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Results for “Manipulator control”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Renewal: Coherent control of spin states in organic electronics – discovery and investigation of complex room-temperature magnetic quantum excitations

In the course of four funding cycles of this project, its research focused on the exploration and understanding of spin-dependent electronic processes in organic semiconductors. It aimed to investigate the potential of harnessing the spin degree of freedom in organic materials for various applications such as spin electronics, quantum information, sensors, and as well as quantum coherent spin phenomena of charge carrier states in organic semiconductors, with the aim to develop room-temperature-based quantum applications. Specifically, the project aimed to: Apply new diagnostic tools, i.e. spin spectroscopy techniques, for paramagnetic charge carrier states in organic semiconductors, based on coherent control with pulsed electron spin resonance to understand spin relaxation and spin mixing mechanisms in organic semiconductor materials and devices such as OLEDs. Explore the nature of charge carrier spin-coupling and pathways for its manipulation to control the physical behaviors of these materials. This involves investigating spin interactions through materials structure, composition, morphological dependencies, isotopic effects, and externally applied electric and magnetic fields, with the goal to manipulate electrical and optical material properties by adjusting spin-orbit, spin-dipolar, spin-exchange, as well as spin-hyperfine interactions to open up this materials class for new applications. Study spin-dependent charge carrier transport and recombination and how these observables are governed by spin-propagation, especially coherent spin propagation as well as collective spin-effects such as the spin-Dicke effect and resonant multi-photon magnetic dipole transitions. The project utilized pulsed electrically detected magnetic resonance (pEDMR) and pulsed optically detected magnetic resonance (pODMR) techniques over a wide frequency range. These techniques enabled the observation and quantification of various spin-spin coupling types, including spin-exchange, spin-dipolar, hyperfine, and spin-orbit interactions. The project will leverage low- to mid-frequency pEDMR/pODMR facilities and collaboration with the National High Magnetic Field Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Black-box optimization of a closed-circuit reverse osmosis system for desalination through extremum seeking control

We study the minimization of the cost function of a closed-circuit desalination reverse osmosis (CCRO) system, which is used for producing drinking water. The cost function is a trade-off between the specific energy consumption and the specific brine management cost. The extremum-seeking controller (ESC) manipulates the critical electric conductivity of the brine to minimize the cost function. Experiments were designed in which the composition of the feed salinity is increased to test the controller’s ability to converge to a new optimum. The ESC was able to shift the critical conductivity to a new optimum, which resulted in a 9% improvement in the cost function.

Chowdhury, Dhruba↗
DOE OSTI2022

Guiding Self-Assembly of Active Colloids by Temporal Modulation of Activity

Self-organization phenomena in ensembles of self-propelled particles open pathways to the synthesis of new dynamic states not accessible by traditional equilibrium processes. The challenge is to develop a set of principles that facilitate the control and manipulation of emergent active states. In this study, we report that dielectric rolling colloids energized by a pulsating electric field self-organize into alternating square lattices with a lattice constant controlled by the parameters of the field. We combine experiments and simulations to examine spatiotemporal properties of the emergent collective patterns and investigate the underlying dynamics of the self-organization.We reveal the resistance of the dynamic lattices to compression and expansion stresses leading to a hysteretic behavior of the lattice constant. The general mechanism of pattern synthesis and control in active ensembles via temporal modulation of activity can be applied to other active colloidal systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Probability Density Function Control of Frequency Fluctuations in Renewable-Rich Power Systems

The stochastic nature of renewable energy sources (RESs) necessitates treating power system frequency response as a random process with a nonstationary probability density function (PDF). Here, based upon the stochastic distribution control theory originated by the second author, this paper proposes a novel stochastic controller to improve the frequency PDF in power grids when integrating a large amount of RESs, thereby minimizing the effects of uncertainties and enhancing overall system stability. The key idea is to manipulate the controllable power generation resources so that the frequency PDF is make to follow a target PDF by using the stochastic distribution control theory originated by the second author. The proposed method can easily be plugged into existing automatic generation controls for multi-area transmission grids. The proposed method is validated via a modified Kundar's two area system and 240-bus Western Electricity Coordinating Council systems. The simulation results show that the proposed control shapes the frequency PDF narrower and sharper, leading to a notable improvement toward minimizing the effects of randomness and uncertainty during grid operation.

frequency↗
DOE OSTI2025

Using chiral-induced spin selectivity as a tool to improve materials and processes for energy science

Studies relating to electrical energy conversion, storage, and generation, date back to the 19th century, however only in recent years have scientists begun to investigate the impact of the electron spin on these processes. Control and manipulation of the electron spin, an intrinsically quantum property of matter, opens new approaches to addressing energy science challenges. Furthermore, the chiral-induced spin selectivity (CISS) effect is enabling for this effort, because of the control over the transport and generation of both pure spin currents and spin-polarized charge currents. In this review article, we begin with a brief introduction on design strategies for the implementation of CISS in materials and then describe recent studies that demonstrate how CISS can be used to improve electrocatalysis and spintronics. Lastly, we conclude with forward-looking thoughts on the next steps for leveraging CISS in energy science.

Batteries↗
DOE OSTI2025

Entanglement engineering of optomechanical systems by reinforcement learning

Entanglement is fundamental to quantum information science and technology, yet controlling and manipulating entanglement—so-called entanglement engineering—for arbitrary quantum systems remains a formidable challenge. There are two difficulties: the fragility of quantum entanglement and its experimental characterization. We develop a model-free deep reinforcement-learning (RL) approach to entanglement engineering, in which feedback control together with weak continuous measurement and partial state observation is exploited to generate and maintain desired entanglement. We employ quantum optomechanical systems with linear or nonlinear photon–phonon interactions to demonstrate the workings of our machine-learning-based entanglement engineering protocol. In particular, the RL agent sequentially interacts with one or multiple parallel quantum optomechanical environments, collects trajectories, and updates the policy to maximize the accumulated reward to create and stabilize quantum entanglement over an arbitrary amount of time. The machine-learning-based model-free control principle is applicable to the entanglement engineering of experimental quantum systems in general.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Understanding Biomass and Polymer Feedstock Variability Through Analytical Pyrolysis and Two Dimensional Gas Chromatography and Mass Spectrometry

Moving toward a circular carbon economy requires enabling reuse of carbon-based macromolecules like those in biomass and polymers. Meeting this goal requires increased upcycling of waste products into higher value products. For biomass waste such as corn stover, pine needles, or bark, one approach is using pyrolysis to convert these feedstocks into bio-oil that can be used for liquid fuel or transformed into other hydrocarbon based products, like bio-polymers. Waste plastics can be upcycled or recycled into new products, or alternatively converted into bio-oil by pyrolysis. Macromolecules from biomass and polymers are challenging to convert into liquid fuel or chemical feedstocks, due to large and sometimes heterogeneous networks of polymeric bonds. We work with the Idaho National Laboratory’s Biomass Feedstock National User Facility and Department of Energy’s Feedstock Conversion Interface Consortium to develop a molecular understanding of biomass variability that occurs naturally and as a result of storage or preprocessing techniques applied to feedstocks, to understand chemical reactions occurring during pyrolysis and other biomass or polymer conversion techniques. Using two dimensional gas chromatography mass spectrometry coupled to analytical pyrolysis provides insight into the molecular changes that occur during the pyrolysis event, and these insights can extend to bench or pilot scale pyrolysis conversions. Understanding pyrolysis of biomass and polymers at a molecular level contributes to development of new tools to predict and manipulate the optimum conditions and identify the best storage, preprocessing, and conversion techniques to maximize output of specific high-value chemical species in the conversion to fuels, or to characterize feedstocks for blending before pyrolysis. Identification and understanding of the molecular level changes resulting from novel preprocessing techniques that can be used to control and manipulate the chemical output of bench or pilot scale pyrolysis is another focus of investigation, including the use of gamma irradiation, acid, or enzyme pre-treatments. We also focus on the impacts of storage conditions and techniques, which can affect moisture levels, degradation, and impacts from naturally occurring microbes in the environment.

09 BIOMASS FUELS↗
DOE OSTI2021

Spatiotemporal control of liquid crystal structure and dynamics through activity patterning

Active materials are capable of converting free energy into mechanical work to produce autonomous motion, and exhibit striking collective dynamics that biology relies on for essential functions. Controlling those dynamics and transport in synthetic systems has been particularly challenging. Here, we introduce the concept of spatially structured activity as a means of controlling and manipulating transport in active nematic liquid crystals consisting of actin filaments and light-sensitive myosin motors. In this work, simulations and experiments are used to demonstrate that topological defects can be generated at will and then constrained to move along specified trajectories by inducing local stresses in an otherwise passive material. These results provide a foundation for the design of autonomous and reconfigurable microfluidic systems where transport is controlled by modulating activity with light.

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

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
DOE OSTI2024

Efficacy and Costs of Restoring Wetland Breeding Habitat for Imperiled Amphibians in the Southeastern U.S.

Herbaceous isolated wetlands in the North American Southeastern Coastal Plain are important breeding sites for many imperiled amphibians. However, most are degraded from alterations to historic fire disturbance and hydrologic regimes. Without fire, encroaching woody vegetation can transition wetlands to more terrestrial conditions and negatively impact amphibian breeding habitat, yet few studies have experimentally tested the efficacy, cost, or temporal requirement of current methods to restore herbaceous wetland vegetation. Here, we tested the interaction of manipulating wetland canopy and leaf litter/duff to promote herbaceous vegetation within one year (i.e., one breeding season) in degraded herbaceous wetlands in South Carolina. We assessed plant response via herbaceous cover, composition, and species similarity to the wetland seed bank and then related treatment performance to treatment cost. Removing trees combined with burning, disturbing, or removing duff significantly increased herbaceous cover and proportions of wetland plants and graminoids. Removing trees alone did not improve herbaceous cover compared to closed-canopy controls, and manipulating duff alone had limited positive effects on plant cover and composition. The most expensive yet effective treatment was Tree Removal-Duff Removal, while Tree Removal-Duff Disturbance was the most cost-effective. At a minimum, we recommend removing trees and burning to kickstart herbaceous recovery. Promisingly, comparisons of our data with previous seed bank studies from these same wetlands indicate there was limited seed bank attrition during 30 years of woody encroachment. Results from this study should aid practitioners in choosing wetland restoration techniques to better conserve at-risk species in the Southeastern Coastal Plain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Innovative mercury treatment technology options for the liquid waste system at the Savannah River Site: scoping studies

The Savannah River Site (SRS) Liquid Waste System (LWS) contains liquids, salts and sludges that are currently being processed into final wasteforms for disposition, specifically, waste glass for sludges, solids and liquids containing high levels of radioactivity, and saltstone grout for low activity decontaminated liquid solutions. The LWS also contains approximately 60,000 kg of mercury present in the following physical and chemical forms, specifically: a) ionic inorganic mercury, organomercury (e.g., methylmercury), and other minor components found in LWS fluids b) mercury solids such as oxides, hydroxides, amalgams sulfides and sorbed mercury, c) accumulations of dense liquid elemental mercury, and d) vapor phase elemental and organomercury mercury found in tank headspace gas and in evaporators. An effective and proactive management strategy of the mercury present in the LWS is needed to support processing of LWS wastes into glass and saltstone. Sustainable processing of the LAWS to completion requires mercury removal from the LWS at a rate of approximately 2,900 kg/yr. This removal can be accomplished through existing mercury treatment systems or newly implemented LWS “purge points”. The chemical speciation of mercury has emerged as the key factor that controls mercury behavior in the LWS. For example, past studies demonstrated that mercury speciation is adversely impacting the performance of existing removal systems so that significant levels of mercury are recycled from the Defense Waste Processing Facility (DWPF) back to the tank farm. Consequently, mercury concentrations have slowly increased in the LWS tank fluids over time. The presence of organo-mercury has also been identified as the cause of increased mercury leaching from saltstone. In response to these challenges, the Department of Energy (DOE) Office of Environmental Management (EM-TD) Technology Development Program has supported a series of scoping studies predicated on manipulating or controlling mercury speciation and mercury behaviors within the constraints of LWS waste chemistry and safety conditions. The intent of these studies was to rapidly triage potential technology options and develop a technically based go / no go recommendation for further work. This composite report presents the results of three scoping studies: 1) advanced photooxidation processes, 2) chemical reduction, and 3) mercury getters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Tuning austenite stability through prior microstructure control in a low-alloy Q&P steel

Quenching and partitioning (Q&P) processing is a widely accepted heat treatment methodology for creating high strength steels consisting of ferrite, martensite, and austenite, while maintaining relatively low manufacturing costs. Though the research on effects of prior microstructure is limited, an understanding of the heat treatment response of different starting microstructures is critical to processing and creating steels with complex microstructures that contain retained austenite and may afford opportunities to further optimize properties. This study investigates the influence of starting microstructure (ferrite/pearlite versus martensite) and prior levels of cold work (38 verses 58 %) on the microstructural development and mechanical properties of a 0.2 C-2.0 Mn-1.5 Si (wt.%) steel exposed to Q&P processing. Samples with a starting martensitic microstructure resulted in higher retained austenite fractions and a more homogeneous microstructure after Q&P processing compared to a starting microstructure of ferrite-pearlite. Starting martensitic microstructures also displayed higher work hardening rates and higher uniform elongations. Larger cold reductions saw accelerated dissolution kinetics and austenite formation during intercritical annealing, resulting in more similar final microstructures from the ferrite-pearlite and martensitic starting microstructures. Finally, the results presented here indicate that varying prior processing can be a route to manipulate and control austenite stability in a Q&P processed steel.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Metal–support interactions in metal oxide-supported atomic, cluster, and nanoparticle catalysis

Supported metal catalysts are essential to a plethora of processes in the chemical industry. The overall performance of these catalysts depends strongly on the interaction of adsorbates at the atomic level, which can be manipulated and controlled by the different constituents of the active material (i.e., support and active metal). The description of catalyst activity and the relationship between active constituent and the support, or metal–support interactions (MSI), in heterogeneous (thermo)catalysts is a complex phenomenon with multivariate (dependent and independent) contributions that are difficult to disentangle, both experimentally and theoretically. So-called “strong metal–support interactions” have been reported for several decades and summarized in excellent review articles. However, in recent years, there has been a proliferation of new findings related to atomically dispersed metal sites, metal oxide defects, and, for example, the generation and evolution of MSI under reaction conditions, which has led to the designation of (sub)classifications of MSI deserving to be critically and systematically evaluated. These include dynamic restructuring under alternating redox and reaction conditions, adsorbate-induced MSI, and evidence of strong interactions in oxide-supported metal oxide catalysts. Here, we review recent literature on MSI in oxide-supported metal particles to provide an up-to-date understanding of the underlying physicochemical principles that dominate the observed effects in supported metal atomic, cluster, and nanoparticle catalysts. Critical evaluation of different subclassifications of MSI is provided, along with discussions on the formation mechanisms, theoretical and characterization advances, and tuning strategies to manipulate catalytic reaction performance. We also provide a perspective on the future of the field, and we discuss the analysis of different MSI effects on catalysis quantitatively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effect of chemical disorder on the electronic stopping of solid solution alloys

The electronic stopping power of nickel-based equiatomic solid solutions alloys NiCr, NiFe and NiCo for protons and alpha projectiles is investigated in detail using real-time time-dependent density functional theory over a wide range of velocities. Recently developed numerical electronic structure methods are used to probe fundamental aspects of electron-ion coupling non-perturbatively and in a fully atomistic context, capturing the effect of the atomic scale disorder. The effects of particular electronic band structures and density of states reflect in the low velocity limit behavior. We compare our results for the alloys with those of a pure nickel target to understand how alloying affects the electronic stopping. We discover that NiCo and NiFe have similar stopping behavior as Ni while NiCr has an asymptotic stopping power that is more than a factor of two larger than its counterparts for velocities below 0.1 a.u.. Overall, we show that the low-velocity limit of electronic stopping power can be manipulated by controlling the broadening of the d-band through the chemical disorder. In this regime, the Bragg’s additive rule for the stopping of composite materials also fails for NiCr.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Exploring wave propagation in heterogeneous metastructures using the relaxed micromorphic model

Metamaterials are artificial structures that can manipulate and control sound waves in ways not possible with conventional materials. While much effort has been undertaken to widen the bandgaps produced by these materials through design of heterogeneities within unit cells, comparatively little work has considered the effect of engineering heterogeneities at the structural scale by combining different types of unit cells. In this paper, we use the relaxed micromorphic model to study wave propagation in heterogeneous metastructures composed of different unit cells. We first establish the efficacy of the relaxed micromorphic model for capturing the salient characteristics of dispersive wave propagation through comparisons with direct numerical simulations for two classes of metamaterial unit cells: namely phononic crystals and locally resonant metamaterials. We then use this model to demonstrate how spatially arranging multiple unit cells into metastructures can lead to tailored and unique properties such as spatially-dependent broadband wave attenuation, rainbow trapping, and pulse shaping. In the case of the broadband wave attenuation application, we show that by building layered metastructures from different metamaterial unit cells, we can slow down or stop wave packets in an enlarged frequency range, while letting other frequencies through. In the case of the rainbow-trapping application, we show that spatial arrangements of different unit cells can be designed to progressively slow down and eventually stop waves with different frequencies at different spatial locations. Finally, in the case of the pulse-shaping application, our results show that heterogeneous metastructures can be designed to tailor the spatial profile of a propagating wave packet. Collectively, these results show the versatility of the relaxed micromorphic model for effectively and accurately simulating wave propagation in heterogeneous metastructures, and how this model can be used to design heterogeneous metastructures with tailored wave propagation functionalities.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

New frontiers in atom probe tomography: a review of research enabled by cryo and/or vacuum transfer systems

There has been a recent surge in the use of cryo and/or vacuum specimen preparation and transfer systems that are broadening the scope of research enabled by the microscopy technique of atom probe tomography. This is driven by the fact that, like for many microscopes, the application of atom probe to air and temperature sensitive materials or wet biological specimens has previously been limited by through-air-transfer and through-vacuum-transfer at room temperature. Here we provide an overview of the critical areas of research that require these new transfer and analysis protocols, as well as a review of current advances in transfer devices, environmental cells and glove boxes for controlled sample manipulation. This includes the study of catalysis and corrosion, the application of atom probe to biological samples, the study of liquid-solid interfaces, natural ageing investigations and the analysis of hydrogen in metals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electronic Structure of Double-Layer Epitaxial Graphene on SiC(0001) Modified by Gd Intercalation

In this work, we systematically study the effects of Gd adsorption and intercalation on the electronic band structure of double-layer epitaxial graphene on Si-terminated SiC(0001) by first-principles calculations. We show that Gd adsorption and intercalation exhibit strong effects on the coupling between the graphene layers and between the buffer layer and substrate. Different adsorption/intercalation geometries can result in very different electron band structures. The number of Dirac cones and the positions of the Dirac cones relative to the Fermi level can be effectively manipulated through controlling the Gd adsorption/intercalation geometries. Our calculations provide useful insights to guide the experimental design of graphene-based materials with desirable functionalities for applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Magnetic Imaging of Domain Walls in the Antiferromagnetic Topological Insulator MnBi 2 Te 4

The control of domain walls or spin textures is crucial for spintronic applications of antiferromagnets. Despite many efforts, it has been challenging to directly visualize antiferromagnetic domains or domain walls with nanoscale resolution, especially in magnetic field. Here, we report magnetic imaging of domain walls in several uniaxial antiferromagnets, the topological insulator MnBi 2 Te 4 family, using cryogenic magnetic force microscopy (MFM). Our MFM results reveal higher magnetic susceptibility inside the domain walls than in domains. Domain walls in these antiferromagnets form randomly with strong thermal and magnetic field dependence. Here, the direct visualization of these domain walls and domain structures in the magnetic field will not only facilitate the exploration of intrinsic topological phenomena in antiferromagnetic topological insulators but will also open a new path toward control and manipulation of domain walls or spin textures in functional antiferromagnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗