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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dual–Interface–Reinforced Flexible Perovskite Solar Cells for Enhanced Performance and Mechanical Reliability

Two key interfaces in flexible perovskite solar cells (f-PSCs) are mechanically reinforced simultaneously: one between the electron-transport layer (ETL) and the 3D metal-halide perovskite (MHP) thin film using self-assembled monolayer (SAM), and the other between the 3D-MHP thin film and the hole-transport layer (HTL) using an in situ grown low-dimensional (LD) MHP capping layer. The interfacial mechanical properties are measured and modeled. This rational interface engineering results in the enhancement of not only the mechanical properties of both interfaces but also their optoelectronic properties holistically. As a result, the new class of dual-interface-reinforced f-PSCs has an unprecedented combination of the following three important performance parameters: high power-conversion efficiency (PCE) of 21.03% (with reduced hysteresis), improved operational stability of 1000 h T90 (duration at 90% initial PCE retained), and enhanced mechanical reliability of 10 000 cycles n88 (number of bending cycles at 88% initial PCE retained). Furthermore, the scientific underpinnings of these synergistic enhancements are elucidated.

14 SOLAR ENERGY↗
DOE OSTI2012

Revisiting Johnson and Jackson boundary conditions for granular flows

In this article, we revisit Johnson and Jackson boundary conditions for granular flows. The oblique collision between a particle and a flat wall is analyzed by adopting the classic rigid-body theory and a more realistic semianalytical model. Based on the kinetic granular theory, the input parameter for the partial-slip boundary conditions, specularity coefficient, which is not measurable in experiments, is then interpreted as a function of the particle-wall restitution coefficient, the frictional coefficient, and the normalized slip velocity at the wall. An analytical expression for the specularity coefficient is suggested for a flat, frictional surface with a low frictional coefficient. The procedure for determining the specularity coefficient for a more general problem is outlined, and a working approximation is provided.

boundary condition↗
DOE OSTI2022

High performance high-power textured Mn/Cu-doped PIN-PMN-PT ceramics

Piezoelectric ceramics with combinatory soft and hard characteristics are highly desired for high-power applications. However, it remains grand challenge to achieve simultaneous presence of hard (e.g. high coercive field, E c ; high mechanical quality factor, Q m ) and soft (e.g. high piezoelectric constant, d; high electromechanical coupling factor, k) piezoelectric properties in piezoelectric ceramics since the mechanism controlling the hard behavior (pinned domain walls) will significantly reduce the soft behavior. Here, we address this grand challenge and demonstrate <001> textured MnO 2 and CuO co-doped Pb(In 1/2 Nb 1/2 )O 3- Pb(Mg 1/3 Nb 2/3 )O 3- PbTiO 3 (PIN-PMN-PT) ceramics exhibiting ultrahigh combined soft and hard piezoelectric properties (d 33 = 713 pC N –1 , k 31 = 0.52, Q m ≈950, E c = 9.6 kV cm –1 , tan δ = 0.45%). The outstanding electromechanical properties are explained by considering composition/phase selection, crystallographic anisotropy and defect engineering. Phase-field model in conjunction with high resolution electron microscopy and diffraction techniques is utilized to delineate the contributions arising from intrinsic piezoelectric response, domain dynamics, and local structural heterogeneity. Furthermore, these results will have significant impact in the development of high-power transducers and actuators.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Performance investigation of a high-field active magnetic regenerator

Regenerative magnetic cycles are of interest for small-scale, high-efficiency cryogen liquefiers; however, commercially relevant performance has yet to be demonstrated. To develop improved engineering prototypes, an efficient modeling tool is required to screen the multi-parameter design space. In this work, we describe an Active Magnetic Regenerative Refrigerator (AMRR) prototype using a high-field superconducting magnet that produces a 100 K temperature span. Using the experimental data, a semi-analytic AMR element model is validated and enhanced system performance is simulated using liquid propane as a heat transfer fluid. In addition, the regenerator composition and fluid flow are simultaneously optimized using a differential evolution algorithm. Simulation results indicate that a natural gas liquefier with a 160 K span and a second-law efficiency exceeding 20% is achievable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Modeling and simulation of vascular tumors embedded in evolving capillary networks

Here in this work, we present a coupled 3D–1D model of solid tumor growth within a dynamically changing vascular network to facilitate realistic simulations of angiogenesis. Additionally, the model includes erosion of the extracellular matrix, interstitial flow, and coupled flow in blood vessels and tissue. We employ continuum mixture theory with stochastic Cahn–Hilliard type phase-field models of tumor growth. The interstitial flow is governed by a mesoscale version of Darcy’s law. The flow in the blood vessels is controlled by Poiseuille flow, and Starling’s law is applied to model the mass transfer in and out of blood vessels. The evolution of the network of blood vessels is orchestrated by the concentration of the tumor angiogenesis factors (TAFs); blood vessels grow towards the increasing TAFs concentrations. This process is not deterministic, allowing random growth of blood vessels and, therefore, due to the coupling of nutrients in tissue and vessels, makes the growth of tumors stochastic. We demonstrate the performance of the model by applying it to a variety of scenarios. Numerical experiments illustrate the flexibility of the model and its ability to generate satellite tumors. Simulations of the effects of angiogenesis on tumor growth are presented as well as sample-independent features of cancer.

3D–1D coupled blood flow models↗
DOE OSTI2023

Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems using state measurements. One approach, known as Sparse Identification of Nonlinear Dynamics (SINDy), assumes the dynamics are sparse within a predetermined basis in the states and finds the expansion coefficients through linear regression with sparsity constraints. This approach requires an accurate estimation of the state time derivatives, which is not necessarily possible in the high-noise regime without additional constraints. We present an approach called Derivative-based SINDy (DSINDy) that combines two novel methods to improve ODE recovery at high-noise levels. First, we denoise the state variables by applying a projection operator that leverages the assumed basis for the system dynamics. Second, we use a second order cone program (SOCP) to find the derivative and governing equations simultaneously. We derive theoretical results for the projection-based denoising step, which allow us to estimate the values of hyperparameters used in the SOCP formulation. This underlying theory helps limit the number of required user-specified parameters. Finally, we present results demonstrating that our approach leads to improved system recovery for the Van der Pol oscillator, the Duffing oscillator, the Rössler attractor, and the Lorenz 96 model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Manufacturing and characterization of continuous fiber-reinforced thermoplastic tape overmolded long fiber thermoplastic

Light-weight construction, design freedom, integration of functions, and compelling cost element are desired by Original Equipment Manufacturers (OEMs) and their suppliers. The emergence of overmolding of continuous-discontinuous reinforcement enables design freedom and ability to tailor stiffness, strength, and damage tolerance for structural applications. In this work, long fiber thermoplastics (LFT) are overmolded with continuous fiber-reinforced thermoplastic (CFRTP) tape are combined using extrusion compression molding process to evaluate the structural performance. The CFRTP tape overmolded LFT samples were characterized using nondestructive and destructive techniques to track fiber alignment, fiber distribution, manufacturing defects, interfacial bonding of the tape – LFT and effect of CFRTP tape on LFT. Mode 1 fracture toughness, G 1c for tape overmolded LFT was higher by 25–30% compared to literature reported G 1c . This response was attributed to excellent fiber distribution, good fiber wetting, and absence of voids at the interface. Three-point bend test indicated that CFRTP tape overmolded LFT composites were better able to resist damage under the bending load compared to constituent LFT composite. Flexural strength of the overmolded composite was higher by 119–142%, and modulus higher by 77–65% compared to constituent LFT composite. Simulated flexural results accurately represents the mechanical behavior of composites. Here, the penetration energy of tape overmolded LFT composites determined by LVI test was in the range of 27.66–30.15 J, which is significantly higher than constituent LFT composite, 7.76 J. CFRTP tape overmolded LFT composite exhibits progressive fiber fracture, matrix cracking, and interfacial debonding failure, whereas, constituent LFT composite showed catastrophic fiber fracture.

42 ENGINEERING↗
DOE OSTI2023

Atomistic determination of Peierls barriers of dislocation glide in nickel

The Peierls barrier measures the lattice resistance to dislocation glide in crystalline solids. We use the nudged elastic band (NEB) method to calculate the Peierls barriers for screw and edge dislocation glide in a face-centered cubic (FCC) metal of Ni. The minimum energy paths (MEPs) across single or sequential Peierls barriers are determined under shear loading. The NEB results show the decreasing Peierls barrier with increasing shear stress, giving the Peierls stress at which the Peierls barrier vanishes. The effects of boundary condition and system size on Peierls barriers are studied by comparing strain- and stress-controlled NEB results. Furthermore, the free-end NEB methods are applied to determine MEPs with improved computational efficiency. The NEB results are also used to evaluate the energetic driving force of dislocation glide, which is consistent with that determined from the Peach-Koehler force. The accuracy of the present NEB results based on an empirical interatomic potential is assessed by comparison with a machine-learning potential. This work demonstrates the robust and efficient quantification of Peierls barriers to dislocation glide in an FCC metal, and it lays a solid foundation for the atomistic determination of Peierls barriers in compositionally complex alloys with the FCC structure in future studies.

42 ENGINEERING↗
DOE OSTI2025

Engineering Clostridium thermocellum for production of 2,3-butanediol from cellulose

Clostridium thermocellum is a promising host for consolidated bioprocessing due to its ability to directly ferment cellulose into fuels and chemicals. However, natural product formation in this organism is limited. Here, we report engineering C. thermocellum for the production of 2,3-butanediol (23BD), a valuable industrial chemical. We functionally expressed a thermophilic 23BD pathway in this organism resulting in a 23BD titer of 19.7 mM from cellulose, representing a metabolic yield of 24%. We used a cell-free systems biology approach to identify limiting steps in the 23BD pathway, revealing that exogenous 23BD dehydrogenase (BDH) activity was essential for production, while native acetolactate synthase (ALS) and acetolactate decarboxylase (ALDC) activities were present but limiting in the parent strain. This approach also revealed redox balance limitations. We demonstrated that this improved understanding of redox balance limitations could be used to increase 23BD titer in vivo, showing that adding acetate could be used to increase 23BD yield. This work establishes a foundation for developing C. thermocellum into a robust platform for 23BD production directly from cellulose and highlights the utility of cell-free systems for guiding metabolic engineering in non-model organisms.

09 BIOMASS FUELS↗
DOE OSTI2022

Toward high efficiency at high temperatures: Recent progress and prospects on InGaN-Based solar cells

III-nitride InGaN material is an ideal candidate for the fabrication of high performance photovoltaic (PV) solar cells, especially for high-temperature applications. Over the past decade, significant efforts have been made to improve the PV performance of InGaN-based solar cells. In this paper, we perform a comprehensive review of the recent developments in InGaN-based solar cells. The topics of discussion include theoretical modeling, material epitaxy, device engineering, and high-temperature measurement. Particularly, we highlight subjects such as substrate technology, and properties that are unique to InGaN materials such as polarization control and their positive thermal coefficient. To date, outstanding high-temperature InGaN-based solar cells with quantum efficiency approaching 80% at 450 °C have been demonstrated. In conclusion, future innovations in epitaxy science, device engineering, and integration methods are required to further advance the efficiency and expand the applications of InGaN-based solar cells.

14 SOLAR ENERGY↗
DOE OSTI2020

Efficient bifurcation and tabulation of multi-dimensional combustion manifolds using deep mixture of experts: An a priori study

This work describes and validates an approach for autonomously bifurcating turbulent combustion man-ifolds to divide regression tasks amongst specialized artificial neural networks (ANNs). This approach relies on the mixture of experts (MoE) framework, where each neural network is trained to be specialized in a given portion of the input space. The assignment of different input regions to the experts is determined by a gating network, which is a neural network classifier. In some previous studies, it has been demonstrated that bifurcation of a complex combustion manifold and fitting different ANNs for each part leads to better fits or faster inference speeds. However, the manner of bifurcation in these studies was based on heuristic approaches or clustering techniques. In contrast, the proposed technique enables automatic bifurcation using non-linear planes in high-dimensional turbulent combustion manifolds that are often associated with complex behavior due to different dominating physics in various zones. Furthermore, the proposed concept is validated using 4-dimensional (4D) and 5D flamelet tables, showing that the errors obtained with a given network size, or conversely the network size required to achieve a given accuracy, is considerably reduced. The effect of the number of experts on inference speed is also investigated, showing that by increasing the number of experts from 1 to 8, the inference time can be approximately reduced by a factor of two. Moreover, it is shown that the MoE approach divides the input manifold in a physically intuitive manner, suggesting that the MoE framework can elucidate high-dimensional datasets in a physically meaningful way.

42 ENGINEERING↗
DOE OSTI2022

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Assessing the osteoblast transcriptome in a model of enhanced bone formation due to constitutive G{sub s}–G protein signaling in osteoblasts

G protein-coupled receptor (GPCR) signaling in osteoblasts (OBs) is an important regulator of bone formation. We previously described a mouse model expressing Rs1, an engineered constitutively active G{sub s}-coupled GPCR, under the control of the 2.3 kb Col I promoter. These mice showed a dramatic age-dependent increase in trabecular bone of femurs. Here, we further evaluated the effects of enhanced G{sub s} signaling in OBs on intramembranous bone formation by examining calvariae of 1- and 9-week-old Col1(2.3)/Rs1 mice and characterized the in vivo gene expression specifically occurring in osteoblasts with activated G{sub s} G protein-coupled receptor signaling, at the cellular level rather than in a whole bone. Rs1 calvariae displayed a dramatic increase in bone volume with partial loss of cortical structure. By immunohistochemistry, Osterix was detected in cells throughout the inter-trabecular space while Osteocalcin was expressed predominantly in cells along bone surfaces, suggesting the role of paracrine mediators secreted from OBs driven by 2.3 kb Col I promoter could influence early OB commitment, differentiation, and/or proliferation. Gene expression analysis of calvarial OBs revealed that genes affected by Rs1 signaling include those encoding proteins important for cell differentiation, cytokines and growth factors, angiogenesis, coagulation, and energy metabolism. The set of G{sub s}-GPCRs and other GPCRs that may contribute to the observed skeletal phenotype and candidate paracrine mediators of the effect of G{sub s} signaling in OBs were also determined. Our results identify novel detailed in vivo cellular changes of the anabolic response of the skeleton to G{sub s} signaling in mature OBs. - Highlights: • OB expression of an engineered G{sub s}-coupled receptor dramatically increases bone mass. • We investigated the changes in gene expression in vivo in enhanced OB G{sub s} signaling. • Genes in cell cycle and transcription were increased in enhanced OB G{sub s} signaling. • GPCRs and paracrine mediators of the effect of G{sub s} signaling in OBs were determined.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

First-Principles Examination of Multiple Criteria of Organic Solvent Oxidative Stability in Batteries

Oxidative instability of the liquid electrolyte at or near battery cathode oxide surfaces has significant detrimental effects on batteries. Organic solvent molecules are often the fuel and precursors of such degradation processes, releasing electrons and protons that react with cathode oxides and electrolyte anions. These reactions contribute to cathode–electrolyte interphase (CEI) film formation, transition-metal ion dissolution, and phase transformation of the surface regions of the cathode. Here we apply density functional theory calculations to examine four criteria of oxidative stability (oxidation potential, hydrogen removal energies, and initial reactivity on two types of oxide facets) using four different solvent/additive molecules (ethylene carbonate, fluoroethylene carbonate, 1,3-dioxolane, and dimethyl ether). The ranking of molecular stability differs with each criterion. Surprisingly, the all-oxygen-terminated basal planes of layered oxides exhibit lower reaction barriers than spinel surface facets with exposed transition-metal cations, especially for ether solvents; the calculations also suggest basal planes contribute to the dissolution of transition-metal ions. Further, the structure–degradation relation complexity underscores the challenge of understanding the function of the CEI but also offers a guide to future degradation-mitigation strategies including facet engineering. Our predictions and models help establish a framework for future studies relevant to high-voltage conditions.

25 ENERGY STORAGE↗
DOE OSTI2019

Characterizing Regional Methane Emissions from Natural Gas Liquids Unloading

A “bottom-up” probabilistic model was developed using engineering first-principles to quantify annualized throughput normalized methane emissions (TNME) from natural gas liquid unloading activities for 18 basins in the United States in 2016. For each basin, six discrete liquid-unloading scenarios are considered, consisting of combinations of well types (conventional and unconventional) and liquid-unloading systems (nonplunger, manual plunger lift, and automatic plunger lift). While previous work has advocated that operational malfunctions and abnormal process conditions explain the existence of super-emitters in the natural gas supply chain, this work finds that super-emitters can arise naturally due to variability in underlying component processes. Additionally, average cumulative methane emissions from liquids unloading, attributed to the natural gas supply chain, across all basins are ~4.8 times higher than those inferred from the 2016 Greenhouse Gas Reporting Program (GHGRP).

Zaimes, George G.↗
DOE OSTI2026

Bayesian Optimization of Catalysis with In-Context Learning

Large language models (LLMs) can perform accurate classification with zero or few examples through in-context learning (ICL), allowing the model to observe query-relevant examples at inference time and eliminating the need for additional weight updates to generalize beyond its original training data. We extend this capability to regression with uncertainty estimation using frozen LLMs (e.g., GPT-4o, Gemini), enabling Bayesian optimization (BO) in natural language without explicit model training or feature engineering. We apply this to materials discovery by representing materials as synthesis and testing procedures for use in natural language prompts. This Bayesian, design-first approach prioritizes optimization toward target material properties before detailed characterization, in contrast to conventional experimental workflows that often emphasize characterization of suboptimal materials. On benchmarks like aqueous solubility and oxidative coupling of methane (OCM), BO-ICL matches or outperforms Gaussian processes. In live experiments on the reverse water–gas shift (RWGS) reaction, BO-ICL identifies multimetallic catalysts that approach equilibrium CO yield within 6 and 10 iterations from a pool of 3,700 and 360,000 candidates, respectively. Our method redefines materials representation and accelerates discovery, with broad applications across catalysis, materials science, and AI.

Calibration↗