resin [Phys. Rev. E 106, 045207 (2022)] for inertial confinement fusion applications. Hugoniot calculations for liquid deuterium are given as another example of how the application of computationally efficient orbital-free density functional theory (OF-DFT) can be utilized with the employment of the developed functionals. Once the functionals have been tuned such that the OF-DFT Hugoniot calculation matches the Kohn–Sham solution at some low-temperature point, agreement with the reference Kohn–Sham results for the rest of the high temperature Hugoniot path is very good with relative errors for compression and pressure on the order of 2% or less.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switching and phase transition mechanisms. However, identification of these mechanisms from observational data sets has remained a problem due to a large variety of possible configurations, many of which are degenerate. Here, an approach based on a combination of deep learning-based semantic segmentation, rotationally invariant variational autoencoder (VAE), and non-negative matrix factorization to enable learning of a latent space representation of the data with multiple real-space rotationally equivalent variants mapped to the same latent space descriptors is introduced. By varying the size of training sub-images in the VAE, the degree of complexity in the structural descriptors is tuned from simple domain wall detection to the identification of switching pathways. Importantly, this yields a powerful tool for the exploration of the dynamic data in mesoscopic electron, scanning probe, optical, and chemical imaging. Moreover, this work adds to the growing body of knowledge of incorporating physical constraints into the machine and deep-learning methods to improve learned descriptors of physical phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurements of elastoresistance under pressure by combining in-situ tunable quasi-uniaxial stress with hydrostatic pressure

Uniaxial stress, as well as hydrostatic pressure are often used to tune material properties in condensed matter physics. Here, we present a setup which allows for the study of the combined effects of quasi-uniaxial stress and hydrostatic pressure. Following earlier designs for measurements under finite stress at ambient pressure (e.g., Chu et al., Science 337, 710 (2012)), the present setup utilizes a piezoelectric actuator to change stress in situ inside the piston-cylinder pressure cell. We show that the actuator can be operated over the full temperature (from 30 K up to 260 K) and pressure range (up to ≈ 2 GPa), resulting in a clear and measurable quasi-uniaxial strain. To demonstrate functionality, measurements of the elastoresistance (i.e., the change of resistance of a sample as a response to quasi-uniaxial strain) under finite hydrostatic pressure on the iron-based compound BaFe 2 As 2 are presented as a proof-of-principle example, and discussed in the framework of electronic nematicity. Overall, this work introduces the combination of in situ tunable quasi-uniaxial stress and large (up to ≈ 2 GPa) hydrostatic pressure as a powerful combination in the study of novel electronic phases. In addition, it also points towards further technical advancements which can be made in the future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Octahedral rotations in Ruddlesden-Popper layered oxides under pressure from first principles

The combination of reduced dimensionality and tunable structural distortions in layered perovskite oxides makes these materials ideal platforms for designing novel properties and functionalities. One example is hybrid improper ferroelectricity in n = 2 Ruddlesden-Popper oxides, where the combination of a layered crystal structure and rotations of the metal-oxide octahedra break symmetry and induce a polarization. Precisely controlling the octahedral rotation distortions, for example by the application of hydrostatic pressure, provides a pathway to tune and optimize the properties of these materials. Here we combine group theoretic methods, density functional theory calculations, and Landau theory analysis to investigate how octahedral rotations respond to pressure in the hybrid improper ferroelectrics Sr 3 Zr 2 O 7 , Ca 3 Ti 2 O 7 , and Sr 3 Sn 2 O 7 . We find that factors that are known to control the pressure response of ABO 3 perovskites—the formal charge of the A- and B-site cations, tolerance factor, and B-site chemistry—also impact the pressure response of these layered perovskites. We also show that coupling between the octahedral rotation and strain order parameters plays a key role in determining the overall pressure response. Despite some similarities, we find that these layered perovskites display a distinct pressure response compared to their ABO 3 perovskite analogs. By identifying trends and underlying mechanisms that control octahedral rotations in Ruddlesden-Popper oxides under pressure, this work lays the foundation for tailoring the structure and properties of these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Mapping the Interfacial Chemistry and Structure of Partially Fluorinated Bottlebrush Polymers and Their Linear Analogues

Polymer interfaces are key to a range of applications including membranes for chemical separations, hydrophobic coatings, and passivating layers for antifouling. While important, challenges remain in probing the interfacial monolayer where the molecular ordering and orientation can change depending on the chemical makeup or processing conditions. In this work, we leverage surface specific vibrational sum frequency generation (SFG) and the associated dependence on molecular symmetry to elucidate the ordering and orientations of key functional groups for poly(2,2,2-trifluoroethyl methacrylate) bottlebrush polymers and their linear polymer analogues. These measurements were framed by atomistic molecular dynamic simulations to provide a complementary physical picture of the gas–polymer interface. Simulations and SFG measurements show that methacrylate backbones are buried beneath a layer of trifluoroethyl containing side groups that result in structurally similar interfaces regardless of the polymer molecular weight or architecture. The average orientational angles of the trifluoroethyl containing side groups differ depending on polymer linear and bottlebrush architectures, suggesting that the surface groups can reorient via available rotational degrees of freedom. Results show that the surfaces of the bottlebrush and linear polymer samples do not strongly depend on molecular weight or architecture. As such, one cannot rely on increasing the molecular weight or altering the architecture to tune surface properties. This insight into the polymer interfacial structure is expected to advance the design of new material interfaces with tailored chemical/functional properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Interlayer Triplet-Sensitized Luminescence in Layered Two-Dimensional Hybrid Metal-Halide Perovskites

In this work, we review an emerging class of 2D layered metal-halide perovskites that exhibit important photophysical behavior involving inorganic exciton-to-molecular triplet energy flow. These novel systems have potential to impact several energy-related fields and processes, including optoelectronics, photon upconversion strategies, and triplet-based photocatalysis. Early studies provided initial guidance and revealed several intriguing questions that more recent developments, in terms of both expanded and diversified compositional tuning and more sophisticated characterization, have begun to answer. These questions center around the delicate interplay between physical and electronic structure that is perturbed by choice of perovskite structural motif and organic spacer properties. In addition to their distinct natures, the energy offsets between the metal-halide and molecular excitons can be leveraged for a variety of unique effects and emergent properties, including fast interlayer energy transfer. We review the key advances with an eye toward strategies for controlling photophysical outcomes based on structure-energy-function relationships.

14 SOLAR ENERGY↗
DOE OSTI2019

PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design

The ever increasing computational cost of Deep Neural Networks (DNN) and the demand for energy efficient hardware for DNN acceleration has made accuracy and hardware cost co-optimization for DNNs tremendously important, especially for edge devices. Owing to the large parameter space and cost of evaluating each parameter in the search space, manually tuning of DNN hyperparameters is impractical. Automatic joint DNN and hardware hyperparameter optimization is indispensable for such problems. Bayesian optimization-based approaches have shown promising results for hyperparameter optimization of DNNs. However, most of these techniques have been developed without considering the underlying hardware, thereby leading to inefficient designs. Further, the few works that perform joint optimization are not generalizable and mainly focus on CMOS-based architectures. In this work, we present a novel pseudo agent-based multiobjective hyperparameter optimization (PABO) for maximizing the DNN performance while obtaining low hardware cost. Compared to the existing methods, our work poses a theoretically different approach for joint optimization of accuracy and hardware cost and focuses on memristive crossbar based accelerators. PABO uses a supervisor agent to establish connections between the posterior Gaussian distribution models of network accuracy and hardware cost requirements. The agent reduces the mathematical complexity of the co-optimization problem by removing unnecessary computations and updates of acquisition functions, thereby achieving significant speed-ups for the optimization procedure. PABO outputs a Pareto frontier that underscores the trade-offs between designing high-accuracy and hardware efficiency. Our results demonstrate a superior performance compared to the state-of-the-art methods both in terms of accuracy and computational speed (~100x speed up).

Parsa, Maryam↗
DOE OSTI2023

Organocatalysis in ring opening copolymerization as a means of tailoring molecular weight dispersity and the subsequent impact on physical properties in 4D printable photopolymers

Vat photopolymerization 3D printing has traditionally relied on free radical crosslinking between alkenes to produce non-degradable parts, which may have limited use in the biomedical and clinical spaces. Photopolymer resins containing functionalized degradable polymers, specifically polyesters, are greatly interesting for 3D printing tissue scaffolds and medical devices. Unfortunately, most polyesters produced for these applications have been made using metal-containing catalysts, which are not without risk for medical applications. Organocatalysis is a viable alternative route to achieving the same types of polyesters. Here, ring opening copolymerization (ROCOP) of allyl and cyclohexene-containing polyesters is examined using bipyridine and a guanidine-containing catalyst. The role of the catalysts, initiators, and cocatalysts are examined for bulk, open air ROCOP reactions. Unlike previous efforts with organocatalysis, the examined catalysts here could be used to tailor the dispersity of the polyesters, with ~10 kDa polyesters with dispersity ranging from 1.3 to 2.5 examined for the impact on rheological and thermomechanical properties related to resin/part behavior. The bipyridine catalysts and a thiourea cocatalyst further are shown, through the introduction of new fluorescence emissions of the purified polyesters. As a result, this work demonstrates that tuning the dispersity of polyester photopolymers provides a direct method of tailoring physical and optical properties in 3D/4D printable materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Autonomous Output‐Oriented Aerosol Jet Printing Enabled by Hybrid Machine Learning

Additive manufacturing (AM) is rapidly revolutionizing modern manufacturing with recent progress in advanced printing methods and improved properties of printed materials. However, traditional AM methods are limited by their input‐oriented nature, which demands tedious trial‐and‐error tuning of printing parameters to achieve desired output properties. Here, in this work, an output‐oriented artificial intelligence‐integrated AM (AIAM) method is reported that enables an user to specify desired output properties while the printer autonomously discovers the optimal input printing parameters by integrating hybrid machine learning models and in situ measurements. Based on a predictive mapping between the input printing parameters and the output properties of interests established with <20 experiments designed by active learning, inverse design tasks are performed to intelligently generate the printing parameter settings that lead to desired outcomes using reinforcement learning. This method is demonstrated by autonomous aerosol jet printing (AJP) of conductive polymer films and achieving user‐defined electrical resistances with an ultralow error of 3.7%. The AIAM method, with its output‐oriented nature, holds the potential to significantly improve the autonomy, predictability, efficiency, and accessibility of the AM processes, which will unlock new possibilities in the autonomous and intelligent printing of a broad range of functional materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tailoring Local Chemical Ordering via Elemental Tuning in High-Entropy Alloys

Due to the large multi-elemental space desired for property screening and optimization, high-entropy alloys (HEAs) hold greater potential over conventional alloys for a range of applications, such as structural materials, energy conversion, and catalysis. However, the relationship between the HEA composition and its local structural/elemental configuration is not well understood, particularly in noble-metal-based HEA nanomaterials, hindering the design and development of nano-HEAs in energy conversion and catalysis applications. In this work, we determined precise atomic-level structural and elemental arrangements in model HEAs composed of RhPtPdFeCo and RuPtPdFeCo to unveil their local characteristics. Notably, by changing just one constituent element in the HEA (Rh to Ru), we found dramatic changes in the elemental arrangement from complete random mixing to a local single elemental ordering feature. Additionally, we demonstrate that the local ordering in RuPtPdFeCo can be further controlled by varying the Ru concentration, allowing us to toggle between local Ru clustering and distinct heterostructures in multicomponent systems. Overall, our study presents a practical approach for manipulating local atomic structures and elemental arrangements in noble-metal-based HEA systems, which could provide in-depth knowledge to mechanistically understand the functionality of noble-metal-based HEA nanomaterials in practical applications.

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

Elucidating ion capture and transport mechanisms of Preyssler anions in aqueous solutions using biased MACE-accelerated MD simulations

Equilibrium and biased multi-atomic cluster expansion (MACE) accelerated molecular dynamics (MD) simulations in aqueous solutions are performed to investigate the ion capture and transport mechanisms of the {P 5 W 30 } Preyssler anion (PA) as the smallest representative member of the extended polyoxometalate (POM) family with an internal cavity. The unique interatomic interactions present in the internal cavity vs the exterior of PA are carefully investigated using equilibrium MACE MD simulations for two representative Na(H 2 O)@PA and Na@PA complexes in aqueous solutions. Our careful analyses of radial distribution functions and coordination numbers show that the presence of confined water in Na(H 2 O)@PA has profound modulating effects on the nature of the interactions of the encapsulated ion with the oxygens of the PA cavity. Using well-converged MACE-accelerated multiple walker well-tempered metadynamics simulations with nanosecond timescales, two different associative (ion exchange) and dissociative (ion ejection) ion transport mechanisms were carefully investigated for Na + as one of the most abundant and representative ions present in seawater and saline solutions. By comparing systems with and without confined water, it was found that the presence of only one pre-encapsulated confined water in Na(H 2 O)@PA dramatically changes the free energy landscape of ion transport processes. It was also found that the contraction and dilation of the two windows present in PA directly influence the Na + and H 2 O transport. Furthermore, the results from this work are helpful, as they show a viable path toward tuning the ion exchange and transport phenomena in aqueous solutions of POM molecular clusters and frameworks.

25 ENERGY STORAGE↗
DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Photochemistry of Hypervalent Iodoazide Derivatives

The photochemical properties and reaction mechanisms of a series of hypervalent iodoazide compounds (R–IN3) were investigated, with substituents (−CH 3 , −H, −CF 3 ) tuning the electronic density of the phenyl ring. With the help of UV irradiation, ultrafast time-resolved spectroscopy, and density functional theory (DFT) calculations, we elucidated the mechanisms of azide radical (N 3 • ) release and its subsequent reactivity. UV–vis spectroscopy reveals that the photoconversion rates follow the trend CH3 > H > CF3, aligning with DFT-calculated ΔG values for ring-opening transitions. Homolytic cleavage of the I–N bond is identified as the dominant pathway for N3• generation upon UV irradiation, occurring within 400 fs. The released azide radicals react with the solvent molecules, while the iodo radical R–I C • fragments undergo a thermodynamically uphill lactone ring-opening (RO) reaction and subsequent hydrogen atom abstraction from the solvent to form carboxylic acids R–I–COOH, as validated by NMR and IR spectroscopy. The study also highlights the role of substituents in influencing reaction kinetics and intermediate stability, with electron-donating groups accelerating the release of the N 3 • species. This work bridges experimental observations with computational predictions, offering a foundation for future advancements in azide-based reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Multicomponent and Multiphase Lipid Nanotubes Formed by Gliding Microtubule-Kinesin Motility and Phase-Separated Giant Unilamellar Vesicles

Cytoskeletal filaments and motor proteins are critical components in the transport and reorganization of membrane-based organelles in eukaryotic cells. Previous studies have recapitulated the microtubule-kinesin transport system in vitro to dynamically assemble large-scale nanotube networks from multilamellar liposomes and polymersomes. Moving toward more biologically relevant systems, this work examines whether lipid nanotube (LNT) networks can be generated from giant unilamellar vesicles (GUVs) and subsequently characterizes how the lipid composition may be tuned to alter the dynamics, structure, and fluidity of networks. Here, we describe a two-step process in which microtubule motility (i) drives the transport and aggregation of GUVs to form structures with a decreased energy barrier for LNT formation and (ii) extrudes LNTs without destroying parent GUVs, allowing for the formation of large LNT networks. We further show that the lipid composition of the GUV influences formation and morphology of the extruded LNTs and associated networks. For example, LNTs formed from phase-separated GUVs (e.g., liquid–solid phase-separated and coexisting liquid-ordered and liquid-disordered phase-separated) display morphologies related to the specific phase behavior reflective of the parent GUVs. Overall, the ability to form nanotubes from compositionally complex vesicles opens the door to generating lipid networks that more closely mimic the structure and function of those found in cellular systems.

59 BASIC BIOLOGICAL SCIENCES↗