Search NASA⌕ Search

SEARCH · Search NASA

Results for “interface properties”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

Dynamic and weak electric double layers in ultrathin nanopores

The unique properties of aqueous electrolytes in ultrathin nanopores have drawn a great deal of attention in a variety of applications, such as power generation, water desalination, and disease diagnosis. Inside the nanopore, at the interface, properties of ions differ from those predicted by the classical ionic layering models (e.g., Gouy–Chapman electric double layer) when the thickness of the nanopore approaches the size of a single atom (e.g., nanopores in a single-layer graphene membrane). Here, using extensive molecular dynamics simulations, the structure and dynamics of aqueous ions inside nanopores are studied for different thicknesses, diameters, and surface charge densities of carbon-based nanopores [ultrathin graphene and finite-thickness carbon nanotubes (CNTs)]. The ion concentration and diffusion coefficient in ultrathin nanopores show no indication of the formation of a Stern layer (an immobile counter-ionic layer) as the counter-ions and nanopore atoms are weakly correlated in time compared to the strong correlation observed in thick nanopores. The weak correlation observed in ultrathin nanopores is indicative of a weak adsorption of counter-ions onto the surface compared to that of thick pores. The vanishing counter-ion adsorption (ion–wall correlation) in ultrathin nanopores leads to several orders of magnitude shorter ionic residence times (picoseconds) compared to the residence times in thick CNTs (seconds). The results of this study will help better understand the structure and dynamics of aqueous ions in ultrathin nanopores.

2D materials↗

Emergent interface vibrational structure of oxide superlattices

As the length scales of materials decrease, the heterogeneities associated with interfaces become almost as important as the surrounding materials. This has led to extensive studies of emergent electronic and magnetic interface properties in superlattices. However, the interfacial vibrations that affect the phonon-mediated properties, such as thermal conductivity, are measured using macroscopic techniques that lack spatial resolution. Although it is accepted that intrinsic phonons change near boundaries, the physical mechanisms and length scales through which interfacial effects influence materials remain unclear. Here we demonstrate the localized vibrational response of interfaces in strontium titanate–calcium titanate superlattices by combining advanced scanning transmission electron microscopy imaging and spectroscopy, density functional theory calculations and ultrafast optical spectroscopy. Structurally diffuse interfaces that bridge the bounding materials are observed and this local structure creates phonon modes that determine the global response of the superlattice once the spacing of the interfaces approaches the phonon spatial extent. Our results provide direct visualization of the progression of the local atomic structure and interface vibrations as they come to determine the vibrational response of an entire superlattice. Direct observation of such local atomic and vibrational phenomena demonstrates that their spatial extent needs to be quantified to understand macroscopic behaviour. Tailoring interfaces, and knowing their local vibrational response, provides a means of pursuing designer solids with emergent infrared and thermal responses.

36 MATERIALS SCIENCE↗

The effects of nanoscale confinement on the behavior of metal laminates

By reducing the layer thickness, h, in metal multilayers from micrometer- to nanometer-levels, scale-dependent transitions in behavior are observed. The role of interface properties in these transitions has been extensively investigated. However, reducing h to the nanoscale regime also imposes a physical geometric confinement on defect-related processes occurring within the layers, an effect that is relatively less explored. Herein, we present illustrative examples of the influence of nanoconfinement on the strength, structure, and radiation response of multilayers. These examples show that nanoconfinement and interface structure and topology act cooperatively in the nanoscale limit, affecting behaviors that cannot be explained based on either factor alone.

36 MATERIALS SCIENCE↗

Degradation behavior of CIGS solar Cells: A parametric analysis

A parametric study of the effect of bulk and interface properties on device characteristics as a function of heat and light stress under open-circuit and short-circuit conditions is developed for Cu(In,Ga)(S,Se) 2 solar cells using SCAPS-1D simulator. The variables and interdependencies modeled include: (1) conduction band offset (CBO) between buffer and absorber; (2) buffer ionized donor density; (3) CIGS shallow acceptor density; (4) CIGS deep acceptor density; (5) CIGS shallow donor density; (6) ionized acceptor concentration in the ordered vacancy compound (OVC) CIGS/buffer interface; and (7) back contact work-function. An increase in absorber shallow acceptor or a decrease in shallow donor density results in an increase in net carrier density and open-circuit voltage (V OC ). Further, a decrease in V OC is observed with an increase in the deep acceptors or neutral midgap defects in the CIGS due to higher charge carrier recombination. A change of CBO from spike to cliff condition is a dominant mechanism of decreasing VOC with an interface defect density of 10 12 cm -2 . The minimum depletion width is found to be specifically sensitive to CBO and interface defect density. An inflection in the capacitance–voltage curves (in reverse bias) is observed with simultaneous increase in bulk deep acceptor density and shallow donor density near the back contact.

14 SOLAR ENERGY↗

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗

Relating Hydro–Mechanical and Elastodynamic Properties of Dynamically Stressed Tensile–Fractured Rock in Relation to Applied Normal Stress, Fracture Aperture, and Contact Area

We exploit nonlinear elastodynamic properties of fractured rock to probe the micro-scale mechanics of fractures and understand the relation between fluid transport and fracture aperture under dynamic stressing. Experiments were conducted on rough, tensile-fractured Westerly granite subject to triaxial stresses. We measure fracture permeability for steady-state fluid flow with deionized water. Pore pressure oscillations are applied at amplitudes ranging from 0.2 to 1 MPa at 1 Hz frequency. During dynamic stressing we transmit ultrasonic signals through the fracture using an array of piezoelectric transducers (PZTs) to monitor evolution of interface properties. We examine the influence of fracture aperture and contact area by conducting measurements at effective normal stresses of 10–20 MPa. Additionally, the evolution of contact area with stress is characterized using pressure sensitive film. These experiments are conducted separately with the same fracture and map contact area at stresses from 9 to 21 MPa. The measurements are a proxy for “true” contact area for the fracture surface and we relate them to elastic properties using the calculated PZT sensor footprints via numerical modeling of Fresnel zones. We compare the elastodynamic response of the fracture using the stress-induced changes in ultrasonic wave velocities for transmitter-receiver pairs to image spatial variations in contact properties. We show that nonlinear elasticity and permeability enhancement decrease with increasing normal stress. Additionally, post-oscillation wave velocity and permeability exhibit quick recoveries toward pre-oscillation values. Estimates of fracture contact area (global and local) demonstrate that the elastodynamic and permeability responses are dominated by fracture topology.

58 GEOSCIENCES↗

Carrier gradients and the role of charge selective contacts in lateral heterojunction all back contact perovskite solar cells

Realizing photovoltaic devices that achieve the full potential of the metal halide perovskite material will require improved insight regarding the role of selective contacts and how key interfaces operate when mobile defects are present. However, measuring interface properties in typical device stacks where the perovskite layer is thin and sandwiched between two contacts has been a challenge. Here, we fabricate p-i-n and p-n lateral heterojunctions with nickel oxide/titanium oxide all back contacts, permitting us to employ a comprehensive analysis approach, including ultraviolet and X-ray photoemission spectroscopy (UPS/XPS), angle-resolved X-ray absorption spectroscopy (XAS), Kelvin probe force microscopy (KPFM), surface photovoltage (SPV), hyperspectral imaging (HSI), and time-resolved fluorescence lifetime imaging microscopy (TR-FLIM) to discern the role of selective contacts. Specifically, we tune the selectivity of the contacts, changing the gradient in the carrier concentration across the surface of the active layer, which is connected to carrier extraction at the buried interface, and thus the device functionality.

25 ENERGY STORAGE↗

Charge Transfer in 2D Halide Perovskites and 2D/3D Heterostructures

Halide perovskites have emerged as a versatile class of materials, with applications spanning photovoltaics, light-emitting diodes, transistors, and photodetectors. The introduction of semiconducting ligands to form two-dimensional (2D) perovskites on the surface of three-dimensional (3D) perovskites in perovskite solar cells has been shown to enhance the performance and stability. To improve the interface properties between the 3D perovskite layer and charge carrier transport layers, understanding the charge transfer (CT) process in 2D perovskites is crucial. In this Perspective, we address common terminological inaccuracies in energy level descriptions, delineate methods for energy alignment characterization, and present practical instances of CT in 2D perovskite-incorporated solar cells. Furthermore, we emphasize the significance of precise terminology, appropriate measurement techniques, and rational design of 2D ligands to harness the full potential of 2D perovskites in optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advances in SnO 2 for Efficient and Stable n-i-p Perovskite Solar Cells

Perovskite solar cells (PSCs) based on the regular n-i-p device architecture have reached above 25% certified efficiency with continuously reported improvements in recent years. A key common factor for these recent breakthroughs is the development of SnO 2 as an effective electron transport layer in these devices. In this review, we discuss the key advances in SnO 2 development, including various deposition approaches and surface treatment strategies, to enhance the bulk and interface properties of SnO 2 for highly efficient and stable n-i-p PSCs. We also discuss the general materials chemistry associated with SnO 2 along with the corresponding materials challenges and improvement strategies, focusing on defects, intrinsic properties, and impact on device characteristics. Finally, we highlight some SnO2 implementations related to scalable processes and flexible devices, and we also provide our perspective on the future development of efficient and stable large-scale perovskite solar modules.

14 SOLAR ENERGY↗

Optical Diagnostics of Discharges in and in Contact With Liquids

Discharges in liquids have been the subject of intensive investigations for a broad range of applications and involve highly coupled and complex phenomena with timescales ranging from picoseconds to seconds and length scales from micrometers to centimeters. This review focuses on some of the challenges in optical diagnostics of discharges in and in contact with liquids; this includes the interpretation of optical emission spectra, the inherently stochastic nature of many discharge phenomena including the initial stages of plasma ignition, and the large gradients in species and plasma properties interfacing with a dynamic liquid interface. We report recent notable advances, controversies in interpretations of diagnostics, and remaining opportunities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Model of Grain Boundary Complexion Transitions and Grain Growth in Yttria-Doped Alumina

In this work, we present a physically-parameterized microstructure evolution model for the Yttria-doped alumina system. Yttria-doped alumina is a well-known ceramic system which undergoes first-order phase-like transitions at grain boundaries, which can radically alter interface properties. The change in interfacial properties in turn can radically change microstructure outcomes during processing, including the induction of abnormal grain growth modes. In this work, we develop a simulation that evolves alumina microstructure as a function of yttria concentration and temperature. In the window studied, we achieve strong agreement with reviewed experimental results in identifying the windows for large grains, small grains, abnormal grain growth, and complexion transition kinetics. We then apply the model to study and demonstrate how the possible inclusion of second-phase particles or uneven solute distribution profiles will impact microstructure evolution. It is found that particles do not significantly affect abnormal grain growth in the window studied (but do lead to reduced grain size through pinning effects). It is found that even modest amounts of solute inhomogeneity will result in substantial changes in microstructure outcomes, frequently leading to clusters of abnormal grains. This model largely corroborates the expectations and hypotheses made from recent experimental studies in oxide-doped alumina systems. Further, it is found that there exists a peak transition fraction for the system at which abnormal grain size tends to be maximized.

Grain Growth, Grain Boundary Complexion, abnormal ↗

Advances and perspectives on mass transfer and enzymatic hydrolysis in the enzyme-mediated lignocellulosic biorefinery: A review

We report enzymatic hydrolysis is a critical process for the cellulase-mediated lignocellulosic biorefinery to produce sugar syrups that can be converted into a whole range of biofuels and biochemicals. Such a process operating at high-solid loadings (i.e., scarcely any free water or roughly ≥ 15% solids, w/w) is considered more economically feasible, as it can generate a high sugar concentration at low operation and capital costs. However, this approach remains restricted and incurs “high-solid effects”, ultimately causing the lower hydrolysis yields with increasing solid loadings. The lack of available water leads to a highly viscous system with impaired mixing that exhibits strong transfer resistance and reaction limitation imposed on enzyme action. Evidently, high-solid enzymatic hydrolysis involves multi-scale mass transfer and multi-phase enzyme reaction, and thus requires a synergistic perspective of transfer and biotransformation to assess the interactions among water, biomass components, and cellulase enzymes. Porous particle characteristics of biomass and its interface properties determine the water form and distribution state surrounding the particles, which are summarized in this review aiming to identify the water-driven multi-scale/multi-phase bioprocesses. Further aided by the cognition of rheological behavior of biomass slurry, solute transfer theories, and enzyme kinetics, the coupling effects of flow-transfer-reaction are revealed under high-solid conditions. Based on the above basic features, this review lucidly explains the causes of high-solid hydrolysis hindrances, highlights the mismatched issues between transfer and reaction, and more importantly, presents the advanced strategies for transfer and reaction enhancements from the viewpoint of process optimization, reactor design, as well as enzyme/auxiliary additive customization.

45 multi-scale, multi-phase, enzymatic reaction↗

Fission gas retention of densely packed uranium carbonitride tristructural-isotropic fuel particles in a 3D printed SiC matrix

The Transformational Challenge Reactor (TCR) fuel form was designed to contain large, densely packed uranium carbonitride (UCN) tristructural-isotropic (TRISO) fuel particles within a 3D printed SiC matrix, increasing the uranium density compared to conventional TRISO fuel forms and offering full geometric freedom for core design. Here, this work summarizes initial low-burnup, high-power irradiation testing of TCR fuel materials, including loose UCN TRISO particles and integral fuel compacts with ~55% TRISO particles by volume, to evaluate fission gas retention. Fission gasses were fully retained in all loose particle tests and in integral compacts irradiated at low (<250 °C) surface temperatures. Initial testing at higher (~700–750 °C) fuel surface temperatures showed fission gas release (FGR) and complete fracture of three compacts, but no FGR was observed in later high temperature tests (~300–750 °C) of both fueled compacts and loose TRISO particles. Calculated thermal stresses in the failed compacts were far less than the measured strength of the SiC matrix and the stresses in some failed compacts were less than those in compacts that did not show FGR. Thermal stress-induced matrix cracks also would not cause complete fracture because the tensile stresses transition to compression in the higher temperature regions. Therefore, fuel failure was likely not caused by thermal stresses and may have been related to leakage currents from the electrical heaters and erratic fuel surface temperatures that were only observed in the test for which failure was observed. In any case, the matrix cracks propagated through the coatings of TRISO particles located in the high-density matrix regions on the peripheries of the compacts, resulting in measurable fission gas release. The discussion focuses on the importance of understanding matrix density distributions and the particle-matrix interface properties to prevent matrix cracks from causing TRISO particle failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Atomic-Scale Andreev Probe of Unconventional Superconductivity

Recent emergence of low-dimensional unconventional superconductors and their exotic interface properties calls for new approaches to probe the pairing symmetry, a fundamental and frequently elusive property of the superconducting condensate. Here, we introduce the unique capability of tunneling Andreev reflection (TAR) to probe unconventional pairing symmetry, utilizing the sensitivity of this technique to specific Andreev reflections. Specifically, suppression of the lowest-order Andreev reflection due to quantum interference but emergence of the higher-order Andreev processes provides direct evidence of the sign-changing order parameter in the paradigmatic FeSe superconductor. Furthermore, TAR spectroscopy also reveals two superconducting gaps, points to a possibility of a nodal gap structure, and directly confirms that superconductivity is locally suppressed along the nematic twin boundary, with preferential and near-complete suppression of the larger energy gap. Furthermore, our findings therefore enable new, atomic-scale insight into microscopic, inhomogeneous, and interfacial properties of emerging quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Molecular Diradical Spin Qubits in a Crystalline Host as a Platform for Quantum Sensing

Doping a luminescent tris(2,4,6-trichlorophenyl)methyl diradical m (TTM) 2 into a host crystal of its diamagnetic precursor m (HTTM) 2 creates a molecular color center with enhanced optical-spin interface properties important for quantum sensing. Optical polarization of the |T 0 ⟩ sublevel of the diradical triplet ground state is achieved by spin-selective intersystem crossing from the |T + ⟩ and |T – ⟩ sublevels of the triplet excited state at ambient and cryogenic temperatures. Coherent spin control of m (TTM) 2 doped into m (HTTM) 2 using pulsed optically detected magnetic resonance (ODMR) spectroscopy results in a 10-fold improvement in ODMR contrast over that observed for randomly oriented m (TTM)2 using continuous-wave ODMR. The diradical doped crystal powders achieve spin coherence times of 2.8, 3.4, and 7.4 μs at 294, 85, and 5 K, respectively. The diradical photoluminescence is sensitive to weak applied magnetic fields independent of temperature, excitation wavelength, and dopant concentration, providing a promising pathway toward robust quantum sensing of anisotropic magnetic fields under ambient conditions.

crystal structure↗

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗