Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Robust stability”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing the Impact of Vacancy Diffusion on Void Dynamics at the Lithium Metal–Solid Electrolyte Interface

Lithium (Li) metal-based solid-state batteries (SSBs) are considered promising candidates for next-generation energy storage due to their superior energy density and enhanced safety compared to conventional Li-ion systems. However, their practical application is limited by challenges such as void formation at the Li-solid electrolyte (SE) interface, which disrupts ion transport and accelerates interfacial degradation. This work investigates how the coupled effects of electro-dissolution kinetics and surface diffusion at the Li metal surface govern the evolution of interfacial morphology during stripping. This work examines the influence of three distinct surface diffusion modes, which are terrace diffusion, step diffusion, and interlayer diffusion, on maintaining interfacial stability. In addition, how the dominant surface diffusion mechanism can overcome the contact loss due to high reaction kinetics is explored. Furthermore, the roughness of the Li metal anode surface is quantified, and the influence of different diffusion mechanisms on the evolution of the dynamic solid–solid interface is examined. The critical role of temperature in enhancing Li surface diffusivity and expanding the regime of stable contact is highlighted. By identifying distinct regimes of interface stability, this study analyzes how non-uniform electrochemical dynamics dictate void morphology evolution and interfacial contact. These insights offer guiding principles for engineering robust Li–SE interfaces in SSBs.

lithium metal anode↗
DOE OSTI2024

Nitrogen: A promising doping strategy for high-performance ovonic threshold switching selectors

The Ovonic Threshold Switching (OTS) selector serves as an essential component in the development of three-dimensional high-density memory integration technology. Nevertheless, the state-of-the-art high-performance OTS materials usually contain toxic elements such as arsenic (As), posing significant risks to both environmental and human health. Nitrogen (N), which belongs to the same group as arsenic (As), has emerged as a highly promising alternative for As doping. However, the underlying mechanisms that govern N-based OTS materials have not yet been extensively investigated. In this study, we delve into the effects of N doping on the structural, bonding, and electronic properties of amorphous GeSe (a-GeNSe) by ab initio molecular dynamics simulations to bridge the knowledge gap. Our findings indicate that upon N doping in a-GeSe, the formation of robust Ge-N bonds, along with N-centered tetrahedral and triangular structures, resulting in the sluggish atomic movement that enhances the thermal stability and endurance of a-GeNSe. The OTS characteristics are significantly influenced by the material’s electronic band structure, and thus the relatively slow performance drift can be attributed to the stabilization of mid-gap states, a result of N doping which effectively slows down the aging process of chalcogenide glass. Moreover, the increased mobility gap in a-GeNSe raises the threshold voltage (V th ), making it more compatible with commercially available phase-change memory materials. Furthermore, our findings reveal the extensive impact of the N element on a typical OTS material and offer valuable perspectives for alternative doping strategies that could potentially supplant As practices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Beyond interpolation: Physics-inspired gating transformers for extrapolating irradiation conditions to novel nuclear fuels

The qualification of advanced nuclear fuels relies on irradiation experiments in test reactors that emulate commercial conditions. Designing these tests requires accurate prediction of key irradiation quantities, particularly heat generation rate and burnup, yet obtaining them typically involves computationally expensive multi-step simulation workflows. We propose a physics-inspired gating transformer (PIGT) that integrates an inverse-square, distance-based attenuation into the encoder representation to bias attention toward physically relevant spatial relationships while retaining data-driven flexibility. Using MiniFuel irradiation data from the High Flux Isotope Reactor at Oak Ridge National Laboratory, we benchmark against ensemble methods, feedforward and recurrent networks, convolutional models, and standard transformers. While baseline models perform well under interpolation, they exhibit a pronounced generalization gap when evaluated on fuels not included in the training set. The proposed model consistently improves extrapolative accuracy and stability, yielding the strongest performance on unseen fuel configurations. These results indicate that a lightweight physics structure embedded within attention mechanisms can substantially improve robustness, enabling more reliable surrogate predictions to accelerate the design of nuclear fuel irradiation experiments.

Fuel qualification↗
DOE OSTI2026

Oxidation, Oligomerization, Isomerization of Hydrocarbons Using Metal–Organic Frameworks

The selective conversion of hydrocarbons into higher-value fuels and feedstocks is essential to the global energy and chemistry landscape. While porous inorganic materials have enabled significant progress in these transformations, achieving high activity, selectivity, and stability under industrially relevant conditions remains challenging. Metal–organic frameworks (MOFs) are a promising platform to precisely control active-site environments and interrogate structure–function relationships due to their crystallinity, tunability, and porosity. This review highlights relevant hydrocarbon transformations and outlines the general mechanisms for oxidation, oligomerization, and isomerization. Metal node acidity, confinement effects, and active site dispersion are analyzed for their impact on reactivity and selectivity across the three reactions. Lastly, we discuss current limitations in catalyst stability and offer a perspective on integrating reticular chemistry with high-throughput experimentation and machine learning to accelerate the discovery and design of robust, next-generation MOF catalysts.

Catalysts↗
DOE OSTI2024

Quantification and assessment of the atmospheric boundary layer height measured during the AWAKEN experiment by a scanning LiDAR

The atmospheric boundary layer (ABL) height plays a key role in many atmospheric processes as one of the dominant flow length scales. However, a systematic quantification of the ABL height over the entire range of scales (i.e., with periods ranging from one minute to one year) is still lacking in literature. In this work, the ABL height is quantified based on high-resolution measurements collected by a scanning pulsed Doppler LiDAR during the recent American WAKE experimeNt (AWAKEN) campaign. The high availability of ABL height estimates (≈2200 collected over one year and each of them based on 10-min averaged statistics) allows to robustly assess five different ABL height models, i.e., one for convective thermal conditions and four for stable conditions. Thermal condition is quantified by a stability parameter spanning three orders of magnitude and probed by near-ground 3D sonic anemometry. The free-atmosphere stability, quantified by the Brunt–Väisälä frequency, is both calculated from simultaneous radiosonde measurements and obtained from the best fit of two of the chosen ABL height models. Good agreement is found between the data and three of the chosen models, quantified by mean absolute errors on the ABL height between 281 and 585 m. Furthermore, the seasonal variability of the convective ABL height model parameters (−15% to +23% with respect to the year baseline) agrees with the variability of buoyancy-generated turbulence caused by the variation in solar radiation throughout the year.

17 WIND ENERGY↗
NASA NTRS1978

On decentralized control of large-scale systems

A scheme is presented for decentralized control of large-scale linear systems which are composed of a number of interconnected subsystems. By ignoring the interconnections, local feedback controls are chosen to optimize each decoupled subsystem. Conditions are provided to establish compatibility of the individual local controllers and achieve stability of the overall system. Besides computational simplifications, the scheme is attractive because of its structural features and the fact that it produces a robust decentralized regulator for large dynamic systems, which can tolerate a wide range of nonlinearities and perturbations among the subsystems.

Siljak, D. D.↗
NASA NTRS1994

Matlab as a robust control design tool

This presentation introduces Matlab as a tool used in flight control research. The example used to illustrate some of the capabilities of this software is a robust controller designed for a single stage to orbit air breathing vehicles's ascent to orbit. The global requirements of the controller are to stabilize the vehicle and follow a trajectory in the presence of atmospheric disturbances and strong dynamic coupling between airframe and propulsion.

Gregory, Irene M.↗
DOE OSTI2021

Towards Efficient Uncertainty estimation in deep learning for robust energy prediction in crystal materials

In material science, recent studies have started to explore the potential of using deep learning to improve property prediction from high-fidelity simulations, e.g, density functional theory (DFT). However, the design spaces are sometimes too large and intractable to sample completely. This results in a critical question that is how to evaluate the confidence and robustness of the prediction. In this paper, we propose an efficient approach to estimate uncertainty in deep learning using a single forward pass and then apply it for robust prediction of the total energy in crystal lattice structures. Our approach is built upon the deep kernel learning (DKL) that originally introduces to leverage the expressiveness of deep neural networks as input with a probabilistic prediction of Gaussian processes (GPs) as output. Existing DKL methods have difficulties in the accuracy of predictive uncertainty, training stability, and scaling to large datasets, which lead to significant barriers in real-world applications. We propose to address these challenges by using an inducing point approximate GP in feature space combined with spectral normalization as a regularization. We finally demonstrate our robust performance on an artificial example and a real-world application from materials chemistry.

Bi, Sirui↗
DOE OSTI2025

Constructing Water‐Stable Porous Organic Salts via Suppressed Proton Integration Using Fluorinated Tetrazole Tectons

Porous organic salts (POSs) are an emerging class of materials with ordered ionic architectures, offering excellent proton transfer and water uptake properties. However, conventional POS synthesis via strong acid–base neutralization (e.g., ─SO₃H and ─NH₂) leads to extensive hydrogen bonding with water, compromising stability in aqueous and water-lean environments. Here, we address this challenge by designing POSs with hydrophobic porous channels and minimal hydrogen bonding formation. Our key innovation is the use of fluorinated tetrazole as a weak acid tecton and a tetra-substituted imidazole precursor devoid of active protons as the base. Single-crystal analysis and computational modeling reveal that the structural integrity of the synthesized POSs arises primarily from cation–anion interactions, with water confined as clusters in the pores, independent of hydrogen bonding with the scaffold. Robustness of the POS structure under aqueous and water-lean conditions is confirmed by X-ray and neutron scattering, as well as computational modeling, confirming preserved packing and crystal structures. The stability of POS is further demonstrated in aqueous iodine capture, with imidazolium cations and C–F functionalizations serving as strong adsorption sites. As a result, the approach developed herein further pushes the boundary of POS materials to withstand both aqueous and water-lean conditions.

Fluorinated tecton↗
NASA NTRS2000

Predictive and Neural Predictive Control of Uncertain Systems

Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

Kelkar, Atul G.↗
DOE OSTI2024

Impact of Mg Substitution on the Structure, Stability, and Properties of the Na 2 Fe 2 F 7 Weberite Cathode

Of the few weberite-type Na-ion cathodes explored to date, Na 2 Fe 2 F 7 exhibits the best performance, with capacities up to 184 mAh/g and energy densities up to 550 Wh/kg reported for this material. However, the development of robust structure–property relationships for this material is complicated by its tendency to form as a mixture of metastable polymorphs, and transform to a lower-energy Na y FeF 3 perovskite compound during electrochemical cycling. Our first-principles-guided exploration of Fe-based weberite solid solutions with redox-inactive Mg 2+ and Al 3+ predicts an enhanced thermodynamic stability of Na 2 Mg x Fe 2–x F 7 as the Mg content is increased, and the x = 0.125 composition is selected for further exploration. We demonstrate that the monoclinic polymorph (space group C2/c) of Na 2 Fe 2 F 7 (Mg0) and of a new Mg-substituted weberite composition, Na 2 Mg 0.125 Fe 1.875 F 7 (Mg0.125), can be isolated using an optimized synthesis protocol. The impact of Mg substitution on the stability of the weberite phase during electrochemical cycling, and on the extent and rate of Na (de)intercalation, is examined. Irrespective of the Mg content, we find that the weberite phase is retained when cycling over a narrow voltage window (2.8–4.0 V vs Na/Na+). Over a wider voltage range (1.9–4.0 V), Mg0 shows steady capacity fade due to its transformation to the NayFeF3 perovskite phase, while Mg0.125 displays more reversible cycling and a reduced phase transformation. Yet, Mg incorporation also leads to kinetically limited Na extraction and a reduced overall capacity. These findings highlight the need for the continued compositional optimization of weberite cathodes to improve their structural stability while maximizing their energy density.

25 ENERGY STORAGE↗
DOE OSTI2025

Thermostable Enzyme Variants in the Lower Mevalonate Pathway Improve Isoprenoid Production by Cell-Free Biocatalysis

Cell-free biocatalysis is a rapidly evolving field with great potential for sustainably producing valuable chemicals. Some challenges in cell-free biocatalysis include reaction longevity, enzyme stability, and the cost of the biocatalysts. Here, the challenge of enzyme instability was addressed by employing thermophilic enzymes to improve the productivity of the lower mevalonate pathway, using limonene as an example isoprenoid product. The Classical mesophilic mevalonate pathway was compared to a newly assembled set of thermophilic enzymes comprising the Archaea I mevalonate pathway. The thermophilic pathway enzymes were thermostable to at least 60 °C and exhibited a 6× longer operating lifetime at 22 °C. Thus, despite lower initial activity rates at ambient temperature, the thermophilic pathway was longer-lived and resulted in a more productive cell-free reaction overall, achieving 1.7× higher yield of limonene compared to using enzymes from mesophiles. Moreover, the thermostable pathway retained activity for longer with the challenge of solvent exposure, namely, ethanol and isoprenol, which broadens the scope of accessible substrates and/or products in cell-free reactions employing this pathway. Altogether, we showed significant improvement in the stability and productivity of the lower mevalonate pathway, which will enable more efficient cell-free biosynthesis of isoprenoid products. This represents a valuable strategy to increase the robustness of cell-free systems by carefully sourcing biocatalysts from thermophilic organisms, which have proven to be resilient to challenges unique to cell-free reaction systems.

09 BIOMASS FUELS↗
DOE OSTI2020

LixNiO/Ni Heterostructure with Strong Basic Lattice Oxygen Enables Electrocatalytic Hydrogen Evolution with Pt-like Activity

The low-cost hydrogen production from water electrolysis is crucial for practical deployment of sustainable hydrogen economy, but is often constrained by the lack of active and robust electrocatalysts from Earth-abundant materials. We describe here an unconventional heterostructure composed of strongly coupled Ni-deficient LixNiO nanoclusters and polycrystalline Ni nanocrystals, and its exceptional activities toward hydrogen evolution reaction (HER) in aqueous electrolytes. The presence of unique lattice oxygen species with strong Brønsted basicity is a significant feature, which spontaneously split water molecules and effectively accelerate the sluggish Volmer H-OH dissociation step in neutral and alkaline HER. In combination with the unpreceded level of intimate LixNiO and Ni interfacial junctions that produces abundant “hotspots” for promoted hydride coupling, the catalyst exhibited kinetic activities almost identical as Pt/C and decent long term stability in universal pH.

Lu, Ke↗
DOE OSTI2025

In-situ polymerized and crosslinked electrolytes with interchangeable Li/Na transport for battery applications

The next generation of batteries requires electrolytes with high conductivity, mechanical stability, good adhesion with electrodes, wide electrochemical windows, and scalability. The present study introduces a concept of doped quasi single-ion conducting copolymers based on methacrylate-(trifluoromethanesulfonyl)imide (TFSI) and vinyl ethylene carbonate which at room temperature are mechanically robust and display ionic conductivities of ~0.1 mS/cm. These electrolytes can be polymerized/crosslinked in-situ, making them easily implementable in current battery manufacturing technologies. They also allow for switching between Li + and Na + transport using simple chemistry procedures. To demonstrate their potential for battery applications, the newly developed Li conductors have been tested in symmetric cells, exhibiting overall impedance below 350 Ohm and plating/stripping stability up to 1 mA/cm 2 . Moreover, lithium metal batteries incorporating this electrolyte and high-voltage Lithium Nickel Manganese Cobalt Oxide (NMC) cathodes show good capacity retention (~79%) during charging and discharging for 80 cycles at C/10 rate and a Coulombic efficiency close to 100% in the entire measurement range. The compositional, mechanical and electrochemical versatility of these electrolytes opens new venues for the design of polymer-based batteries capable of fast charging and extended cycle life, aligning with the current global green energy storage strategies.

Polymer electrolytes↗
DOE OSTI2024

Optimizing Deep Geothermal Drilling for Energy Sustainability in the Appalachian Basin

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings.

Environmental Sciences & Ecology↗
DOE OSTI2025

Robust Implicit Adaptive Low Rank Time-Stepping Methods for Matrix Differential Equations

In this work, we develop implicit rank-adaptive schemes for time-dependent matrix differential equations. The dynamic low rank approximation (DLRA) is a well-known technique to capture the dynamic low rank structure based on Dirac–Frenkel time-dependent variational principle. In recent years, it has attracted a lot of attention due to its wide applicability. Our schemes are inspired by the three-step procedure used in the rank adaptive version of the unconventional robust integrator (the so called BUG integrator) (Ceruti et al. in BIT Numer Math 62(4):1149–1174, 2022) for DLRA. First, a prediction (basis update) step is made computing the approximate column and row spaces at the next time level. Second, a Galerkin evolution step is invoked using an implicit solves for the small core matrix. Finally, a truncation is made according to a prescribed error threshold. Since the DLRA is evolving the differential equation projected on to the tangent space of the low rank manifold, the error estimate of the BUG integrator contains the tangent projection (modeling) error which cannot be easily controlled by mesh refinement. This can cause convergence issue for equations with cross terms. To address this issue, we propose a simple modification, consisting of merging the row and column spaces from the explicit step truncation method together with the BUG spaces in the prediction step. In addition, we propose an adaptive strategy where the BUG spaces are only computed if the residual for the solution obtained from the prediction space by explicit step truncation method, is too large. Here, we prove stability and estimate the local truncation error of the schemes under assumptions. We benchmark the schemes in several tests, such as anisotropic diffusion, solid body rotation and the combination of the two, to show robust convergence properties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mechanical, Morphological, and Charge Transport Properties of NDI Polymers with Variable Built‐in Π‐Conjugation Lengths Probed by Simulation and Experiment

Abstract Mechanically deformable polymeric semiconductors are a key material for fabricating flexible organic thin‐film transistors (FOTFTs)—the building block of electronic circuits and wearable electronic devices. However, for many π‐conjugated polymers achieving mechanical deformability and efficient charge transport remains challenging. Here the effects of polymer backbone bending stiffness and film microstructure on mechanical flexibility and charge transport are investigated via experimental and computational methods for a series of electron‐transporting naphthalene diimide (NDI) polymers having differing extents of π‐conjugation. The results show that replacing increasing amounts of the π‐conjugated comonomer dithienylvinylene (TVT) with the π‐nonconjugated comonomer dithienylethane (TET) in the backbone of the fully π‐conjugated polymeric semiconductor, PNDI‐TVT 100 (yielding polymeric series PNDI‐TVT x , 100 ≥x≥ 0), lowers backbone rigidity, degree of texturing, and π–π stacking interactions between NDI moieties. Importantly, this comonomer substitution increases the mechanical robustness of PNDI‐TVT x while retaining efficient charge transport. Thus, reducing the TVT content of PNDI‐TVT x suppresses film crack formation and dramatically stabilizes the field‐effect electron mobility upon bending (e.g., 2 mm over 2000 bending cycles). This work provides a route to tune π–π stacking in π‐conjugated polymers while simultaneously promoting mechanical flexibility and retaining good carrier mobility in FOTFTs.

Chemistry↗
DOE OSTI2021

Extending a 10‐node composite tetrahedral finite element for solid mechanics

Abstract We propose to extend the composite tetrahedral finite element first introduced by Thoutireddy et al. (2002) and recently reformulated by Ostien et al. (2016). We generalize the gradient operator and mass matrix to curved domains through analytical expressions weighted by subtetrahedra Jacobians. Optimal integration weights are constructed to increase the accuracy of Gaussian quadrature. We preserve the variational structure of the formulation through a new five‐field functional with additional, independent fields for the Jacobian and the pressure. This approach not only obviates volumetric locking but also yields symmetry. A deleterious soft mode, common to both the quadratic and composite tetrahedral element with constant pressure formulations is effectively stabilized through a novel convex energy penalty function. Numerous numerical examples spanning a patch test to the impact of a Taylor bar demonstrate the accuracy, robustness, and convergence of the extended composite tetrahedral element for application to structural metals.

Foulk III, James W.↗