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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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Direct observation of nanoscale dynamics of ferroelectric degradation
Failure of polarization reversal, i.e., ferroelectric degradation, induced by cyclic electric loadings in ferroelectric materials, has been a long-standing challenge that negatively impacts the application of ferroelectrics in devices where reliability is critical. It is generally believed that space charges or injected charges dominate the ferroelectric degradation. However, the physics behind the phenomenon remains unclear. Here, using in-situ biasing transmission electron microscopy, we discover change of charge distribution in thin ferroelectrics during cyclic electric loadings. Charge accumulation at domain walls is the main reason of the formation of c domains, which are less responsive to the applied electric field. The rapid growth of the frozen c domains leads to the ferroelectric degradation. This finding gives insights into the nature of ferroelectric degradation in nanodevices, and reveals the role of the injected charges in polarization reversal.
Multiscale computational understanding and growth of 2D materials: a review
Abstract The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.
Nanoscale Structure and Interfacial Electrochemical Reactivity of Moiré-Engineered Atomic Layers
Here, the electronic properties of atomically thin van der Waals (vdW) materials can be precisely manipulated by vertically stacking them with a controlled offset (for example, a rotational offset─i.e., twist─between the layers, or a small difference in lattice constant) to generate moiré superlattices. In recent years, the application of this “twistronics” concept to interfacial electrochemistry has unveiled unique pathways for tailoring the electrochemical reactivity. Furthermore, this Account provides an overview of our work that leveraged a suite of structural characterization methods, such as interferometric four-dimensional scanning transmission electron microscopy, dark-field transmission electron microscopy, and scanning tunneling microscopy, along with nanoscale electrochemical measurement techniques, namely, scanning electrochemical cell microscopy (SECCM), to uncover and dissect the profound impact of electrode electronic structure, controlled by interlayer twist, on interfacial electron transfer kinetics.
Enhanced polymorph metastability drives glycine nucleation in aqueous salt solutions
Crystal nucleation from aqueous solutions influences countless geological, biochemical, astrophysical, environmental, and materials science–related phenomena, including ice formation, the manufacturing of active pharmaceutical ingredients, development of diseases such as Alzheimer’s and the origin of life itself. Understanding and controlling nucleation is essential for designing materials with specific properties, developing strategies to inhibit or promote crystallization in various contexts and preventing pathological aggregation in neurodegenerative diseases. Similar to the protein structure prediction problem—where a single amino acid sequence can in theory adopt one most stable conformation but in practice may sample multiple competing conformations—crystal nucleation faces a parallel challenge: the same chemical species can form diverse polymorphs under different environmental conditions (e.g., temperature, pressure, solvent). Each polymorph presents its own set of physical and chemical properties, highlighting the importance of understanding and controlling polymorph selection in fields ranging from pharmaceuticals to materials design. Despite advances in experimental and computational methods for studying phase transitions and polymorph stability, nucleation remains challenging due to its nanoscale nature. Furthermore, in practical settings, salts and impurities can further influence crystal nucleation in diverse contexts, from scaling in pipelines and desalination plants to the durability of concrete and the efficiency of battery materials. This can lead to the formation of polymorphs that may differ from the most stable phase in pure solutions. Or, even though the final structure might appear same irrespective of whether the environment contained impurities or not, the mechanism through which it was formed might be completely different and not intuitive.
Realignment and suppression of charge density waves in the rare-earth tritellurides 𝑅Te 3 (𝑅 = La, Gd, Er)
The rare-earth tritellurides have a rich phase diagram that includes charge density waves (CDWs), superconductivity, and magnetic order, offering a platform to study the interplay between these phases on a square-net system. Prior studies have shown that defects can affect the CDW characteristics in these materials, yet coupling between the CDW order and the underlying microstructure has not been studied at the nanoscale. Here we use scanning transmission electron microscopy at cryogenic temperatures to directly visualize the effects of defects on the CDW order and provide a spatially resolved microscopic correlation between the CDW transition and structural defects. Here, we show that in the presence of extended defects, such as dislocations and stacking faults, the weak orthorhombicity of the rare-earth tritellurides is lost and the material becomes pseudotetragonal. Since the orthorhombicity acts as a symmetry breaking field for the CDW transitions in rare-earth tritellurides, the presence of these extended defects modulates the energetics of the CDWs and suppresses the ground-state CDW phase at low temperature.
Improving Strain-localized GaSe Single Photon Emitters with Electrical Doping
Exciton localization through nanoscale strain has been used to create highly efficient single-photon emitters (SPEs) in 2D materials. However, the strong Coulomb interactions between excitons can lead to nonradiative recombination through exciton–exciton annihilation, negatively impacting SPE performance. Here, we investigate the effect of Coulomb interactions on the brightness, single photon purity, and operating temperatures of strain-localized GaSe SPEs by using electrostatic doping. By gating GaSe to the charge neutrality point, the exciton–exciton annihilation nonradiative pathway is suppressed, leading to ∼60% improvement of emission intensity and an enhancement of the single photon purity g (2) (0) from 0.55 to 0.28. The operating temperature also increased from 4.5 K to 85 K consequently. In conclusion, this research provides insight into many-body interactions in excitons confined by nanoscale strain and lays the groundwork for the optimization of SPEs for optoelectronics and quantum photonics.
Understanding Degradation Mechanisms in SrIrO 3 Oxygen Evolution Electrocatalysts: Chemical and Structural Microscopy at the Nanoscale
Designing acid-stable oxygen evolution reaction electrocatalysts is key to developing sustainable energy technologies such as polymer electrolyte membrane electrolyzers but has proven challenging due to the high applied anodic potentials and corrosive electrolyte. This work showcases advanced nanoscale microscopy techniques supported by complementary structural and chemical characterization to develop a fundamental understanding of stability in promising SrIrO 3 thin film electrocatalyst materials. Cross-sectional high-resolution transmission electron microscopy illustrates atomic-scale bulk and surface structure, while secondary ion mass spectrometry imaging using a helium ion microscope provides the nanoscale lateral elemental distribution at the surface. After accelerated degradation tests under anodic potential, the SrIrO 3 film thins and roughens, but the lateral distribution of Sr and Ir remains homogeneous. A layer-wise dissolution mechanism is hypothesized, wherein anodic potential causes the IrO x -rich surface to dissolve and be regenerated by Sr leaching. Finally, the characterization approaches utilized herein and mechanistic insights into SrIrO 3 are translatable to a wide range of catalyst systems.
Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals
Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, in this study, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.
Vortex Matter in Confined Superconductors and Mesoscopic Hybrid Heterostructures. Final report
This program studied the fundamental features that underlie the behavior of hybrid ferromagnet/superconductor heterostructures both in the regime of magnetic coupling and proximity effect. In ferromagnet/superconductor hybrid structures, the source of superconducting correlations and ferromagnetism are spatially separated. Therefore, the interplay between ferromagnetism and superconductivity results in physical effects that are not easily observed in bulk superconductors and allows to tune the local superconducting and vortex properties, realizing, thus, a new class of materials. In the case of proximity effect the ferromagnet and the superconductor are in contact and leakage of superconducting pairs is allowed into the ferromagnetic layer. Typically, the decay length for the superconducting pair correlations in the ferromagnet is of the order of one nanometer due to the typically large ferromagnetic exchange field. However, a suitable magnetic structure in the ferromagnetic material can be used to align the spins of the superconducting pairs allowing much longer penetration of superconductivity in the magnetic material. These superconducting pairs with aligned spins can carry spin and provide the basis for superconducting spintronics devices. In the case of magnetic coupling the effect of a spatial inhomogeneous stray field produced by the ferromagnet substantially modifies the nucleation of the order parameter in the superconducting layer and can lead to a significant change in the local superconducting properties. Therefore, magnetically coupled planar ferromagnet-superconductor hybrid structures offer new avenues for manipulation of the superconductivity at the nanoscale and convenient means to control vortex dynamics.
Elucidating molecular scale interactions underlying the freezing behavior of salt solutions in silica nanopores
Elucidating the influence of nanoscale confinement on the freezing behavior of salt solutions is of fundamental interest to environmental security and materials science and engineering. Specific structural information such as the coordination environment of ions in confined aqueous medium, effects on the extended hexagonal network of water molecules and their mutual non-bonding interactions in confinement are sparse in the literature along with the change in the dynamical characteristics of water in the presence of ions. To address these knowledge gaps, the current study is focused on investigating the influence of reduced dimensionality arising from nanoscale confinement on the structural evolution of salt solutions on freezing and the associated fluid–surface interactions. In this regard, operando wide-angle X-ray scattering (WAXS) measurements and classical molecular dynamics (MD) simulations are conducted with water and 0.5 M CaCl 2 , MgCl 2 and KCl solutions confined in 4 nm sized SBA-15 silica pores upon cooling from 300 K to 200 K. The freezing point of the salt solutions is depressed to 235 K which is about 10 K lower than that of confined water. The translational dynamics of confined salt solutions indicates shifts in the fragile-to-strong dynamical crossover to a lower temperature compared to pure water. The strong electrostatic attraction between the cations and the surrounding water molecules contributes to the freezing point depression in confined salt solutions. These insights unlock the molecular-scale basis and mechanisms underlying the freezing behavior of confined salt solutions.
Investigating Porous Media for Relief Printing Using Micro-Architected Materials
Advances in printed electronics are predicated on the integration of sophisticated printing technologies with functional materials. Although scalable manufacturing methods, such as letterpress and flexographic printing, have significant history in graphic arts printing, functional applications require sophisticated control and understanding of nanoscale transfer of fluid inks. In this paper, a versatile platform is introduced to study and engineer printing forms, exploiting a microscale additive manufacturing process to design micro-architected materials with controllable porosity and deformation. Building on this technology, controlled ink transfer for submicron functional films is demonstrated. The design freedom and high-resolution 3D control afforded by this method provide a rich framework for studying mechanics of fluid transfer for advanced manufacturing processes.
Tuning the Porous Structure in PMMA-Templated Mesoporous MoO 2 for Pseudocapacitive Li-Ion Electrodes
MoO 2 is an exciting candidate for next-generation energy storage. It can be used for fast-charging applications in nanoscale form, but its kinetic performance is often limited by insulating MoO 3 surface oxide layers. Here, we developed methods to produce polymer-templated porous MoO 2 powders where electrical conductivity was well-maintained throughout the structure, even in the presence of some surface oxidation. Porosity, pore size, and crystallite size were controlled by varying the amount and size of the colloidal templates and through calcination temperature. The electrochemical performance was correlated with nanoscale structure: samples with high porosity, medium pore sizes, and good crystallinity display optimal rate capabilities, with over 100 mAh g −1 delivered in 3 min and 93% capacity retention after 1000 cycles. Kinetic studies were performed on samples with the largest and smallest crystallite sizes to understand the charge storage mechanism. In the sample with the smallest crystallite size, 85% of the total stored charge was capacitive, compared to 60% for the largest crystallite size. Sloping voltage profiles in materials with smaller domain sizes further suggest suppression of intercalation-induced phase transitions. This work thus provides insights into the mechanisms of charge storage in nanoscale MoO 2 and design parameters for the production of fast charging materials.
Nanoscale Antiferromagnetic Domain Imaging using Full-Field Resonant X-ray Magnetic Diffraction Microscopy
The physical properties of magnetic materials frequently depend not only on the microscopic spin and electronic structures, but also on the structures of mesoscopic length scales that emerge, for instance, from domain formations, or chemical and/or electronic phase separations. However, experimental access to such mesoscopic structures is currently limited, especially for antiferromagnets with net zero magnetization. Here, full-field microscopy and resonant magnetic X-ray diffraction are combined to visualize antiferromagnetic (AF) domains of the spin–orbit Mott insulator Sr 2 IrO 4 with area over ≈0.1 mm 2 and with spatial resolution as high as ≈150 nm. With the unprecedented wide field of views and high spatial resolution, an intertwining of two AF domains on a length comparable to the measured average AF domain wall width of 545 nm is revealed. This mesoscopic structure comprises a substantial portion of the sample surface, and thus can result in a macroscopic response unexpected from its microscopic magnetic structure. In particular, the symmetry analysis presented in this work shows that the inversion symmetry, which is preserved by the microscopic AF order, becomes ill-defined at the mesoscopic length scale. We report this result underscores the importance of this novel technique for a thorough understanding of the physical properties of antiferromagnets.
Turn‐On of Current‐Induced Spin Torque Upon Non‐collinear Antiferromagnetic Ordering in Delafossite PdCrO 2
We report measurements of the current-induced spin torque produced by the delafossite antiferromagnet PdCrO 2 and acting on an adjacent ferromagnetic permalloy layer. The spin torque increases strongly as the temperature is reduced through the Néel temperature, when the PdCrO 2 transitions from a paramagnetic phase to a noncollinear antiferromagnetic state. This result is qualitatively consistent with density functional theory calculations regarding how spin-current generation changes upon antiferromagnetic ordering in PdCrO 2 .
Evaluating the efficiency of touch-spun scaffolds in producing dense cell cultures for tissue engineering applications
Developing efficient scaffolds for long-term cell cultivation remains a challenge in tissue engineering. Biomimetic approaches aim to create a three-dimensional (3D) extracellular matrix (ECM)-like fiber network with a tunable hierarchical structure to promote sufficient cell attachment, differentiation, and overall viability. Among the fiber fabrication methods documented in the literature, mechanical fiber drawing techniques, such as touch-spinning, have garnered significant research interest. This is due to the simplicity of the equipment, the ability to control fiber diameter and interfiber spacing at the nanoscale without the need for external fields, and the absence of specific requirements for material dielectric properties. Despite the advantages of mechanically drawn scaffolds in biomedical research, the methodologies for cell culturing and analysis for these materials have not been adequately addressed. In this study, we assess the potential of touch-spun scaffolds in promoting NIH/3T3-GFP fibroblast cell growth for tissue engineering applications. Polycaprolactone/polyethylene oxide (PCL/PEO)-based fiber arrays with a controlled interfiber spacing of 91.9 ± 25.0 μm (N = 50) were fabricated using a modified touch-spinning apparatus and then assembled into 2D and 3D scaffolds through additive manufacturing technology. A comparative cell analysis conducted for single- and multi-layered structures showed that the 3D touch-spun scaffolds support healthy growth of up to 6.5 million fibroblast cells within 21 days and offer enhanced cell viability compared to conventional 2D fiber scaffolds, as confirmed by the Presto Blue assay. Furthermore, the metabolic activity of fibroblasts on 3D scaffolds assessed by the MTT test is approximately four times higher than that of the positive control, making the 3D touch-spun materials ideal for long-term cell culture applications.
Improved Capacity Retention of Lithium Ion Batteries under Fast Charge via Metal-Coated Graphite Electrodes
A primary barrier preventing repetitive fast charging of Li-ion batteries is lithium metal plating at the graphite anode. One approach toward mitigating Li metal deposition is the deliberate modification of the graphite anode surface with materials demonstrating high overpotentials unfavorable for Li metal nucleation, such as Ni or Cu nanoscale films. This research explores Ni and Cu surface coatings at different areal loadings (3 or 11 μg cm -2 ) on the electrochemistry of graphite/LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) type Li-ion batteries. Extended galvanostatic cycling of control and metal-coated electrodes in graphite/NMC622 pouch cells are conducted under high rate conditions. Based on the overpotential of Li deposition on metal foil, both Ni and Cu treatments were anticipated to result in reduced lithium deposition. The higher metal film loadings of 11 μg cm -2 Ni- or Cu-coated electrodes exhibit the highest capacity retention after 500 cycles, with mean improvements of 8% and 9%, respectively, over uncoated graphite electrodes. Li plating quantified by X-ray diffraction indicates that the metal films effectively reduce the quantity of plated Li compared to untreated electrodes, with 11 μg cm -2 Cu providing the greatest benefit.
Helium Bubbles and Blistering in a Nanolayered Metal/Hydride Composite
Helium is insoluble in most metals and precipitates out to form nanoscale bubbles when the concentration is greater than 1 at.%, which can alter the material properties. Introducing controlled defects such as multilayer interfaces may offer some level of helium bubble management. This study investigates the effects of multilayered composites on helium behavior in ion-implanted, multilayered ErD 2 /Mo thin film composites. Following in-situ and ex-situ helium implantation, scanning and transmission electron microscopy showed the development of spherical helium bubbles within the matrix, but primarily at the layer interfaces. Bubble linkage and surface blistering is observed after high fluence ex-situ helium implantation. These results show the ability of metallic multilayers to alter helium bubble distributions even in the presence of a hydride layer, increasing the lifetime of materials in helium environments.