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Results for “guide 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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Escherichia coli Cas1/2 Endonuclease Complex Modifies Self-Targeting CRISPR/Cascade Spacers Reducing Silencing Guide Stability

CRISPR-based interference has become common in various applications from genetic circuits to dynamic metabolic control. In E. coli, the native CRISPR Cascade system can be utilized for silencing by deletion of the cas3 nuclease along with expression of guide RNA arrays, where multiple genes can be silenced from a single transcript. We notice the loss of spacer sequences from guide arrays utilized for dynamic silencing. Here, we report that unstable guide arrays are due to expression of the Cas1/2 endonuclease complex. We propose a model wherein basal Cas1/2 endonuclease activity results in the loss of spacers from guide arrays. Subsequently, mutant guide arrays can be amplified through selection. Replacing a constitutive promoter driving Cascade complex expression with a tightly controlled inducible promoter improves guide array stability, while minimizing leaky gene silencing. Additionally, these results demonstrate the potential of Cas1/2 mediated guide deletion as a mechanism to avoid CRISPR based autoimmunity.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2021

First-Principles Characterization of Surface Phonons of Halide Perovskite CsPbI 3 and Their Role in Stabilization

The stability of halide perovskites has been a long-standing issue for their real-world application. Approaches to improve stability include nanostructuring, dimensionality reduction, and strain engineering, where surfaces play an important role in the formation of a stable structure. To understand the mechanism we compute the lattice dynamics of the surface of CsPbI 3 using density functional theory. We demonstrate, for the first time, that CsPbI 3 crystals exhibit surface phonons that are localized on the outermost layers of the slabs, and we perform a complete symmetry characterization including an identification of the Raman/IR active modes. These surface phonons are present in the optically active cubic phase but are absent in the optically inactive "yellow" phase. Furthermore, we show that the surface suppresses bulk instabilities by hardening soft modes of the bulk cubic phase, resulting in phase stabilization and quenching of dynamical disorder. Finally, this study is fundamental for understanding the structural behavior of halide perovskite materials with high surface area-to-volume ratios, and for guiding stabilization strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Synthetic accessibility and stability rules of NASICONs

In this paper we develop the stability rules for NASICON-structured materials, as an example of compounds with complex bond topology and composition. By first-principles high-throughput computation of 3881 potential NASICON phases, we have developed guiding stability rules of NASICON and validated the ab initio predictive capability through the synthesis of six attempted materials, five of which were successful. A simple two-dimensional descriptor for predicting NASICON stability was extracted with sure independence screening and machine learned ranking, which classifies NASICON phases in terms of their synthetic accessibility. This machine-learned tolerance factor is based on the Na content, elemental radii and electronegativities, and the Madelung energy and can offer reasonable accuracy for separating stable and unstable NASICONs. This work will not only provide tools to understand the synthetic accessibility of NASICON-type materials, but also demonstrates an efficient paradigm for discovering new materials with complicated composition and atomic structure.

25 ENERGY STORAGE↗
DOE OSTI2022

Interleukin-2 superkines by computational design

Significance While computational engineering of therapeutic proteins is a desirable goal, in practice the optimization of protein–protein interactions requires substantial experimental intervention. We present here a computational approach that focuses on stabilizing core protein structures rather than engineering the protein–protein interface. Using this approach, we designed thermostabilized interleukin-2 (IL-2) variants that bind tightly to their receptor without experimental optimization, mimicking the properties of the yeast-display engineered IL-2 variant “super-2.” Our results suggest that structure-guided stabilization may be a general method for in silico affinity maturation of protein–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Computation-guided discovery of coating materials to stabilize the interface between lithium garnet solid electrolyte and high-energy cathodes for all-solid-state lithium batteries

All-solid-state batteries with a lithium metal anode, enabled by lithium garnet solid electrolytes such as Li 7 La 3 Zr 2 O 12 (LLZO), are a promising next-generation energy-storage technology. The further development of all-solid-state battery requires the integration of high-energy cathodes such as LiNi 1-x-y Mn x Co y O 2 (NMC) with the garnet solid electrolyte with stable and low-resistance interfaces, which requires a coating layer to stabilize the interface during high-temperature sintering and electrochemical cycling. In order to guide the future development of interfacial coatings, we perform high-throughput thermodynamic analyses based on first-principles computation to investigate the stability of LLZO garnet and high-energy NMC cathodes with a wide range of materials chemistries. Here our study reveals the factors governing the materials stability with LLZO garnet and NMC cathodes, and identifies the mechanisms of good coating layers stable with LLZO and NMC. In addition to classifying known coating layers, our study provides detailed guiding charts and multiple new materials systems as promising coatings for stabilizing LLZO—NMC interfaces to enable high-energy-density garnet-based all-solid-state batteries. Our demonstrated computation scheme and high-throughput analyses are generally applicable to investigate and screen coating materials for stabilizing interfaces in energy-related applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Computational thermodynamics-guided alloy design and phase stability in CoCrFeMnNi-based medium-and high-entropy alloys: An experimental-theoretical study

A computational thermodynamics approach has been employed to design CoCrFeMnNi-based medium- and high-entropy alloys (M/HEAs) with systematically varied compositions (Co(( 80-X )/ 2 )Cr(( 80-X )/ 2 )Fe X Mn 10 Ni 10 with x = 30, 40, and 50 at.%) and phase stability. Since the formation of sigma phase, usually brittle and undesirable, is a common concern, when this class of alloys is subjected to elevated temperatures (600–1000 °C), predicting its formation becomes essential. Thus, its formation and the phase equilibria were studied using the CALPHAD method, and two empirical methods, namely, valence electron concentration (VEC) and paired sigma-forming element (PSFE). Isothermal aging treatments at 900–1100 °C for 20 h were performed, since CALPHAD and VEC/PSFE predictions diverged. Both prediction methods were compared with experimental characterization by a combination of scanning electron microscopy and high-energy synchrotron X-ray diffraction. In conclusion, the predictions from the VEC/PSFE and CALPHAD calculations (depending on the database used) were shown to be quite accurate.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Guide to Current Limiting and Stability with Grid-Forming Inverters

The electric power grid is changing. For many decades, the synchronous generator - an electromechanical device invented in 1887 - has been the workhorse and backbone of power grids across the globe. Our entire infrastructure is built around it. But times change, and so does the power grid. Since the early 21st century, we have seen a gradual shift in modern power grids away from synchronous generators to ones dominated by power electronic inverter-based resources (IBRs). Sources such as photovoltaics, wind turbines, battery storage, fuel cells, and other technologies like high-voltage DC transmission interconnections all rely on an inverter to connect and interface with the grid. They are increasingly being installed on the grid to augment, or even replace, traditional energy sources. This change is a fundamental shift that brings tremendous technical challenges and questions: Can a power grid remain stable with many more inverter-based resources? How do we avoid more blackouts on the grid? How do we keep the grid secure and resilient during disturbances? After all, power electronic inverters are nothing like the big, rotating, iron-and-copper machines that the grid heavily relies on. Many of these questions can be answered by using grid-forming (GFM) inverters, yet many research challenges remain. This document explores GFM inverters and how they can help stabilize the future grid, especially during disturbances and contingencies. It summarizes a two-year research and development fellowship program at NREL. We point interested readers to more detailed works developed during the project along the way. Let's dive in

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Tuning Enzyme Thermostability via Computationally Guided Covalent Stapling and Structural Basis of Enhanced Stabilization

Enhancing the thermostability of enzymes without impacting their catalytic function represents an important yet challenging goal in protein engineering and biocatalysis. We recently introduced a novel method for enzyme thermostabilization that relies on the computationally guided installation of genetically encoded thioether “staples” into a protein via cysteine alkylation with the noncanonical amino acid O-2-bromoethyl tyrosine (O2beY). Here, we demonstrate the functionality of an expanded set of electrophilic amino acids featuring chloroacetamido, acrylamido, and vinylsulfonamido side-chain groups for protein stapling using this strategy. Using a myoglobin-based cyclopropanase as a model enzyme, our studies show that covalent stapling with pchloroacetamido-phenylalanine (pCaaF) provides higher stapling efficiency and enhanced stability (thermodynamic and kinetic) compared to the other stapled variants and the parent protein. Interestingly, molecular simulations of conformational flexibility of the cross-links show that the pCaaF staple allows fewer energetically feasible conformers than the other staples, and this property may be a broader indicator of stability enhancement. Using this strategy, pCaaF-stapled variants with significantly enhanced stability against thermal denaturation (ΔT m ' = +27 °C) and temperature-induced heme loss (ΔT 50 = +30 °C) were obtained while maintaining high levels of catalytic activity and stereoselectivity. Crystallographic analyses of singly and doubly stapled variants provide key insights into the structural basis for stabilization, which includes both direct interactions of the staples with protein residues and indirect interactions through adjacent residues involved in heme binding. This work expands the toolbox of protein stapling strategies available for protein stabilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Navigating thermal stability intricacies of high-nickel cathodes for high-energy lithium batteries

High-nickel oxide cathodes, LiNi x M 1−x O 2 (x ≥ 0.8), are preferred in automotive lithium batteries, but they face thermal instability challenges. Inconsistent literature reports and unstandardized testing protocols further complicate quantitative assessments of the thermal stability of these cathodes. Here, we present here a statistical thermal analysis based on the differential scanning calorimetry measurements of 15 representative cathode materials with different compositions, morphologies and states of charge. The findings reveal that each cathode has a critical state of charge that defines its safe operating limit, which is affected by the metal–oxygen bond strength and surface reactivity. The thermal runaway temperature is dictated by the layered Li 1−x NiO 2 to LiNi 2 O 4 spinel-like phase transition, which is thermodynamically determined by the metal–oxygen bond covalency and kinetically influenced by the cation mixing and particle size. Raman spectroscopy is used to predict the thermal runaway temperature on the basis of the linear relationship between them. Finally, we propose a thermal stability index to quantify cathode thermal stability as a guide for developing safer high-nickel cathodes.

batteries↗
DOE OSTI2024

Cryogenic platform to investigate strong microwave cavity-spin coupling in correlated magnetic materials

We present a comprehensive exploration of loop-gap resonators for electron spin resonance (ESR) studies, enabling investigations into the hybridization of solid-state magnetic materials with microwave polariton modes. The experimental setup, implemented in a Physical Property Measurement System by Quantum Design, allows for measurements of ESR spectra at temperatures as low as 2 Kelvin. The versatility of continuous wave ESR spectroscopy is demonstrated through experiments on CuSO 4 •5H 2 O and MgCr 2 O 4 , showcasing the g-tensor and magnetic susceptibilities of these materials. The study delves into the challenges of fitting spectra under strong hybridization conditions and underscores the significance of proper calibration and stabilization. The detailed guide provided serves as a valuable resource for laboratories interested in exploring hybrid quantum systems through microwave resonators.

electron spin resonance spectroscopy↗
DOE OSTI2020

Physics-guided machine learning approaches to predict the ideal stability properties of fusion plasmas

One of the biggest challenges to achieve the goal of producing fusion energy in tokamak devices is the necessity of avoiding disruptions of the plasma current due to instabilities. The disruption event characterization and forecasting (DECAF) framework has been developed in this purpose, integrating physics models of many causal events that can lead to a disruption. Two different machine learning approaches are proposed to improve the ideal magnetohydrodynamic (MHD) no-wall limit component of the kinetic stability model included in DECAF. First, a random forest regressor (RFR), was adopted to reproduce the DCON computed change in plasma potential energy without wall effects for a large database of equilibria from the national spherical torus experiment (NSTX). This tree-based method provides an analysis of the importance of each input feature, giving an insight into the underlying physics phenomena. Secondly, a fully-connected neural network has been trained on sets of calculations with the DCON code, to get an improved closed form equation of the no-wall β limit as a function of the relevant plasma parameters indicated by the RFR. The neural network has been guided by physics theory of ideal MHD in its extension outside the domain of the NSTX experimental data. The estimated value has been incorporated into the DECAF kinetic stability model and tested against a set of experimentally stable and unstable discharges. Moreover, the neural network results were used to simulate a real-time stability assessment using only quantities available in real-time. Finally, the portability of the model was investigated, showing encouraging results by testing the NSTX-trained algorithm on the mega ampere spherical tokamak (MAST).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum ↗
DOE OSTI2021

Gyrokinetic and extended-MHD simulations of a flow shear stabilized Z-pinch experiment

Axisymmetric (m = 0) gyrokinetic and extended-MHD simulations of a sheared-flow Z-pinch plasma are performed with the high-order finite volume code COGENT. The present gyrokinetic model solves the long-wavelength limit of the gyrokinetic equation for both ion and electron species coupled to the electrostatic gyro-Poisson equation for the electrostatic potential. The extended-MHD model is electromagnetic and includes the effects of the gyro-viscous pressure tensor, diamagnetic electron and ion heat fluxes, and generalized Ohm's law. Additionally, a prominent feature of this work is that the radial profiles for the plasma density and temperature are taken from the fusion Z-pinch experiment (FuZE), and the magnetic field profile is obtained as a solution of the MHD force balance equation. Such an approach allows to address realistic plasma parameters and provide insights into the current and planned experiments. In particular, it is demonstrated that the radial profiles play an important role in stabilization, as the embedded guiding center (E×B ) drift has a strong radial shear, which can contribute to the Z-pinch stabilization even in the absence of the fluid flow shear. The results of simulations for the FuZE plasma parameters show a decrease in the linear growth rate with an increase in the flow shear; however, full stabilization in the linear regime is not observed even for large (comparable to the Alfvén velocity) radial variations of the axial flow. Nonlinear stability properties of the FuZE plasmas are also studied, and it is found that profile broadening can have a pronounced stabilizing effect in the nonlinear regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

The Role of Demixing and Crystallization Kinetics on the Stability of Non‐Fullerene Organic Solar Cells

Abstract With power conversion efficiency now over 17%, a long operational lifetime is essential for the successful application of organic solar cells. However, most non‐fullerene acceptors can crystallize and destroy devices, yet the fundamental underlying thermodynamic and kinetic aspects of acceptor crystallization have received limited attention. Here, room‐temperature (RT) diffusion coefficients of 3.4 × 10 −23 and 2.0 × 10 −22 are measured for ITIC‐2Cl and ITIC‐2F, two state‐of‐the‐art non‐fullerene acceptors. The low coefficients are enough to provide for kinetic stabilization of the morphology against demixing at RT. Additionally profound differences in crystallization characteristics are discovered between ITIC‐2F and ITIC‐2Cl. The differences as observed by secondary‐ion mass spectrometry, differential scanning calorimetry (DSC), grazing‐incidence wide‐angle X‐ray scattering, and microscopy can be related directly to device degradation and are attributed to the significantly different nucleation and growth rates, with a difference in the growth rate of a factor of 12 at RT. ITIC‐4F and ITIC‐4Cl exhibit similar characteristics. The results reveal the importance of diffusion coefficients and melting enthalpies in controlling the growth rates, and that differences in halogenation can drastically change crystallization kinetics and device stability. It is furthermore delineated how low nucleation density and large growth rates can be inferred from DSC and microscopy experiments which could be used to guide molecular design for stability.

Hu, Huawei↗
DOE OSTI2021

A Bayesian Framework for Milling Stability Prediction and Reverse Parameter Identification

This paper describes a physics-guided Bayesian framework for identifying the milling stability boundary and system parameters through iterative testing. Prior uncertainties for the parameters are identified through physical simulation and literature reviews, without physical testing of the actual milling system. Those uncertainties are then propagated to the stability map using a physics-based stability model, which is used to suggest a test point. The uncertainties are updated based on the new information acquired from the cutting test to form a new probability distribution, called the posterior. Finally, the posterior are compared to measured values for the stability boundary and system parameters to evaluate the approach. Based on experimental observations, the advantages and disadvantages of using a physics-guided model are discussed.

Cornelius, Aaron↗
DOE OSTI2022

Structure-based design of prefusion-stabilized human metapneumovirus fusion proteins

The human metapneumovirus (hMPV) fusion (F) protein is essential for viral entry and is a key target of neutralizing antibodies and vaccine development. The prefusion conformation is thought to be the optimal vaccine antigen, but previously described prefusion F proteins expressed poorly and were not well stabilized. Here, we use structures of hMPV F to guide the design of 42 variants containing stabilizing substitutions. Through combinatorial addition of disulfide bonds, cavity-filling substitutions, and improved electrostatic interactions, we describe a prefusion-stabilized F protein (DS-CavEs2) that expresses at 15mg/L and has a melting temperature of 71.9°C. Crystal structures of two prefusion-stabilized hMPV F variants reveal that antigenic surfaces are largely unperturbed. Importantly, immunization of mice with DS-CavEs2 elicits significantly higher neutralizing antibody titers against hMPV A1 and B1 viruses than postfusion F. The improved properties of DS-CavEs2 will advance the development of hMPV vaccines and the isolation of therapeutic antibodies.

59 BASIC BIOLOGICAL SCIENCES↗