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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving Efficiency and Stability of Perovskite Solar Cells Enabled by A Near-Infrared-Absorbing Moisture Barrier

Simultaneously improving device efficiency and stability is the most important issue in perovskite solar cell (PSC) research. Here, we strategically introduce a multi-functional interface layer (MFIL) with integrated roles of: (1) electron transport, (2) moisture barrier, (3) near-infrared photocurrent enhancement, (4) trap passivation, and (5) ion migration suppression to enhance the device performance. The narrow-band-gap non-fullerene acceptor, Y6, was screened out to replace the most commonly used PCBM in the inverted PSCs. A significantly improved power conversion efficiency of 21.0% was achieved, along with a remarkable stability (up to 1,700 h) without encapsulation under various external stimuli (light, heat, and moisture). Furthermore, systematic studies of the molecular orientation or passivation and the charge carrier dynamics at the interface between perovskite and MFIL were presented. These results offer deep insights for designing advanced interlayers and establish the correlations between molecular orientation, interface molecular bonding, trap state density, non-radiation recombination, and the device performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Computational studies reveal Fluorine based quinolines to be potent inhibitors for proteins involved in SARS-CoV-2 assembly

World is witnessing one of the worst pandemics of this century caused by SARS-CoV-2 virus which has affected millions of individuals. Despite rapid efforts to develop vaccines and drugs for COVID-19, the disease is still not under control. Chloroquine (CQ) and Hydroxychloroquine (HCQ) are two very promising inhibitors which have shown positive effect in combating the disease in preliminary experimental studies, but their use was reduced due to severe side-effects. Here, we performed a theoretical investigation of the same by studying the binding of the molecules with SARS-COV-2 Spike protein, the complex formed by Spike and ACE2 human receptor and a human serine protease TMPRSS2 which aids in cleavage of the Spike protein to initiate the viral activation in the body. Both the molecules had shown very good docking energies in the range of -6kcal/mol. Subsequently, we did a high throughput screening for other potential quinoline candidates which could be used as inhibitors. From the large pool of ligand candidates, we shortlisted the top three ligands (binding energy -8kcal/mol). We tested the stability of the docked complexes by running Molecular Dynamics (MD) simulations where we observed the stability of the quinoline analogues with the Spike-ACE2 and TMPRSS2 nevertheless the quinolines were not stable with the Spike protein alone. Thus, although the inhibitors bond very well with the protein molecules their intrinsic binding affinity depends on the protein dynamics. Moreover, the quinolines were stable when bound to electronegative pockets of Spike-ACE2 or TMPRSS2 but not with Viral Spike protein. We also observed that a Fluoride based compound: 3-[3-(Trifluoromethyl)phenyl]quinoline helps the inhibitor to bind with both Spike-ACE2 and TMPRSS2 with equal probability. The molecular details presented in this study would be very useful for developing quinoline based drugs for COVID-19 treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Understanding Solid-Electrolyte Interphase Formation at the Lithium Metal Anode of Lithium-Sulfur Batteries

Lithium-sulfur (Li-S) batteries are one of the most promising chemistries for the next generation of energy storage devices. In a standard Li-S cell, the metallic lithium anode is an essential component of the battery due to its low density, extremely high theoretical specific capacity, and very low negative electrochemical potential. However, several challenges related to the use of Li metal have prevented this battery technology from becoming commercially available. For instance, Li-anodes are highly reactive, which results in the continuous decomposition of the electrolyte and the formation of the solid-electrolyte interphase (SEI) layer. This, combined with the non-uniform deposition of Liions during plating at the anode surface, can seriously affect the performance, cycling, and safety of the battery. In addition, it has been suggested that a controlled SEI formation at the metallic Li anode can yield enhanced battery performance. Hence, a comprehensive understanding of how the SEI layer is formed can help elucidate improvements in this battery technology. In this work, the formation of the SEI layer in Li-S batteries is investigated using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. The stability of liquid organic-based electrolyte components, salt concentration, electron-rich environments, and the use of inorganic solid-state electrolyte (SSE) materials are explored in order to provide molecular-level fundamental insights into how the nature and composition of the electrolyte can alter the initial stages of the SEI formation. The products of electrolyte decomposition and electro-/chemical reaction pathways of liquid electrolyte component such as solvent and salts are predicted from AIMD simulations of electrolyte-anode interfaces. Energetics of reactions from DFT ground-state optimizations are also presented to confirm the decomposition mechanisms. Some significant differences are then drawn regarding the use of low and high salt concentrations. Simulations under electron-rich environments show additional multielectron electrochemical reactions of solvent and salt decomposition taking place due to the excess of electrons and the presence of radical anions in the solution. Finally, the initial stages of formation, stability, and main constituents of interfaces between Li-metal and Sbased electrodes with sulfide-based SSEs are characterized in detail.

25 ENERGY STORAGE↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2020

Review: knots and other new topological effects in liquid crystals and colloids

Abstract Humankind has been obsessed with knots in religion, culture and daily life for millennia, while physicists like Gauss, Kelvin and Maxwell already involved them in models centuries ago. Nowadays, colloidal particles can be fabricated to have shapes of knots and links with arbitrary complexity. In liquid crystals, closed loops of singular vortex lines can be knotted by using colloidal particles and laser tweezers, as well as by confining nematic fluids into micrometer-sized droplets with complex topology. Knotted and linked colloidal particles induce knots and links of singular defects, which can be interlinked (or not) with colloidal particle knots, revealing the diversity of interactions between topologies of knotted fields and topologically nontrivial surfaces of colloidal objects. Even more diverse knotted structures emerge in nonsingular molecular alignment and magnetization fields in liquid crystals and colloidal ferromagnets. The topological solitons include hopfions, skyrmions, heliknotons, torons and other spatially localized continuous structures, which are classified based on homotopy theory, characterized by integer-valued topological invariants and often contain knotted or linked preimages, nonsingular regions of space corresponding to single points of the order parameter space. A zoo of topological solitons in liquid crystals, colloids and ferromagnets promises new breeds of information displays and a plethora of data storage, electro-optic and photonic applications. Their particle-like collective dynamics echoes coherent motions in active matter, ranging from crowds of people to schools of fish. This review discusses the state of the art in the field, as well as highlights recent developments and open questions in physics of knotted soft matter. We systematically overview knotted field configurations, the allowed transformations between them, their physical stability and how one can use one form of knotted fields to model, create and imprint other forms. The large variety of symmetries accessible to liquid crystals and colloids offer insights into stability, transformation and emergent dynamics of fully nonsingular and singular knotted fields of fundamental and applied importance. The common thread of this review is the ability to experimentally visualize these knots in real space. The review concludes with a discussion of how the studies of knots in liquid crystals and colloids can offer insights into topologically related structures in other branches of physics, with answers to many open questions, as well as how these experimentally observable knots hold a strong potential for providing new inspirations to the mathematical knot theory.

Physics↗
DOE OSTI2025

Optimization of an aerostructural machining process using physics-guided Bayesian stability modelling

Existing algorithms for predicting milling chatter have not been widely adopted in industry since they require specialized instruments to measure the stability inputs. This study describes how the machining process for a meter-scale aluminum aerostructure was optimized using a physics-guided Bayesian stability model. The study was performed in collaboration with an industrial partner on production machines to evaluate the practicality of the proposed method under real-world conditions. For each cutting tool, the Bayesian approach automatically selected a small number of cutting tests, which were monitored using a microphone to observe the chatter frequency. The algorithm learned the system dynamics, cutting forces, and stability map from these test results. A novel algorithm for predicting tool bending stress was incorporated into the test selection algorithm to avoid tool breakage. On average, each set of optimized cutting parameters required less than six tests to identify and were 97% more productive than baseline parameters from the cutting tool manufacturer. The machining program was then further optimized using commercial feedrate scheduling software to remove cutting force spikes and reduce air cutting time. Five components were machined using the optimized process. These results demonstrate the potential for physics-guided Bayesian models to improve productivity in industrial settings.

Cornelius, Aaron [UT Knoxville]↗
DOE OSTI2024

Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees

We present differentiable predictive control (DPC), a method for offline learning of constrained neural control policies for nonlinear dynamical systems with performance guarantees. We show that the sensitivities of the parametric optimal control problem can be used to obtain direct policy gradients. Specifically, we employ automatic differentiation (AD) to efficiently compute the sensitivities of the model predictive control (MPC) objective function and constraints penalties. To guarantee safety upon deployment, we derive probabilistic guarantees on closed-loop stability and constraint satisfaction based on indicator functions and Hoeffding’s inequality. We empirically demonstrate that the proposed method can learn neural control policies for various parametric optimal control tasks. In particular, we show that the proposed DPC method can stabilize systems with unstable dynamics, track time-varying references, and satisfy nonlinear state and input constraints. Our DPC method has practical time savings compared to alternative approaches for fast and memory-efficient controller design. Specifically, DPC does not depend on a supervisory controller as opposed to approximate MPC based on imitation learning. We demonstrate that, without losing performance, DPC is scalable with greatly reduced demands on memory and computation compared to implicit and explicit MPC while being more sample efficient than model-free reinforcement learning (RL) algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗
DOE OSTI2024

Conducting polymer-based electrochemical sensors: Progress, challenges, and future perspectives

Conducting polymers are promising due to their unique properties, such as excellent electrical and optical properties, physical and chemical stability, high conductivity, and effective redox properties with high-temperature stability and biocompatibility. Due to these properties, conducting polymers are useful in diverse applications like sensors, batteries, oil industries, biosensors, biomedicines, catalysis, cancer treatment, etc. This review article aims to discuss the recent trends and analysis of conducting polymer-based electrochemical sensors in diverse areas with all required sensor characteristics, such as the derived limit of detection, utilized techniques for the sensing analysis and derived linear dynamic range with the stability of the sensors. Conducting polymers and their nanocomposites-based electrochemical sensors have demonstrated exceptional capabilities towards detecting various biomolecules, heavy metals, pesticides, and viruses like SARS-COV-2. Incorporation of redox mediators, use of conducting hydrogels, and molecular imprinting are promising strategies for better performance of the derived sensor. The article has demonstrated the existing challenges and limitations and provided solutions in the field. In the future, conducting polymers-based electrochemical sensors can be utilized in wearable sensors and integrated with IoT devices for better reach in real-time applications. They can also be made more accessible with precise control and data output by following specific methodologies. Utilizing green and sustainable conducting polymers can be crucial in advancing eco-friendly practices in the future. Conducting polymer-based electrochemical sensors has affectivity in neurochemical and pathogen sensing, which is essential for brain function and mental health.

42 ENGINEERING↗
DOE OSTI2025

Stability and Performance of 3d Transition Metal Carbo‐Sulfides: A Density Functional Theory Exploration for Li‐Ion Battery Anodes

As the demand for high-performance and reliable energy storage devices continues to rise, identifying new anode materials is crucial for advancing Li-ion battery (LIB) technology. Inspired by recent experimental breakthroughs in synthesizing two-dimensional transition metal carbo-chalcogenides (2D-TMCCs), density functional theory calculations are performed to systematically explore their sulfide variants (TM 2 S 2 C) spanning all 3d transition metals in three possible phases. Through comprehensive evaluations of thermodynamic, dynamic, mechanical, and thermal stabilities, seven stable 2D-TMCC candidates are identified, four of which exhibit superior battery performance. Notably, V-based 2D-TMCCs across all three phases deliver moderate open-circuit voltages (OCV), efficient Li diffusion, and substantial capacities, making them promising candidates for industrial applications without requiring specific phase controls. A Cr-based 2D-TMCC (with sulfur atoms above carbon atoms) offers the highest capacity of 515.40 mAh g −1 , the lowest Li diffusion barrier, and an optimal OCV, highlighting its appealing potential as an anode material for LIBs. Furthermore, significant Li–Li spacing and pronounced electron delocalization in these four 2D-TMCCs suggest a reduced risk of dendrite formation. This work expands the 2D-TMCC family and identifies up-and-coming candidates for next-generation LIB anodes.

anode materials↗
DOE OSTI2023

Enhancing SRF cavity stability and minimizing detuning with data-driven resonance control based on dynamic mode decomposition

Effective resonance control of superconducting radio frequency (SRF) cavities is critical for large machines like LCLS-II, as failure to achieve proper control can result in increased RF power consumption, higher cryogenic heat loads, and increased costs. To address this challenge, we have developed a machine learning (ML) model based on the dynamic mode decomposition method to represent the forced cavity dynamics. Using this model, we designed a model predictive controller (MPC) and demonstrated through simulation that the MPC can effectively stabilize the amplitude and phase of SRF cavities using only a frequency actuator, even in the presence of multiple mechanical modes. The lightweight and explicit ML model makes the controller suitable for direct implementation on field-programmable gate arrays, unlocking the full potential of SRF linacs like LCLS-II, enabling higher beam power and energy, and also serving as an advanced motion controller for various applications, such as photon beamlines and storage rings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Stability and distortion of fcc LaH 10 with path-integral molecular dynamics

The synthesis of the high-temperature superconductor LaH 10 requires pressures in excess of 100 GPa, wherein it adopts a face-centered cubic structure. Upon decompression, this structure undergoes a distortion, which still supports superconductivity, but with a lower critical temperature. Previous calculations have shown that quantum and anharmonic effects are necessary to stabilize the cubic structure, but have not resolved the low pressure distortion. Using large scale path-integral molecular dynamics enabled by a machine learned potential, we show that a rhombohedral distortion appears at sufficiently low pressures. Here, we also highlight the importance of quantum zero-point motion in stabilizing the cubic structure.

08 HYDROGEN↗
DOE OSTI2021

Dynamics and chemical mode analysis of plasma thermal-chemical instability

The stability of the weakly ionized plasma and the transition from a stable homogeneous discharge to unstable filaments play an important role in gas laser physics, plasma-assisted combustion, chemical reforming, and material synthesis. Here, theoretical stability analysis and thermal-chemical mode analysis were performed to understand the mechanism of plasma thermal-chemical instability by using a zero-dimensional plasma system with both simplified and detailed chemical kinetics of H 2 /O 2 /N 2 mixtures. The plasma dynamic and kinetic models accounted for multiple physical mechanisms in the chemically-reactive weakly ionized plasma, including ionization, attachment/detachment, recombination, vibrational and electronic energy relaxation, convective and diffusive species/heat removal, Joule heating, and detailed chemical kinetics. An analytical criterion and the explosive mode species/temperature pointers were formulated while the representative active species were identified for different thermal-chemical modes. The results showed that in addition to the classical thermal-ionization mechanism, various chemical modes from chemical heat imbalance and elementary kinetics significantly modified the time dynamics and the stability of the weakly ionized plasma. The present analysis provides insights and guidance to control plasma instability using chemical kinetics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Floquet stability analyses of stratified oscillating boundary layers on adiabatic slopes

The presence of a no-slip, impermeable, adiabatic, sloped boundary in an otherwise quiescent, stably stratified, Boussinesq flow generates baroclinic vorticity within a diffusive boundary layer. Such conditions are typical of the oscillating boundary layers on adiabatic abyssal slopes, sloped lake bathymetry and sloped coastal bathymetry in the absence of high-wavenumber internal waves, mean flows, far-field turbulence on larger scales, and resonant tidal–bathymetric interaction. We investigate the linear stability of the oscillating flow within non-dimensional parameter space typical of the $M_2$ tide and hydraulically smooth, middle-latitude abyssal slopes through Floquet linear stability analysis. The flow dynamics depends on three non-dimensional variables: the Reynolds number for Stokes’ second problem, the Prandtl number, and a frequency ratio that accounts for the resonance conditions ($C$, criticality) of the buoyant restoring force and the tidal forcing. The Floquet analysis results suggest that oscillating laminar boundary layers on adiabatic abyssal slopes are increasingly unstable as Reynolds number, criticality parameter and/or spanwise disturbance wavenumber are increased. We also show that the two-dimensional Floquet linear instability necessarily generates three-dimensional baroclinic vorticity, which suggests that the evolution of the gravitational instabilities may be nonlinear as $t→∞$.

42 ENGINEERING↗
DOE OSTI2021

Impact of Thermal Stress on Attachment and Stability of High Temperature Strain Sensors

Static and dynamic strain sensing is required in high-temperature (HT), harsh-environments (HE) for industrial, aerospace, and energy sector applications to ensure equipment and process safety, reduce the cost of operation and maintenance, and increase process efficiency. Challenges that arise in HT HE sensing applications include device mounting, packaging, integrity, and stability to HT HE conditions. In previously reported work, static and dynamic strain surface acoustic wave resonator (SAWR) sensors were fabricated on langasite (LGS) and mounted on Inconel 625 strain beams for wireless testing up to 400°C. In this work, it has been identified that after subjecting the mounted SAWR strain sensor to thermal cycling between 100°C and 425°C, the measured sensitivity to dynamic strain decreased by 73% due to cracking at the adhesive/LGS interface, further deteriorating after additional thermal cycles. Strain modeling of the mounted LGS sensor chip up to 400°C revealed the existence of concentrated strain at the borders of the LGS chip. Microcracks caused by dicing make the chip boarders the most susceptible location for cracks to initiate when the sensor is subjected to thermal stress. In an attempt to mitigate the high strain at the LGS chip borders due to heating, adhesive shaping is proposed in this work. Simulations indicate a strain reduction of 50% at the border is achieved using both circular and triangular adhesive shapes, while also reducing the maximum strain over the entire adhesive/LGS interface by around 30%. Furthermore, the technique is thus promising for improving the integrity, reliability, and stability of static and dynamic strain sensors, particularly while operating under HT HE with several hundreddegree Celsius temperature excursions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Teaching an Old Reagent New Tricks: Synthesis, Unusual Reactivity, and Solution Dynamics of Borohydride Grignard Compounds

Grignard reagents of general formula RMgX (X = Cl - , Br - , I - ) have been utilized in various chemistries for over 100 years. Here, we report that replacing the halide in a Grignard reagent with a reactive borohydride anion adds a new synthetic dimension for these influential compounds. Here, we synthesized the series RMgBH 4 (R=Et, n-Bu, Ph, Bn) and characterized the reactivity toward both organic and inorganic molecules. Using butylmagnesium borohydride (BuMgBH 4 ) as an exemplar, we demonstrate that these compounds possess unique reactivity due to the presence of reducing borohydride groups, resulting in tandem reactivity with organic amides/esters to generate secondary and primary alcohols. Molecular dynamics simulations indicate the stability of BuMgBH 4 is comparable to that of Mg(BH 4 ) 2 + MgBu 2 , validating the Schlenk equilibrium in borohydride Grignard compounds. Metadynamics simulations confirm that the equilibrium is kinetically accessible through solvent-mediated processes. BuMgBH 4 also reacts with CO 2 and NH 3 , revealing potential uses for CO 2 utilization and as a mixed-anion metal borohydride/amide precursor.

36 MATERIALS SCIENCE↗