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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Broadband THz Modulation via Solid–State Organic Electrochemical Devices

The sub-Terahertz and Terahertz bands play a critical role in next-generation wireless communication and sensing technologies, thanks to the large amount of available bandwidth in this spectral regime. While long-wavelength (microwave to mm-Wave) and short-wavelength (near-infrared to ultraviolet) devices are well-established and studied, the sub-THz to THz regime remains relatively underexplored and underutilized. Traditional approaches used in the aforementioned spectral regions are more difficult to replicate in the THz band, leading to the need for the development of novel devices and structures that can manipulate THz radiation effectively. Herein a novel organic, solid-state electrochemical device is presented, capable of achieving modulation depths of over 90% from ≈500 nm of a conducting polymer that switches conductivity over a large dynamic range upon application of an electronically controllable external bias. The stability of such devices under long-term, repeated voltage switching, as well as continuous biasing at a single voltage, is also explored. Switching stabilities and long-term bias stabilities are achieved over two days for both use cases. Additionally, both depletion mode (always “ON”) and accumulation mode (always “OFF”) operation are demonstrated. These results suggest applications of organic electrochemical THz modulators in large area and flexible implementations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The developments in modifying functionality of lignin and its application in biocomposites

With the advancement of sustainable material innovations, renewable natural biopolymers are gradually replacing traditional metal and petroleum-based synthetic materials due to their environmental friendliness, biodegradability, and economic advantages. Lignin, the second most abundant natural aromatic polymer in the plant kingdom, has emerged as a key candidate raw material for the development of green polymer systems because of its unique phenylpropane unit network structure, high carbon content, and rich functional group characteristics. However, challenges such as the inherent structural complexity, chemical inertness, and uneven molecular weight distribution of lignin limit its direct application. By employing modification strategies such as chemical functionalization and physical regulation, researchers can precisely control its reactivity, thermal stability, and interfacial compatibility, enabling the preparation of high-performance lignin-based functional composites. Here, this paper systematically reviews the principles and methodological advancements in lignin's multi-dimensional modification technology. It analyzes the mechanisms by which various chemical and physical modification techniques enhance the mechanical properties, functional responsiveness, and environmental adaptability of materials, and discusses innovative applications in fields such as intelligent packaging, biomedical materials, and energy storage devices. Furthermore, this review addresses the key challenges encountered in the high-value transformation of lignin, with the aim of offering a theoretical framework and technical pathway for the transformative development of lignin from agricultural and forestry by-products to functional material platforms.

Functional composites↗
DOE OSTI2026

Phase-field approach to cellular blebbing

Bulges in the plasma membrane of cells known as blebs can form spontaneously in a wide range of biological processes, but what controls their shape and stability remains incompletely understood. Here, to address this we introduce a dual phase-field model with coupled order parameters representing the cell cortex and plasma membrane that can quantitatively model blebbing in three dimensions. Simulations and sharp-interface analyses reveal that, depending on whether blebbing occurs by detachment of the plasma membrane or rupture of the actin cortex, blebs can form discontinuously through a saddle-node bifurcation or continuously with increasing cortical tension. The model predictions are in good quantitative agreement with existing experimental data for laser-induced cortex rupture.

Biological and medical sciences↗
DOE OSTI2025

Temperature and Strain Sensing Characteristics of a 128° YX-Cut LiNbO 3 Rayleigh-Mode SAW Sensor From Room to Cryogenic Temperatures

Accurate, passive, and wireless monitoring of cryogenic hardware is essential for high-energy physics, space propulsion, and biomedical instrumentation. Here, this study quantifies the coupled temperature-strain behavior of Rayleigh-mode surface acoustic-wave (SAW) delay-line sensors fabricated on 128° YX-cut LiNbO 3 . A nonlinear finite element (FE) model incorporating Varshni-based elastic constants, higher-order thermal expansion, and temperature-dependent piezo- and dielectric coefficients was developed and validated experimentally between 280K and 80K. Free-standing (first test condition) and bonded/wired (second test condition) devices exhibited indistinguishable thermal responses; the average temperature coefficient of delay (TCD) in the critical cryogenic range from 130K down to 80K differed by only 0.15 ppm/K (0.32%), confirming that bonding-induced stress is negligible. Over 280-80K the measured TCD was 61.77 ppm/K, while the FE model predicted an equivalent temperature coefficient of frequency (TCF) of −62.74 ppm/K with an overall coefficient of determination R2 = 0.998. In the critical cryogenic interval 130-80K the TCD fell to 47.66 ppm/K, indicating improved thermal stability at low temperature. Controlled loading (0-300 με) revealed a strain coefficient of delay (SCD) that rises from 0.53 ± 0.02 ppm/με at 300K to 1.05 ± 0.02 ppm/με at 80K. This modest sensitivity confirms that, for temperature sensing, strain is a second-order perturbation above 135K but must be compensated at deeper cryogenic levels. Overall, this work establishes a predictive multiphysics model together with repeatable wired measurements that confirm the suitability of SAW sensors for temperature and strain monitoring in extreme cryogenic environments, while also providing a baseline for future wireless implementations.

25 ENERGY STORAGE↗
DOE OSTI2025

Distribution of nickel(II) ions adsorbed at the muscovite mica (001)-water interface determined by in-situ resonant anomalous X-ray reflectivity

Mineral-water interfaces mediate adsorption, ion exchange, and secondary mineral formation that control element mobility in natural and engineered systems. Reliable prediction and control of these processes require a fundamental understanding of the interfacial structure that links adsorbed ion speciation to macroscopic sorption capacity and strength. Here, we determine atomic-scale changes in hydration and distribution of Ni(II) at the muscovite mica (001)-water interface using in situ high-resolution X-ray reflectivity (XR) and resonant anomalous X-ray reflectivity (RAXR) at 1 mM NiCl2 and pH 5.7. XR reveals reorganization of the primary hydration structure relative to that in deionized water: the water layer adsorbed in the cavity sites at a height of ~1.3 Å disappears, while distinct solution layers emerge at ~2.3, ~4.1, and ~5.6 Å above the basal oxygen plane. RAXR resolves three interfacial Ni(II) species: a dominant outer-sphere complex at 3.65 Å (~80% of the total coverage), a minor inner-sphere complex at 0.75 Å, and a low-coverage, more distant outer-sphere species at 5.63 Å. These three adsorbed Ni(II) species account for a total Ni(II) coverage of 0.54 ± 0.02 ion per unit cell area that compensates for the surface charge. These results highlight the role of interfacial hydration in controlling the speciation and stability of adsorbate cations on the negatively charged mica surface, providing quantitative insight into predicting the geochemical behavior of divalent metal cations in the aqueous environments.

Lee, Sang Soo↗
DOE OSTI2024

Introduction to Grid Forming Inverters: A Key to Transforming our Power Grid [Slides]

A grid-forming (GFM) inverter-based resource (IBR) controls maintain an internal voltage phasor that is constant or nearly constant in the sub-transient to transient time frame. This definition means that the GFM IBR will nearly immediately respond to changes in the external system and attempt to maintain IBR control during challenging network conditions to maintain grid stability. In GFM IBR, the voltage phasor is controlled to maintain synchronism with other devices in the grid while regulating the active and reactive power appropriately to support the grid. This contrasts with conventional GFL IBR controls wherein immediately after a disturbance (0-5 cycles), within the normal operating range of voltage, the output current phasor magnitude and angle remain unchanged, and the current phasor begins changing only within the transient time frame (tens of cycles) to strictly control the active and reactive power being injected into the network. This presentation gives an introduction to GFM IBR and presents the current state of the art in this area.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

PIP-II LLRF Master Oscillator and Precision Reference Line - Station Level Design and Testing

The PIP-II superconducting linac at Fermilab requires a highly stable RF Reference Line to maintain phase syn- chronization throughout the accelerator. Temperature- induced changes in the electrical length of long coaxial cables can introduce phase drift and measurement errors. The reference-line architecture mitigates these effects by phase averaging the forward and reflected RF signals, while a phase-locked loop anchors the system to the mas- ter oscillator. This work focuses on the characterization, validation, and mechanical integration of station-level RF assemblies using CAD modeling, vector network analyzer measurements, and spectrum analyzer testing. PID-controlled thermal plates will stabilize critical RF components and further reduce temperature-dependent phase and amplitude variations. These methods sup- port repeatable, standardized designs that can be reliably integrated across the different reference-line stations.

Mosher, Alexander [U. Illinois, Chicago]↗
DOE OSTI2025

Toward Thermally Stimuli-Responsive Polymeric Vesicles Fabricated by Block Copolymer Blends for Nanocarriers

Polymeric vesicles, characterized by enhanced colloidal stability, excellent mechanical properties, controllable surface functionality, and adjustable membrane thickness, are extremely useful in nano- and bio-technology for potential applications as nanosized carriers for drugs and enzymes. However, a few preparative steps are necessary to achieve a unilamellar vesicle with a narrow size distribution. Herein, we report the spontaneous formation of unilamellar polymeric vesicles with nanometer sizes (<50 nm), fabricated by simply mixing diblock copolymers (P(EO-AGE)(2K-2K) and P(EO-AGE)(0.75K-2K)) with differing hydrophilic mass fractions in aqueous solutions. Depending on the mixing ratio of block copolymers and the temperature, the block copolymer mixtures self-assemble into various nanostructures, such as spherical and cylindrical micelles, or vesicles. The self-assembled structures of the block copolymer mixtures were characterized by small-angle neutron scattering, resulting in a phase diagram drawn as a function of temperature and the mixing condition. Notably, the critical temperature for the micelle-to-vesicle phase transition can be easily controlled by altering the mixing conditions; it decreases with an increase in the concentration of one of the block copolymers.

block copolymers↗
DOE OSTI2026

PIP-II LLRF Master Oscillator and Precision Reference Line- Station Level Design and Testing

The PIP-II superconducting linac at Fermilab requires a highly stable RF Reference Line to maintain phase synchronization throughout the accelerator. Temperature-induced changes in the electrical length of long coaxial cables can introduce phase drift and measurement errors. The reference-line architecture mitigates these effects by phase averaging the forward and reflected RF signals, while a phase-locked loop anchors the system to the master oscillator. This work focuses on the characterization, validation, and mechanical integration of station-level RF assemblies using CAD modeling, vector network analyzer measurements, and spectrum analyzer testing. PID-controlled thermal plates will stabilize critical RF components and further reduce temperature-dependent phase and amplitude variations. These methods support repeatable, standardized designs that can be reliably integrated across the different reference-line stations.

Mosher, Alexander [U. Illinois, Chicago; Fermilab]↗
DOE OSTI2024

Spin disorder control of topological spin texture

Abstract Stabilization of topological spin textures in layered magnets has the potential to drive the development of advanced low-dimensional spintronics devices. However, achieving reliable and flexible manipulation of the topological spin textures beyond skyrmion in a two-dimensional magnet system remains challenging. Here, we demonstrate the introduction of magnetic iron atoms between the van der Waals gap of a layered magnet, Fe 3 GaTe 2 , to modify local anisotropic magnetic interactions. Consequently, we present direct observations of the order-disorder skyrmion lattices transition. In addition, non-trivial topological solitons, such as skyrmioniums and skyrmion bags, are realized at room temperature. Our work highlights the influence of random spin control of non-trivial topological spin textures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design and Analysis of an Integral MPPT Control Law for Wave Energy Conversion Systems

In this paper, we propose an integral-based maximum power point tracking (MPPT) algorithm for point absorber wave energy conversion (WEC) systems. A permanent magnet synchronous generator (PMSG) is coupled to the point absorber and its drive implements the proposed MPPT control. While the rotating frame of reference of the PMSG implements power control, the slower mechanical frequency of the incident waves are processed with an additional transformation that yields another set of dc dynamics. The computed dc power in the new reference frame, which is focused on slow wave dynamics, is input to the MPPT control law that tunes the emulated resistance of the machine drive to extract peak power from the wave absorber device. We derive a stability condition for the proposed controller and validate our control design on a simulated 10kW system.

wave energy, maximum power point tracking (MPPT), ↗
DOE OSTI2024

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

The increasing penetration of converter-based renewable generation has resulted in faster frequency dynamics, and low and variable inertia. As a result, there is a need for frequency control methods that are able to stabilize a disturbance in the power system at timescales comparable to the fast converter dynamics. This paper proposes a combined linear and neural network controller for inverter-based primary frequency control that is stable at time-varying levels of inertia. We model the time-variance in inertia via a switched affine hybrid system model. We derive stability certificates for the proposed controller via a quadratic candidate Lyapunov function. We test the proposed control on a 12-bus 3-area test network, and compare its performance with a base case linear controller, optimized linear controller, and finite-horizon Linear Quadratic Regulator (LQR). Our proposed controller achieves faster mean settling time and over 50% reduction in average control cost across 100 inertia scenarios compared to the optimized linear controller. Unlike LQR which requires complete knowledge of the inertia trajectories and system dynamics over the entire control time horizon, our proposed controller is real-time tractable, and achieves comparable performance to LQR.

data-driven control↗
DOE OSTI2025

Diffusion of acceptor dopants in monoclinic 𝛽−Ga 2⁢ O 3

𝛽−Ga 2 ⁢O 3 is a promising material for next-generation power electronics because of its ultrawide band gap and high critical breakdown voltage. However, realizing its full potential requires precise control over dopant incorporation and stability. In this work, we use first-principles calculations to systematically assess the diffusion behavior of eight potential deep-level substitutional acceptors (Au, Ca, Co, Cu, Fe, Mg, Mn, and Ni) in 𝛽−Ga 2 ⁢O 3 . We consider two key diffusion mechanisms: (i) interstitial diffusion under nonequilibrium conditions relevant to ion implantation, and (ii) trap-limited diffusion (TLD) under near-equilibrium thermal annealing conditions. Our results reveal a strong diffusion anisotropy along the 𝑏 and 𝑐 axes, with dopant behavior governed by competition between diffusion and incorporation (or dissociation) activation energies. Under interstitial diffusion, Ca$^{2+}_{i}$ and Mg$^{2+}_{i}$ show the most favorable combination of low migration and incorporation barriers, making them promising candidates for efficient doping along the 𝑏 and 𝑐 axes, respectively. In contrast, Au$^{+}_{i}$ diffuses readily, but exhibits an incorporation barrier that exceeds 5 eV, rendering it ineffective as a dopant. From a thermal stability perspective, Co$^{2+}_{i}$ shows poor activation but high diffusion barriers, which may suppress undesirable migration at elevated temperatures. Under trap-limited diffusion, the dissociation of dopant-host complexes controls mobility. Mg$^{2+}_{i}$ again emerges as a leading candidate, exhibiting the lowest dissociation barriers along both axes, whereas Co$^{2+}_{i}$ and Fe$^{2+}_{i}$ display the highest barriers, suggesting improved dopant retention under thermal stress. In conclusion, our findings guide dopant selection by balancing activation and thermal stability, essential for robust semi-insulating substrates.

Defects↗
DOE OSTI2025

Characterization of Impedance and Stability for Doubly-Fed Induction Generator Based on Voltage-Modulated Direct Power Control

Voltage-modulated direct power control (VM-DPC) applied to the doubly-fed induction generator (DFIG) offers superior steady-state and transient performance but remains underexplored for suppressing wideband oscillations. Here, this article proposes a comprehensive impedance for the VM-DPC-based DFIG, analyzing its impedance characteristics and stability mechanisms compared with the DFIG based on vector-oriented control (VOC). The unified power transfer function is defined for DFIGs employing VM-DPC or VOC to ensure consistent comparison benchmarks. The comprehensive impedance of VM-DPC-based DFIG, incorporating mechanical and grid-side converter (GSC) dynamics, is derived using complex vector modeling in the αβ -frame. Furthermore, the influence of VM-DPC parameters and grid strength on the stability of grid-connected DFIG systems is assessed through eigenvalue trajectory analysis. Impedance analysis reveals the significant contributions of mechanical and GSC dynamics to DFIG impedance, as well as the narrower frequency range of negative resistance in the VM-DPC-based DFIG compared to the VOC-based DFIG. Stability analysis identifies the VM-DPC parameters of the rotor-side converter as dominant factors affecting system stability and confirms that the VM-DPC-based DFIG achieves better stability under weak grid conditions than its VOC-based counterpart. These findings are validated through simulations and experiments.

42 ENGINEERING↗
DOE OSTI2024

Lyapunov-based nonlinear control of nonautonomous systems with individual input constraints

A control algorithm that can locally stabilize a specific class of multi-input multi-output nonautonomous nonlinear dynamical systems while satisfying individual input constraints is developed. The proposed Lyapunov-based state-feedback control law inherently accounts for the actuator amplitude saturation limits without the need for computationally expensive real-time optimization techniques. In addition to the control law, a formal definition for the local “controllable region” within which the controller can asymptotically drive the system states to the origin and satisfy the input saturation limits is also presented. The nonautonomous nature of the system dynamics implies that the “controllable region” continuously evolves with time. Therefore, a sufficient condition to maintain the system states within the “controllable region” is proposed in this work to make practical implementation feasible. The effectiveness of the controller is tested for a specific control problem arising in tokamaks, which are toroidal devices that use strong magnetic fields to confine a plasma (hot ionized gas). Here, the primary emphasis of tokamak research is to regulate the plasma properties around predetermined values to achieve stable plasma confinement. Nonlinear simulations show that the proposed controller can achieve the desired plasma control objectives in a DIII-D tokamak scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

Abstract mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Cetnar, Daniel P.↗
DOE OSTI2026

Small-Signal Stability of Grid-Forming Converters Under Fault Conditions

Threshold virtual impedance (TVI)-based current limiting for grid-forming converters (GFMs) has gained great interest due to its ability to maintain voltage source behaviour during faults. However, sequence component extraction (SCE) and negative-sequence control (NSC) are often overlooked in small-signal stability assessments during faults. This paper develops small-signal sequence impedance models for GFMs under four well-known SCE methods based on TVI current limiting control during symmetrical fault conditions. Using the developed impedance models, the impacts of SCE and NSC, and the voltage and current control loop bandwidths, on system stability during faults are investigated. Additionally, since negative-sequence TVI (TVI-) is typically added along with its positive-sequence counterpart, which is often inductive, inductive and resistive TVI- are examined. The findings suggest that a higher voltage or current control loop bandwidth has a negative impact on system stability, while SCE and NSC largely reduce the stable range for voltage and current control loop bandwidth during faults, and that the severity of such impacts is determined by the particular SCE method. Furthermore, it is observed that inductive TVI- significantly degrades system stability, while resistive TVI- can enhance stability when suitable SCE methods are appropriately selected and designed. Matlab/Simulink electromagnetic transient simulations validate these analytical results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

AutoFocus: AI/ML-driven real-time wavefront diagnostics to autonomously align and optimize X-ray optics

We present an integrated system that combines advanced wavefront diagnostics with artificial intelligence (AI) to automate and optimize X-ray optics at synchrotron beamlines. This system couples real-time wavefront sensing with AI-driven control algorithms to achieve precise beam alignment, stabilization, and performance optimization. A key feature is the use of multi-fidelity transfer learning, which enables knowledge gained from both real-world beamline optimizations and ultra-realistic digital twin simulations to be effectively applied to in situ optimization. By leveraging multi-objective bayesian optimization, the system continuously refines its performance, reducing optimization time and minimizing the need for manual adjustments. Designed for seamless deployment, it operates with existing beamline hardware and provides an intuitive graphical interface. Initial deployments at the advanced photon source beamlines have demonstrated its ability to enhance beam stability, improve reproducibility, and significantly streamline alignment procedures. This AI-enhanced control framework represents a significant step toward fully autonomous beamline operation in next-generation synchrotron facilities.

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗