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DOE OSTI2025

Autonomous Synthesis of Metastable Materials Using a Modular Mixed-Flow Reactor

Understanding and controlling atomic-level processes at solid-liquid interfaces is key to advancing technologies in energy storage, carbon capture, critical element recovery, and materials synthesis. Many of these processes are dominated by the formation of short-lived intermediate precipitates that determine the final properties of synthesized materials. However, studying these intermediates is challenging due to their sensitivity and the reliance on trial-and-error methods. To address this, we developed an automated variable-volume mixed-flow reactor (MFR) to optimize metastable material synthesis and investigate rapid kinetic processes. This state-of-the-art MFR system, paired with an automated modeling framework, enables efficient synthesis and real-time analysis of transient phases. Benchmarking with advanced capabilities, such as wide-/small-angle X-ray scattering, allows us to resolve fast nucleation and growth dynamics that were previously inaccessible. By combining automation, ML-guided optimization, and tailored kinetic modeling, this approach provides a robust platform for improving material design and achieving precise control over solid-liquid reactions.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Design of high performance multivariable control systems for supermaneuverable aircraft at high angle of attack

The main motivation for the work under the present grant was to use nonlinear feedback linearization methods to further enhance performance capabilities of the aircraft, and robustify its response throughout its operating envelope. The idea was to use these methods in lieu of standard Taylor series linearization, in order to obtain a well behaved linearized plant, in its entire operational regime. Thus, feedback linearization was going to constitute an 'inner loop', which would then define a 'design plant model' to be compensated for robustness and guaranteed performance in an 'outer loop' application of modern linear control methods. The motivation for this was twofold; first, earlier work had shown that by appropriately conditioning the plant through conventional, simple feedback in an 'inner loop', the resulting overall compensated plant design enjoyed considerable enhancement of performance robustness in the presence of parametric uncertainty. Second, the nonlinear techniques did not have any proven robustness properties in the presence of unstructured uncertainty; a definition of robustness (and performance) is very difficult to achieve outside the frequency domain; to date, none is available for the purposes of control system design. Thus, by proper design of the outer loop, such properties could still be 'injected' in the overall system.

Valavani, Lena↗

DOE OSTI2020

Nonlinear optical control of chiral charge pumping in a topological Weyl semimetal

Solids with topologically robust electronic states exhibit unusual electronic and optical properties that do not exist in other materials. A particularly interesting example is chiral charge pumping, the so-called chiral anomaly, in recently discovered topological Weyl semimetals, where simultaneous application of parallel DC electric and magnetic fields creates an imbalance in the number of carriers of opposite topological charge (chirality). Here, using time-resolved terahertz measurements on the Weyl semimetal TaAs in a magnetic field, we optically interrogate the chiral anomaly by dynamically pumping the chiral charges and monitoring their subsequent relaxation of the nonequilibrium state. Theory based on Boltzmann transport shows that the observed effects originate from an optical nonlinearity in the chiral charge pumping process. Our measurements reveal that the nonequilibrium chiral excitation relaxation time is much greater than 1 ns. The observation of terahertz-controlled chiral carriers with long coherence times and topological protection suggests the application of Weyl semimetals for quantum optoelectronic technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Low- n stability and plasma response to RMP in various STEP scenarios

The low-n (n is the toroidal mode number) magnetohydrodynamic (MHD) stability and plasma response are numerically investigated for various scenarios designed for STEP, that are relevant for the H-mode pedestal analysis. Control of the edge-localized modes (ELMs) with externally applied resonant magnetic perturbations (RMPs) is considered. Optimization of the ELM control coil current configuration, based on the computed plasma MHD response and well-established figures of merit validated on present-day experiments, finds reasonable robustness of a fixed coil phasing (for a given n-number) to control ELMs in all five STEP plasmas considered. Based on certain semi-empirical criteria, the required coil current to achieve ELM suppression is estimated to be about 10–20 kAt with the n = 1 or 2 RMP configuration and about 100–200 kAt for the n = 4 RMP. Systematic linear stability calculations are used to map out stability windows for the low-n kink-peeling modes, in terms of the ideal-wall location and variation of the edge safety factor q 95 with respect to the target design. The kink-peeling stability boundary is found to be generally sensitive to the q 95 variation, which has implications for achieving the quiescent H-mode regime in STEP. Full toroidal quasilinear initial-value simulations for these STEP plasmas find that generation of the edge-harmonic oscillations (EHOs) depends sensitively on the plasma scenario, the initial linear stability of the kink-peeling modes, the initial plasma toroidal flow and q 95 . In general, it is easier (more robust) to access the EHO-regime for two of the cases considered with smaller plasma volume and higher on-axis safety factor. Finally, quasilinear simulations find robust density pumpout due to applied RMPs in these STEP plasmas, but the effect on the plasma toroidal flow varies among different cases.

EHO↗

DOE OSTI2020

Topological nanophotonics for photoluminescence control

Rare-earth-doped nanocrystals are emerging light sources that can produce tunable emissions in colours and lifetimes, which has been typically achieved in chemistry and material science. However, one important optical challenge – polarization of photoluminescence – remains largely out of control by chemistry methods. Control over photoluminescence polarization can be gained via coupling of emitters to resonant nanostructures such as optical antennas and metasurfaces. However, the resulting polarization is typically sensitive to position disorder of emitters, which is difficult to mitigate. Recently, new classes of disorder-immune optical systems have been explored within the framework of topological photonics. Here we explore disorder-robust topological arrays of Mie-resonant nanoparticles for polarization control of photoluminescence of nanocrystals. We demonstrate polarized emission from rare-earth-doped nanocrystals governed by photonic topological edge states supported by zigzag arrays of dielectric resonators. We verify the topological origin of polarized photoluminescence by comparing emission from nanoparticles coupled to topologically trivial and nontrivial arrays of nanoresonators. We expect that our results may open a new direction in the study of topology-enable emission properties of topological edge states in many photonic systems.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Control concepts for active magnetic bearings

Active Magnetic Bearings (AMB) are becoming increasingly significant for various industrial applications. Examples are turbo-compressors, centrifuges, high speed milling and grinding spindles, vibration isolation, linear guides, magnetically levitated trains, vacuum and space applications. Thanks to the rapid progress and drastic cost reduction in power- and micro-electronics, the number of AMB applications is growing very rapidly. Industrial uses of AMBs leads to new requirements for AMB-actuators, sensor systems, and rotor dynamics. Especially desirable are new and better control concepts to meet demand such as low cost AMB, high stiffness, high performance, high robustness, high damping up to several kHz, vibration isolation, force-free rotation, and unbalance cancellation. This paper surveys various control concepts for AMBs and discusses their advantages and disadvantages. Theoretical and experimental results are presented.

Siegwart, Roland↗

DOE OSTI2026

Octave-spanning terahertz quarter-wave plates based on over-coupled Fabry–Pérot resonances in reflective metal–dielectric–metal metasurfaces

Compact devices for broadband polarization control in the terahertz (THz) regime remain challenging to realize due to the intrinsic phase dispersion associated with birefringent materials and resonant structures. Here, we demonstrate achromatic THz quarter-wave plates with near-unity efficiency and operating under a wide range of incidence angles, based on over-coupled metal–dielectric–metal reflective metasurfaces. The devices operate as single-port anisotropic Fabry–Pérot cavities, in which the phase dispersion of the over-coupled resonances is engineered to maintain an approximately constant relative phase delay between orthogonal field components over a broad frequency range. Four complementary metasurface designs operating at an incidence angle of 45° collectively cover the 0.25–3 THz frequency range accessible to a typical THz time-domain spectroscopy system. Each device exhibits an approximately octave-wide operational bandwidth, with axial ratios below 3 dB and polarization-conversion efficiencies exceeding 80% across most of the operating band. Systematic structural optimization suppresses coupling to diffraction and guided-wave modes, thereby further extending the usable bandwidth while preserving the required phase relationship between orthogonal polarizations. The demonstrated metasurfaces are compatible with wafer-scale fabrication processes, and experimental results show excellent agreement with simulations. These findings establish over-coupled reflective metasurfaces as a robust, scalable, and versatile platform for broadband THz polarization control.

36 MATERIALS SCIENCE↗

NASA NTRS2000

Robustness of Flexible Systems With Component-Level Uncertainties

Robustness of flexible systems in the presence of model uncertainties at the component level is considered. Specifically, an approach for formulating robustness of flexible systems in the presence of frequency and damping uncertainties at the component level is presented. The synthesis of the components is based on a modifications of a controls-based algorithm for component mode synthesis. The formulation deals first with robustness of synthesized flexible systems. It is then extended to deal with global (non-synthesized ) dynamic models with component-level uncertainties by projecting uncertainties from component levels to system level. A numerical example involving a two-dimensional simulated docking problem is worked out to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗

NASA NTRS1998

Optimal Controller Design for the Microgravity Isolation Mount (MIM)

H2 controllers, when designed using an appropriate design model and carefully chosen frequency weightings, appear to provide robust performance and robust stability for Microgravity Isolation Mount (MIM). The STS-85 flight data will be used to evaluate the H2 controllers' performance on the actual hardware under working conditions. Next, full-order H-infinity controllers will be developed, as an intermediate step, in order to determine appropriate H-infinity performance weights for use in the mixed-norm design. Finally the basic procedure outlined above will be used to develop fixed-order mixed-norm controllers for MIM.

Hampton, R. David↗

NASA NTRS2009

Flight Test Comparison of Different Adaptive Augmentations for Fault Tolerant Control Laws for a Modified F-15 Aircraft

This report describes the improvements and enhancements to a neural network based approach for directly adapting to aerodynamic changes resulting from damage or failures. This research is a follow-on effort to flight tests performed on the NASA F-15 aircraft as part of the Intelligent Flight Control System research effort. Previous flight test results demonstrated the potential for performance improvement under destabilizing damage conditions. Little or no improvement was provided under simulated control surface failures, however, and the adaptive system was prone to pilot-induced oscillations. An improved controller was designed to reduce the occurrence of pilot-induced oscillations and increase robustness to failures in general. This report presents an analysis of the neural networks used in the previous flight test, the improved adaptive controller, and the baseline case with no adaptation. Flight test results demonstrate significant improvement in performance by using the new adaptive controller compared with the previous adaptive system and the baseline system for control surface failures.

Burken, John J.↗

DOE OSTI2020

Modeling and control of cascaded bridgeless multilevel rectifier under unbalanced load conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality. The complete design process of the proposed converter is developed step by step in order to meet all the desired objectives. The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to mathematically derive requirements for the number of partially controlled and fully controlled H-bridges in the proposed H-bridge converter. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. After exploring various well-established control methods, a novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization, power factor correction, and elimination of zero crossing current distortion under both balanced and unbalanced load conditions. The converter can also be used for reactive power compensation in a grid tied power system if a sufficient number of fully controlled H-bridge modules are included. Processor-In-the-Loop (PIL) simulation has been the utilized to validate the performance of discrete control structure. Simulation and experimental results validate the models and control method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Consensus Control (Wind Farm Collective Yaw Control) [SWR-19-11]

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This code implements a framework for implementing an autonomous wind farm that incorporates information from local sensors in real time to better align turbines in a wind farm. Oftentimes, measurements made at an individual turbine are noisy and unreliable. By incorporating measurements from multiple nearby turbines, a more robust estimate of the wind direction can be obtained at an individual turbine. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction and could decrease dynamic yaw misalignment, decrease the amount of time a turbine spends yawing due to a more robust input to the yaw controller, and increase resiliency to faulty wind-vane measurements.

King, Jennifer↗

DOE OSTI2023

Control development and sizing analysis for a 5th generation district heating and cooling network using Modelica

5th generation district heating and cooling system (5GDHC) are a relatively new concept. They use a single district loop near ambient temperature to provide heating and cooling. This paper improves on the modelling and control of a 5GDHC system called the reservoir network. The study updates the sewage heat exchanger plant model to more realistically represent seasonal changes, uses refined pump models with variable efficiency, introduces a ground coupled district pipe model to consider the inertia of the district network and implements a new control strategy for geothermal storage and sewage heat exchanger. The new approach reduced operating costs, mainly due to pumping cost for storage, sewage heat exchanger plant and distribution pump, while increasing the overall robustness of the approach in different sizing conditions. Thanks to the new controller, the pumping consumption was reduced by 21% with respect to the original baseline. Furthermore, the new control makes the system take better advantage of design changes, when reducing borehole field size and increasing the sewage heat exchanger size, the pumping energy savings become 29% with respect to the original baseline. Lastly, borehole field temperature stability was analyzed through 40 years of simulation.

Zanetti, Ettore↗

DOE OSTI2021

Error-Level-Controlled Synthetic Forecasts for Renewable Generation

Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the importance of short-term (hours ahead) renewable generation forecasting in power systems operation, it becomes crucial to address the potential inaccuracies in these forecasts. To systematically evaluate the performance of controllers in the presence of imperfect forecasts, we generate synthetic forecasts using actual renewable generation profiles (one from solar and one from wind). These synthetic forecasts incorporate different levels of statistical error, allowing us to control and manipulate the accuracy of the predictions. The primary objective is to employ synthetic forecasts with controlled yet realistic error levels to systematically investigate how controllers adapt to variations in forecast accuracy, providing valuable insights into their robustness and effectiveness under real-world conditions.

Array↗

NASA NTRS2014

Full Scale Advanced Systems Testbed (FAST): Capabilities and Recent Flight Research

At the NASA Armstrong Flight Research Center research is being conducted into flight control technologies that will enable the next generation of air and space vehicles. The Full Scale Advanced Systems Testbed (FAST) aircraft provides a laboratory for flight exploration of these technologies. In recent years novel but simple adaptive architectures for aircraft and rockets have been researched along with control technologies for improving aircraft fuel efficiency and control structural interaction. This presentation outlines the FAST capabilities and provides a snapshot of the research accomplishments to date. Flight experimentation allows a researcher to substantiate or invalidate their assumptions and intuition about a new technology or innovative approach Data early in a development cycle is invaluable for determining which technology barriers are real and which ones are imagined Data for a technology at a low TRL can be used to steer and focus the exploration and fuel rapid advances based on real world lessons learned It is important to identify technologies that are mature enough to benefit from flight research data and not be tempted to wait until we have solved all the potential issues prior to getting some data Sometimes a stagnated technology just needs a little real world data to get it going One trick to getting data for low TRL technologies is finding an environment where it is okay to take risks, where occasional failure is an expected outcome Learning how things fail is often as valuable as showing that they work FAST has been architected to facilitate this type of testing for control system technologies, specifically novel algorithms and sensors Rapid prototyping with a quick turnaround in a fly-fix-fly paradigm Sometimes it's easier and cheaper to just go fly it than to analyze the problem to death The goal is to find and test control technologies that would benefit from flight data and find solutions to the real barriers to innovation. The FAST vehicle is a flexible laboratory for nascent technologies that would benefit from early life cycle flight research data It provides a robust and safe environment where innovative techniques can be explored in a fly-fix-fly rapid prototyping paradigm IRAC Simple adaptive control technologies can provide real benefits without undo complexity Adverse pilot/adaptive system interactions can be mitigated and tools have been developed to evaluate those interactions ICP Substantial fuel savings can be achieved over a broad range of vehicles and configurations with intelligent control solutions LVAC The AAC design is robust and effective for the SLS mission, and promises to provide benefits to other platforms as well OCLA Hopefully will show that structural feedback can be seamlessly integrated with performance and stability objectives All of these control technologies have been implemented into the same baseline control law and could be combined into one control solution that answers many pressing questions for modern vehicle configurations

flight controls↗

DOE OSTI2025

Contrastive learning for robust representations of neutrino data

In neutrino physics, analyses often depend on large simulated datasets, making it essential for models to generalize effectively to real-world detector data. Contrastive learning, a well-established technique in deep learning, offers a promising solution to this challenge. By applying controlled data augmentations to simulated data, contrastive learning enables the extraction of robust and transferable features. This improves the ability of models trained on simulations to adapt to real experimental data distributions. In this paper, we investigate the application of contrastive learning methods in the context of neutrino physics. Through a combination of empirical evaluations and theoretical insights, we demonstrate how contrastive learning enhances model performance and adaptability. Additionally, we compare it to other domain adaptation techniques, highlighting the unique advantages of contrastive learning for this field. Published by the American Physical Society 2025

Wilkinson, Alex (ORCID:0000000253404506)↗

NASA NTRS2008

Fault-Tolerant, Multiple-Zone Temperature Control

A computer program has been written as an essential part of an electronic temperature control system for a spaceborne instrument that contains several zones. The system was developed because the temperature and the rate of change of temperature in each zone are required to be maintained to within limits that amount to degrees of precision thought to be unattainable by use of simple bimetallic thermostats. The software collects temperature readings from six platinum resistance thermometers, calculates temperature errors from the readings, and implements a proportional + integral + derivative (PID) control algorithm that adjusts heater power levels. The software accepts, via a serial port, commands to change its operational parameters. The software attempts to detect and mitigate a host of potential faults. It is robust to many kinds of faults in that it can maintain PID control in the presence of those faults.

Granger, James↗

NASA NTRS1994

A Novel Approach to Noise-Filtering Based on a Gain-Scheduling Neural Network Architecture

A gain-scheduling neural network architecture is proposed to enhance the noise-filtering efficiency of feedforward neural networks, in terms of both nominal performance and robustness. The synergistic benefits of the proposed architecture are demonstrated and discussed in the context of the noise-filtering of signals that are typically encountered in aerospace control systems. The synthesis of such a gain-scheduled neurofiltering provides the robustness of linear filtering, while preserving the nominal performance advantage of conventional nonlinear neurofiltering. Quantitative performance and robustness evaluations are provided for the signal processing of pitch rate responses to typical pilot command inputs for a modern fighter aircraft model.

Troudet, T.↗