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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method

Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.

bundle method↗
DOE OSTI2022

Local imaging of diamagnetism in proximity-coupled niobium nanoisland arrays on gold thin films.

In this work, we study the effect of engineered disorder on the local magnetic response of proximity-coupled superconducting island arrays by comparing scanning superconducting quantum interference device (SQUID) susceptibility measurements to a model in which we treat the system as a network of one-dimensional (1D) superconductor-normal-metal-superconductor Josephson junctions, each with a Josephson coupling energy E-J determined by the junction length or distance between islands. We find that the disordered arrays exhibit a spatially inhomogeneous diamagnetic response which, for low local applied magnetic fields, is well described by this junction network model, and we discuss these results as they relate to inhomogeneous 2D superconductors. Our model of the static magnetic response of the arrays does not fully capture the onset of nonlinearity and dissipation with increasing applied field, as these effects are associated with vortex motion due to the dynamic nature of the scanning SQUID susceptometry measurement. This work demonstrates a model 2D superconducting system with engineered disorder, and it highlights the impact of dissipation on the local magnetic properties of 2D superconductors and Josephson junction arrays.

Bishop-Van Horn, Logan↗
DOE OSTI2026

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗
DOE OSTI2020

Proximity Spin–Orbit Torque on a Two-Dimensional Magnet within van der Waals Heterostructure: Current-Driven Antiferromagnet-to-Ferromagnet Reversible Nonequilibrium Phase Transition in Bilayer CrI 3

The recently discovered two-dimensional magnetic insulator CrI 3 is an intriguing case for basic research and spintronic applications since it is a ferromagnet in the bulk but an antiferromagnet in bilayer form, with its magnetic ordering amenable to external manipulations. Using the first-principles quantum transport approach, we predict that injecting unpolarized charge current parallel to the interface of the bilayer-CrI 3 /monolayer-TaSe 2 van der Waals (vdW) heterostructure will induce spin–orbit torque and thereby drive the dynamics of magnetization on the first monolayer of CrI 3 in direct contact with TaSe 2 . By combining the calculated complex angular dependence of spin–orbit torque with the Landau-Lifshitz-Gilbert equation for classical dynamics of magnetization, we demonstrate that current pulses can switch the direction of magnetization on the first monolayer to become parallel to that of the second monolayer, thereby converting CrI 3 from antiferromagnet to ferromagnet while not requiring any external magnetic field. We explain the mechanism of this reversible current-driven nonequilibrium phase transition by showing that first monolayer of CrI 3 carries current due to evanescent wave functions injected by metallic transition metal dichalcogenide TaSe 2 , while concurrently acquiring strong spin–orbit coupling via such a proximity effect, whereas the second monolayer of CrI 3 remains insulating. Furthermore, the transition can be detected by passing vertical read current through the vdW heterostructure, encapsulated by a bilayer of hexagonal boron nitride and sandwiched between graphite electrodes, where we find a tunneling magnetoresistance of ≃240%.

2D magnetic materials↗
DOE OSTI2020

A proximity‐based image‐processing algorithm for colloid assignment in segmented multiphase flow datasets

Summary Colloidal transport and deposition are of both environmental and engineering importance. Easier access to x‐ray microtomography (XMT) coupled with improved imaging resolution has made XMT a unique and viable tool for visualizing and quantifying these processes. Currently, there is scant information in the literature addressing colloid segmentation and analysis in saturated and unsaturated porous media, in particular related to spatial partitioning of colloids. To support this need, an approach to assign segmented colloidal particles and aggregates to different partitioning classes based on their proximity to different phases is presented here. The method uses different markers for each attachment site (e.g. wetting‐nonwetting phase interfaces). An example XMT dataset from a drainage experiment is used to demonstrate the efficacy of the image processing algorithms. Flow conditions, and fluid and colloid properties, can thus be compared to the behaviour of colloids within the porous medium. This algorithm can help elucidate colloidal deposition mechanisms and the importance of different attachment sites, explore the importance of fluid properties, as well as the arrangement and shape of the colloids.

BRUECK, C. L.↗
DOE OSTI2025

Thermodynamic Theory of Proximity Ferroelectricity

Proximity ferroelectricity has recently been reported as a new design paradigm for inducing ferroelectricity, where a nonferroelectric polar material becomes a ferroelectric one by interfacing with a thin ferroelectric layer. Strongly polar materials, such as AlN and ZnO, which were previously unswitchable with an external field below their dielectric breakdown fields, can now be switched with practical coercive fields when they are in intimate proximity to a switchable ferroelectric. Here, we develop a general Landau-Ginzburg theory of proximity ferroelectricity in multilayers of nonferroelectrics and ferroelectrics to analyze their switchability and coercive fields. The theory predicts regimes of both “proximity switching,” where the multilayers collectively switch, and “proximity suppression,” where they collectively do not switch. The mechanism of the proximity ferroelectricity is an internal electric field determined by the polarization of the layers and their relative thickness in a self-consistent manner that renormalizes the double-well ferroelectric potential to lower the steepness of the switching barrier. Further reduction in the coercive field emerges from charged defects in the bulk that act as nucleation centers. The application of the theory to proximity ferroelectricity in Al x−1⁢ Sc x ⁢N/AlN and Zn 1−x ⁢Mg x ⁢O/ZnO bilayers is demonstrated. The theory further predicts that dielectric-ferroelectric and paraelectric-ferroelectric multilayers can potentially lead to induced ferroelectricity in the dielectric or paraelectric layers, resulting in the entire stack being switched, an exciting avenue for new discoveries. This thawing of “frozen ferroelectrics,” paraelectrics, and potentially dielectrics with high dielectric constants promises a large class of new ferroelectrics with exciting prospects for previously unrealizable domain-patterned optoelectronic and memory technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Suppressing proximity effects during rapid serial two-photon lithography through tuning of reaction–diffusion kinetics

The ability of two-photon lithography (TPL) to print deterministic nanoporous 3D structures is highly valuable for many applications. However, it is challenging to print such structures rapidly due to the proximity effects that cause closely spaced features to enlarge and merge. A key challenge is the limited understanding of the origins and spatiotemporal dynamics of the long-range proximity effects that extend beyond the optical focal spot. Here, we empirically investigate these proximity effects in serial TPL using custom-made acrylate-based photoresists. We demonstrate that the complex spatiotemporal dynamics of the proximity effects can be explained through the kinetics of the reaction–diffusion photopolymerization mechanisms that underlie the curing process. Specifically, we show that the proximity effects arise due to comparable timescales of reaction and diffusion of oxygen. Furthermore, we demonstrate that long-range proximity effects can be suppressed by introducing phenolic inhibitors, which reduce oxygen consumption through non-inhibiting side reactions and promote faster termination of curing reactions. These insights enabled improving the linewidths from >400 to 260 nm during printing of nanoporous 3D woodpiles at scanning speeds of 50 mm s −1 . Thus, the knowledge generated here can be applied to deterministically tune the proximity effects and enable rapid printing of high-resolution nanoporous 3D structures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tip-based proximity ferroelectric switching and piezoelectric response in wurtzite multilayers

Proximity ferroelectricity is a paradigm for inducing ferroelectricity when a nonferroelectric polar material (such as Al⁢ N), which is unswitchable with an external field below the dielectric breakdown field, becomes a practically switchable ferroelectric in direct contact with a thin switchable ferroelectric layer (such as Al 1−𝑥 ⁢Sc 𝑥 ⁢N). Here, we develop a Landau-Ginzburg-Devonshire approach to study the proximity effect of local piezoelectric response and polarization reversal in wurtzite ferroelectric multilayers under a sharp electrically biased tip. Using finite-element modeling, we analyze the probe-induced nucleation of nanodomains, the features of local polarization hysteresis loops and coercive fields in the Al 1−𝑥 ⁢Sc 𝑥 ⁢N/Al⁢ N bilayers and three-layers. Similar to the wurtzite multilayers sandwiched between two parallel electrodes, the regimes of “proximity switching” (when all layers collectively switch) and the regime of “proximity suppression” (when they collectively do not switch) are the only two possible regimes in the probe-electrode geometry. However, the parameters and asymmetry of the local piezoresponse and polarization hysteresis loops depend significantly on the sequence of the layers with respect to the probe. The physical mechanism of proximity ferroelectricity in the local probe geometry is a depolarizing electric field determined by the polarization of the layers and their relative thickness. The field, whose direction is opposite to the polarization vector in the layer(s) with the larger spontaneous polarization (such as Al⁢ N), renormalizes the double-well ferroelectric potential to lower the steepness of the switching barrier in the “otherwise unswitchable” polar layers. Tip-based control of domains in otherwise nonferroelectric layers using proximity ferroelectricity can provide nanoscale control of domain reversal in memory, actuation, sensing, and optical applications. The ability of the tip-induced proximity switching to differentially switch multilayers, based on the order of the layers, provides a powerful tool for selective domain engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Proximal Galerkin: A Structure-Preserving Finite Element Method for Pointwise Bound Constraints

The proximal Galerkin finite element method is a high-order, low iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of pointwise bound constraints in infinite-dimensional function spaces. This paper introduces the proximal Galerkin method and applies it to solve free boundary problems, enforce discrete maximum principles, and develop a scalable, mesh-independent algorithm for optimal design with pointwise bound constraints. This paper also introduces the latent variable proximal point (LVPP) algorithm, from which the proximal Galerkin method derives. When analyzing the classical obstacle problem, we discover that the underlying variational inequality can be replaced by a sequence of second-order partial differential equations (PDEs) that are readily discretized and solved with, e.g., the proximal Galerkin method. Throughout this work, we arrive at several contributions that may be of independent interest. These include (1) a semilinear PDE we refer to as the entropic Poisson equation; (2) an algebraic/geometric connection between high-order positivity-preserving discretizations and certain infinite-dimensional Lie groups; and (3) a gradient-based, bound-preserving algorithm for two-field, density-based topology optimization. The complete proximal Galerkin methodology combines ideas from nonlinear programming, functional analysis, tropical algebra, and differential geometry and can potentially lead to new synergies among these areas as well as within variational and numerical analysis. Open-source implementations of our methods accompany this work to facilitate reproduction and broader adoption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Explainable machine learning to quantify the value of proximal remote sensing in latent energy flux estimation

Proximal remote sensing has the potential to provide critical information on vegetation biophysical factors that can predict land-atmosphere exchange of water and energy. Latent energy (LE) flux is traditionally estimated using process-based models which rely on vegetation parameters that change during the growing season. Data-driven models have the potential to address these issues by offering flexible predictor selection and more efficient utilization of the information in predictor sets. These models require careful choice of predictors to avoid redundancy and allow robust cross-validation. In this study we present a systematic and comprehensive evaluation of machine learning (ML) models to assess the capability of meteorological and proximal sensing data for predicting LE at a half-hourly temporal resolution across multiple growing seasons for an agricultural system. The results presented here demonstrate that a model using four environmental predictors in combination with two proximal sensing variables can capture 88 % of the variability in LE. ML models using only three predictors (one meteorological and two proximal remote sensing) captured 81 % of LE variability, offering the best trade-off between performance and complexity. An ML model utilizing only two predictors, one proximal remote sensing variable and downwelling radiation, captured 77 % of LE variability. These results demonstrate the power of proximal remote sensing and meteorological observations to estimate land-atmosphere water vapor exchange, providing a solution where more direct methods such as eddy covariance are not available and for evaluations of agronomic management and genotypic variations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Three-dimensional spheroid culture induces apical-basal polarity and the original characteristics of immortalized human renal proximal tubule epithelial cells

Highlights: • Immortalized proximal tubule cells (HK-2 cells) formed a tubule-like structure. • The 3D spheroid culture enhanced apical-basal polarity of HK-2 cells. • The 3D spheroid culture induced Na transport function of HK-2 cells. • The 3D spheroid culture promoted up-regulation of kidney development-related genes. The proximal tubules, which are part of the kidney, maintain blood homeostasis by absorbing amino acids, glucose, water, and ions such as sodium (Na), potassium, and bicarbonate. Proximal tubule dysfunction is associated with the pathogenesis of many kidney diseases. Renal proximal tubular epithelial cells (RPTECs) are responsible for the main functions of the proximal tubules. Therefore, in vitro experiments using RPTECs would greatly enhance our understanding of nephron physiology and pathobiology. It is preferable to use immortalized cell lines, such as human kidney-2 (HK-2) cells, because they are derived from humans and maintain growth indefinitely. However, tissue-specific RPTEC phenotypes, including apical-basal polarization, are frequently lost in conventional two-dimensional culture methods in part due to microenvironmental deficiencies. To overcome this limitation, we developed a three-dimensional (3D) spheroid culture method for HK-2 cells using an extracellular matrix. HK-2 spheroids in 3D culture formed a tubule-like architecture with cellular polarity and showed markedly restored Na transport function. 3D culture of HK-2 cells also increased expression of kidney development–related genes, including WNT9B. Models of human renal tubules using HK-2 spheroids will greatly improve our understanding of the physiology and pathobiology of the kidney.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Layer-resolved magnetic proximity effect in van der Waals heterostructures

Magnetic proximity effects are integral to manipulating spintronic, superconducting, excitonic and topological phenomena in heterostructures. These effects are highly sensitive to the interfacial electronic properties, such as electron wavefunction overlap and band alignment. The recent emergence of magnetic two-dimensional materials opens new possibilities for exploring proximity effects in van der Waals heterostructures. In particular, atomically thin CrI 3 exhibits layered antiferromagnetism, in which adjacent ferromagnetic monolayers are antiferromagnetically coupled. In this paper, we report a layer-resolved magnetic proximity effect in heterostructures formed by monolayer WSe 2 and bi/trilayer CrI 3 . By controlling the individual layer magnetization in CrI 3 with a magnetic field, we show that the spin-dependent charge transfer between WSe 2 and CrI 3 is dominated by the interfacial CrI 3 layer, while the proximity exchange field is highly sensitive to the layered magnetic structure as a whole. In combination with reflective magnetic circular dichroism measurements, these properties allow the use of monolayer WSe 2 as a spatially sensitive magnetic sensor to map out layered antiferromagnetic domain structures at zero magnetic field as well as antiferromagnetic/ferromagnetic domains at finite magnetic fields. Our work reveals a way to control proximity effects and probe interfacial magnetic order via van der Waals engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Always/Never Safety Framework for Satellite Rendezvous and Proximity Operations and On-Orbit Servicing

Space rendezvous and proximity operations are increasing in numbers, enabling inspections, diagnostics, and maintenance of on-orbit systems. Because collision, loss of control, and unintended damage can impact the system under examination -- and at the extreme, cause system break-up and space debris -- the safety practices for rendezvous and proximity operations can have significant implications for national security. This study examines the applicability of the Always/Never surety framework, which was developed for United States nuclear weapons, as a model safety basis for unmanned space proximity operations. This unclassified framework has understandable safety approaches and principles and focuses on a system being always safenever unsafe. The authors consider that the adapting the framework might present a means for standardization across government and commerce, encouraging a consistent approach and a set of clarifying safety principles and applications for rendezvous and proximity operations. The framework also offers a consistent taxonomy, presents safety and reliability requirements organized by four environment categories, defines accident or abnormal conditions, contributes a strategy for identifying hostile and tactical environments, and enables decision-making for determining if conditions are safe for proximity space operations.

42 ENGINEERING↗
DOE OSTI2022

Proximity Effects and Topological Spin Currents in van der Waals Heterostructures (Final Report)

The major goal of this grant has been to study spin-polarized topological edge states. The original proposal was focused specifically on those of the quantum anomalous Hall (QAH) effect, which was proposed to be realizable via a (simultaneous) magnetic and spin-orbit proximity effect in graphene. En route to realizing the QAH effect, the goal was also to study the newly-discovered 2D magnetic insulators, which have finally been isolated in the single-to-few atomic layers from compounds whose bulk properties have known since the 1970s, and the extent to which magnetic effects could be seen in graphene via proximity coupling. Since the original proposal, the scope of the work has expanded to include study of the topological edge states of the quantum spin Hall (QSH) effect and how they are modified by proximity effects and in twisted bilayers. The broader scientific context of the experiments in this proposal is to understand the physical mechanisms behind proximity effects in van der Waals heterostructures. Perhaps the ultimate scientific and technological goal of realizing topological states through proximity effects is the creation of Majorana zero modes in solid-state devices, which has been identified as a major priority in condensed-matter physics and quantum information because of the potential use of Majorana zero modes in topological quantum computing. Van der Waals materials offer advantages in this area because of the diversity of materials that can potentially be used and the unique device architectures that are possible using the van der Waals assembly techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Origin of Suppression of Proximity-Induced Superconductivity in Bi/Bi 2 Sr 2 CaCu 2 O 8+δ Heterostructures

Mixing of topological states with superconductivity could result in topological superconductivity with the elusive Majorana fermions potentially applicable in fault-tolerant quantum computing. One possible candidate considered for realization of topological superconductivity is thin bismuth films on Bi 2 Sr 2 CaCu 2 O 8+δ (Bi2212). Here, we present angle-resolved and core-level photoemission spectroscopy studies of thin Bi films grown in-situ on as-grown Bi2212 that show the absence of proximity effect. We find that the electron transfer from the film to the substrate and the resulting severe underdoping of Bi2212 at the interface is a likely origin for the absence of proximity effect. We also propose a possible way of preventing a total loss of proximity effect in this system. Our results offer a better and more universal understanding of the film/cuprate interface and resolve many issues related to the proximity effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Gate-Tunable Proximity Effects in Graphene on Layered Magnetic Insulators

The extreme versatility of van der Waals materials derives from their ability to exhibit new electronic properties when assembled in proximity with dissimilar crystals. 1 For example, although graphene is inherently non-magnetic, recent work has reported a magnetic proximity effect in graphene interfaced with magnetic substrates, potentially enabling a pathway towards achieving a high-temperature quantum anomalous Hall effect. Here, we investigate heterostructures of graphene and chromium trihalide magnetic insulators (CrI 3 , CrBr 3 , and CrCl 3 ). Surprisingly, we are unable to detect a magnetic exchange field in the graphene, but instead discover proximity effects featuring unprecedented gate-tunability. The graphene becomes highly hole-doped due to charge transfer from the neighboring magnetic insulator, and further exhibits a variety of atypical gate-dependent transport features. The charge transfer can additionally be altered upon switching the magnetic states of the nearest CrI 3 layers. In conclusion, our results provide a roadmap for exploiting proximity effects arising in graphene coupled to magnetic insulators.

2D magnet↗