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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Biosensor and optogenetics for systems biology of yeast branched-chain alcohol production and tolerance

In this project we combined synthetic biology, systems biology, protein engineering and metabolic engineering to study, control, and improve the production of branched chain alcohols (BCAs), a class of advanced biofuels preferred by the DOE, in the yeast Saccharomyces cerevisiae. This involved the development and application of optogenetic systems as a new modality of dynamic control of native and engineered metabolic pathways, using light as inducible or repressible agent. The optogenetic systems include gene circuits for light control of gene expression, as well as light-assembled synthetic organelles and photo-switchable protein binders to control metabolic and protein function with light at the protein level. In addition, we developed the first genetically encoded biosensor for BCA production in yeast, which we used to design high throughput assays to identify highly productive strains, pathways, and enzymes. We also showed that this biosensor can be functionally co-expressed with optogenetic circuits in the same strain, raising the possibility of establishing, for the first time, computer-interfaced closed-loop controls of engineered metabolic pathways. The yeast gene deletion library was also utilized to conduct the first systems-level study on BCA toxicity in yeast, which uncovered key fundamental principles of yeast sensitivity and tolerance to these alcohols, allowing us to design highly tolerant strains with increased BCA production. This project, thus comprises the development of several new technologies, which we integrated to make new discoveries on the dynamics of BCA production and their mechanisms of cellular toxicity and tolerance, as well as to establish new paradigms to engineer and control metabolic pathways and microbial fermentations with light, for the production of BCAs and other products of interest to the DOE.

2-metyl-1-butanol↗
DOE OSTI2022

Dynamic, hollow nanotubular networks with superadjustable pH-responsive and temperature resistant rheological characteristics

Recently, the interest in stimuli-responsive and adaptable materials has continuously grown in various fields and applications. For such responsive systems, different triggers, including pH, light, pressure, temperature, and electric field, have been utilized to control dynamics and assembly. Among these, pH is one of the most convenient, energy-efficient, and economic modalities. Besides, plenty of traditional materials have poor thermal and salt stability, limiting their applications. Herein, we report a new design of a pH-responsive viscoelastic supramolecular complex (VSC) based on commplexation of a new long-chain amino-amide and maleic acid. In this study, the system demonstrated a sol–gel-sol transition from pH 2 to 10, with the largest static viscosity occurring at pH 6 (~1000 Pa·s) and the smallest viscosity at pH 4 (~3.3 Pa·s), indicating ~ 300-fold control over the viscosity. For a given concentration, the static viscosity of VSC was about 15 times larger than that of CTAB/NaSal, a well-established dynamic viscoelastic system, and no pH-responsiveness was observed for the traditional system. In addition, the VSC demonstrated a superior temperature tolerance and lower temperature dependence. The potential of these intriguing dynamics viscoelastic systems was evaluated for hydraulic fracturing and enhanced oil recovery applications. Proppant settling velocity of DMAA/MA was 500 ~ 1000 times lower than that of CTAB/NaSal and common traditional polymers. Likewise, the oil recovery percentage could be significantly improved with the utilization of DMAA/MA compared to the CTAB/NaSal (86 % vs 52 %). Aside from applications in hydraulic fracturing and enhanced oil recovery, we anticipate that the intriguing rheological properties of this viscoelastic system can be beneficial for other chemical engineering applications including personal care products, cosmetics, lubricants, and biomedical gels.

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

Effect of Nanoconfinement on Polymer Chain Dynamics

Here, we report on a study of the effects of nanoconfinement on polymer chain dynamics within the framework developed by Muthukumar [Muthukumar, M. (1991). Journal of Non-Crystalline Solids, 131, 654-666.], who suggests that there is an entropically controlled dynamical regime between the Rouse and the reptation regimes that affects the power law dependence on molecular weight of the transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

On-Chip Cavity Electroacoustics Using Lithium Niobate Phononic Crystal Resonators

Mechanical systems are pivotal in quantum technologies because of their long coherent time and versatile coupling to qubit systems. So far, the coherent and dynamic control of gigahertz-frequency mechanical modes mostly relies on optomechanical coupling and piezoelectric coupling to superconducting qubits. Here, we demonstrate on-chip cavity electroacoustic dynamics using our microwave-frequency electrically modulated phononic crystal resonators on lithium niobate. Leveraging the high dispersion of phononic crystal, our acoustic modes space unevenly in the frequency spectrum, emulating atomic energy levels. Atomiclike transitions between different acoustic modes are selectively achieved by applying electrical fields to modulate acoustic modes via the nonlinear piezoelectricity of lithium niobate. Among two modes, we demonstrate Autler-Townes splitting, ac Stark shift, and Rabi oscillation with a maximum cooperativity of 4.18. Extending to three modes, we achieve nonreciprocal frequency conversions with an isolation up to 20 dB. Nonreciprocity can be tuned by the time delay between the two modulating pulses. Finally, our cavity electroacoustic platform could find broad applications in sensing, microwave signal processing, acoustic computing, and quantum acoustics.

Rabi model↗
DOE OSTI2022

Electrical Switching of Nematic Plasmonic Nanocolloids for Infrared Solar Gain Control

Controlling solar gain is essential to reduce the energy consumption by residential and commercial buildings, which are responsible for ≈40% of all energy generated globally. However, the dynamic control of solar gain in the near-infrared that corresponds to ≈50% of the overall Sun's energy at the Earth's surface, separately from the visible spectral range has been a challenge, albeit commercial coatings provide passive control while retaining highly visible transmission. To address this problem, in this paper switchable silver colloids (SSCs) are demonstrated, colloidal analogs of the common silver coatings used for solar gain control. When dispersed in a nematic liquid crystal, orientations of such plasmonic silver nanoplates are controlled by ≈1 V low-voltage electric fields, allowing for sub-second switching of the near-infrared-based solar gain. Installed and retrofit products made from thin films of such nanoplate dispersions confined between glass and plastic substrates, respectively, exhibit electrically controlled infrared-based solar gain while retaining high visible-range transparency, low haze, and high color rendering index. Furthermore, this study's findings reveal a great potential of soft-matter systems in addressing energy-related problems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Non-volatile electric control of magnetic and topological properties of MnBi 2 Te 4 thin films

In this letter, we propose a mechanism to control the magnetic properties of topological quantum material (TQM) by using magnetoelectric coupling: this mechanism uses a heterostructure of TQM with two-dimensional (2D) ferroelectric material, which can dynamically control the magnetic order by changing the polarization of the ferroelectric material and induce possible topological phase transitions. This concept is demonstrated using the example of the bilayer MnBi 2 Te 4 on ferroelectric In 2 Se 3 or In 2 Te 3 , where the polarization direction of the 2D ferroelectrics determines the interfacial band alignment and consequently the direction of the charge transfer. This charge transfer, in turn, enhances the stability of the ferromagnetic state of MnBi 2 Te 4 and leads to a possible topological phase transition between the quantum anomalous Hall (QAH) effect and the zero plateau QAH. Our work provides a route to dynamically alter the magnetic ordering of TQMs and could lead to the discovery of new multifunctional topological heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Flexible Transformers

Advanced grid solutions are comprised of advanced transmission technologies and grid enhancing technologies. In this webinar, experts will provide participants with insights into eight advanced grid solutions. The advanced transmission technologies that will be discussed include point-to-point high voltage direct current and advanced conductoring and the grid enhancing technologies that experts will explore include topology optimization, advanced power flow control, dynamic line rating, energy storage, virtual power plants, and advanced flexible transformers

flexible power transformer, power flow controller,↗
DOE OSTI2024

Towards predictive control of reversible nanoparticle assembly with solid-binding proteins

Although a broad range of ligand-functionalized nanoparticles and physico-chemical triggers have been exploited to create stimuli-responsive colloidal systems, little attention has been paid to the reversible assembly of unmodified nanoparticles with non-covalently bound proteins. Previously, we reported that a derivative of green fluorescent protein engineered with oppositely located silica-binding peptides mediates the repeated assembly and disassembly of 10-nm silica nanoparticles when pH is toggled between 7.5 and 8.5. We captured the subtle interplay between interparticle electrostatic repulsion and their protein-mediated short-range attraction with a multiscale model energetically benchmarked to collective system behavior captured by scattering experiments. Here, in this work, we show that both solution conditions (pH and ionic strength) and protein engineering (sequence and position of engineered silica-binding peptides) provide pathways for reversible control over growth and fragmentation, leading to clusters ranging in size from 25 nm protein-coated particles to micrometer-size aggregate. We further find that the higher electrolyte environment associated with successive cycles of base addition eventually eliminates reversibility. Our model accurately predicts these multiple length scales phenomena. The underpinning concepts provide design principles for the dynamic control of other protein- and particle-based nanocomposites.

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

Optimizing Sub-Sampled STEM Imaging for Beam Sensitive Materials and Dynamic Processes

The goal of this research is to quantify how sub-sampling and inpainting (broadly classified as methods in Artificial Intelligence) can be used to obtain the highest resolution images under any experimental conditions, and to use this to reproducibly control dynamic in-situ processes in gases and liquids on the nanoscale. As atomic diffusion under non-extreme conditions is typically in the sub-ms time domain, the ability to use this sub-sampling approach to reduce the effect of the electron beam and to speed-up the imaging process represents the optimum combination of spatial and temporal resolution achievable in a conventional microscope. This LDRD funding demonstrated the feasibility of imaging dynamics in complex energy systems using this methodology by establishing the optimum experimental sampling conditions (optimizing the number of pixels, speed, contrast and resolution) for each experiment. For in-situ liquid cell experiments this analysis shows that simply by distributing the same dose and dose rate maximally in space and time, the kinetics for radiolysis products can be modified significantly. The final stage of this work, i.e. the experimental demonstration of its use for nucleation and growth, was severely curtailed by issues with COVID19. However, all the experiments are designed and currently underway, with the goal to complete the final demonstration and publication as soon as safety concerns for laboratory access are met.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Background cancellation for frequency-selective quantum sensing

A key challenge in quantum sensing is the detection of weak time dependent signals, particularly those that arise as specific frequency perturbations over a background field. Conventional methods usually demand complex dynamical control of the quantum sensor and heavy classical post-processing. We propose a quantum sensor that leverages time independent interactions and entanglement to function as a passive, tunable, thresholded frequency filter. By encoding the frequency selectivity and thresholding behavior directly into the dynamics, the sensor is responsive only to a target frequency of choice whose amplitude is above a threshold. This approach circumvents the need for complex control schemes and reduces the post-processing overhead.

Puig, Ricard [Los Alamos; Ecole Polytechnique, Lau↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Nanostructuring and Underscreening of Bisalt Electrolytes with Dual-Anion Effects: Insights from Small-Angle Scattering Prepeak Analysis

Using small-angle neutron scattering, we studied the nanostructure of a prototypical D(H)-bonded network electrolyte, alkaline sodium aluminate bisalt, at concentrations up to solute volume fraction of ~0.5. Analysis of the structure factor prepeak at 0.1 < Q < 1.0 Å-1 showed that its evolution is associated with nanoscopic species distribution in water-anion network., with differences in characteristic distance d between OD- and Al(OD)4- anions related to their distinct sizes and interactions. When the solute volume fraction approached 0.5, a common/maximum value of ~4.5 Å was found for the correlation length ? that characterizes the electrostatic force in concentrated electrolyte solution before precipitation occurred. This implies that the solutions’ morphology and behavior at high concentrations may be governed by geometric factors, rather than the chemistry of the specific anion. Furthermore, the scaling of ? with concentration yielded an exponent of 1.25(1), suggesting that ? is limited to a few Å. By combining the current observations of structural heterogeneity at the nanoscale, with dynamic heterogeneity at the microscopic scale from our previous quasi-elastic neutron scattering study, we have established a structural origin of local “caging” and restricted structural relaxation processes. These local solvent-solute interactions not only control dynamics heterogeneity in concentrated electrolytes but also are responsible for crystallization processes in industrial setting, such as aluminum production and radioactive waste treatment.

Wang, Hsiu-Wen↗
DOE OSTI2022

Broadband‐Tunable Third‐Harmonic Generation Using Phase‐Change Chalcogenides

Despite remarkable progress in passive nonlinear nanophotonics, dynamically controlled ultracompact nonlinear optical sources with high efficiency remain elusive. Nonvolatility, large refractive index contrast between amorphous and crystalline phases, low thermal threshold for crystallization, and particularly high‐third‐order nonlinear optical susceptibility of phase‐change alloy Ge 2 Sb 2 Te 5 (GST) make it a promising candidate for active subwavelength metaphotonic structures for realization of third‐harmonic generation (THG) devices. Herein, a GST‐based asymmetric Fabry–Perot cavity is numerically designed and experimentally demonstrated to show a dynamically reconfigurable structure with a large shift of the THG resonant band. In addition, continuous resonant spectral shifting bridged by a precisely controlled semicrystalline phase of GST is realized. Tunable THG with the fundamental wavelength ranging from 1150 to 1400 nm is presented, which corresponds to a broadband THG source in the violet‐blue visible wavelength range. Herein, the potential of GST subwavelength structures as a reliable platform for realization of the broadband‐tunable frequency‐conversion sources for applications such as THG microscopy and optical communication is indicated.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Controlling single rare earth ion emission in an electro-optical nanocavity

Abstract Rare earth emitters enable critical quantum resources including spin qubits, single photon sources, and quantum memories. Yet, probing of single ions remains challenging due to low emission rate of their intra-4 f optical transitions. One feasible approach is through Purcell-enhanced emission in optical cavities. The ability to modulate cavity-ion coupling in real-time will further elevate the capacity of such systems. Here, we demonstrate direct control of single ion emission by embedding erbium dopants in an electro-optically active photonic crystal cavity patterned from thin-film lithium niobate. Purcell factor over 170 enables single ion detection, which is verified by second-order autocorrelation measurement. Dynamic control of emission rate is realized by leveraging electro-optic tuning of resonance frequency. Using this feature, storage, and retrieval of single ion excitation is further demonstrated, without perturbing the emission characteristics. These results promise new opportunities for controllable single-photon sources and efficient spin-photon interfaces.

42 ENGINEERING↗
DOE OSTI2026

Covalent Adaptable Networks: Reprocessable Cross-Linked Polymers

Thermoset polymers have desirable properties, such as excellent thermal and mechanical stability, but their covalent cross-links typically prevent repair or recycling. By enabling and controlling dynamic exchange reactions within polymer networks, their covalent bonds rearrange and allow the polymer to be reshaped. These viscoelastic polymer networks, now known as covalent adaptable networks (CANs), are an important frontier for improving plastic circularity, as well as for designing valuable stimuli-responsive materials. This Review describes the history of CANs, dating back to the early days of polymer science, and the evolution of their classification and nomenclature. A comprehensive survey of dynamic reactions and linkage chemistries is provided, as well as methods to characterize and reprocess CANs. Beyond straightforward reprocessing, many advanced applications of CANs and their composites are now emerging. Lastly, we provide perspective on how the development of new chemistries, strategies to control stimuli-responsive bond exchange and mechanical properties, and a deep understanding of exchange reactions will advance this field toward scalable, sustainable, and high-value materials.

Sun, Molly [Northwestern University, Evanston, IL ↗
DOE OSTI2023

Coordinated Wind Power Plant and Battery Control for Active Power Services

This article considers joint active power control of wind turbines and battery storage to follow a plant-level power reference signal. The joint control dynamically curtails the energy from a subset of the wind turbines and stores or withdraws energy from the battery to meet the power reference setpoint while accounting for wind plant aerodynamic interactions, such as wake losses. As a use case, we study the performance of the controller in maintaining a constant power output over hourly periods. A wind plant operating in this way would rely much less on other grid resources to meet its contractual agreements, thereby improving grid reliability, especially in grids with high penetration of wind and solar generation. We compare the operation of the wind plant under joint active power control to standard power-maximizing control with battery support. We present an analysis of the performance of the control system architecture. To study the impact of the battery size on performance, we simulate a 50-MW wind plant supported by batteries ranging from 8 to 64?MWh. We then evaluate the over and undergeneration penalties incurred by the plant during the simulation period.

17 WIND ENERGY↗
DOE OSTI2022

Machine Learning with Gradient-Based Optimization of Nuclear Waste Vitrification with Uncertainties and Constraints

Gekko is an optimization suite in Python that solves optimization problems involving mixed-integer, nonlinear, and differential equations. The purpose of this study is to integrate common Machine Learning (ML) algorithms such as Gaussian Process Regression (GPR), support vector regression (SVR), and artificial neural network (ANN) models into Gekko to solve data based optimization problems. Uncertainty quantification (UQ) is used alongside ML for better decision making. These methods include ensemble methods, model-specific methods, conformal predictions, and the delta method. An optimization problem involving nuclear waste vitrification is presented to demonstrate the benefit of ML in this field. ML models are compared against the current partial quadratic mixture (PQM) model in an optimization problem in Gekko. GPR with conformal uncertainty was chosen as the best substitute model as it had a lower mean squared error of 0.0025 compared to 0.018 and more confidently predicted a higher waste loading of 37.5 wt% compared to 34 wt%. The example problem shows that these tools can be used in similar industry settings where easier use and better performance is needed over classical approaches. Future works with these tools include expanding them with other regression models and UQ methods, and exploration into other optimization problems or dynamic control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗