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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Using Quantum Sensors to Probe the Quasiparticle Excess in Quantum Circuits due to Ionizing Radiation

This project quantified natural ionizing radiation as a source of excess quasiparticles in superconducting quantum circuits. Thermal Kinetic Inductance Detectors (TKIDs) were developed and deployed to measure event‑by‑event energy deposition in silicon substrates at millikelvin temperatures. Measurements and radiation transport simulations showed strong agreement across keV–MeV energies, providing validated background models and design guidance to mitigate radiation‑induced decoherence in superconducting qubits and detectors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Recycling of Printed Circuit Boards to Recover Critical Materials

The printed circuit board (PCB), a central component of most electronic devices, represents a significant fraction of the electronic product waste stream. The complex composition of PCBs, consisting of metals, polymers, and fiberglass, requires specialized recovery steps to reclaim valuable and critical materials and the safe disposal of brominated compounds. In this review paper, we describe the current state of critical material recovery and traditional recycling technologies and identify key obstacles to large-scale implementation. Metals present at high concentrations, such as copper, lead, and iron, are conventionally recovered from PCBs using hydrometallurgical, pyrometallurgical, or electrometallurgical processes. Hydrometallurgical methods achieve high selectivity through chemical leaching but pose significant challenges for effluent and reagent recovery. Pyrometallurgical methods facilitate rapid metal separation through smelting but require substantial energy and may release harmful gases. Electrometallurgical techniques produce high-purity metals but are constrained by pretreatment requirements and the consumption of energy. The non-metallic fraction of PCB waste is recycled using thermochemical conversion, microwave-aided heating, and direct recycling of epoxy–fiberglass composites, enabling material or energy recovery. The recovered polymer from direct recycling may have reduced mechanical strength and poor compatibility with new polymer matrices, and the resulting products from the thermal conversion suffer from incomplete conversion, degradation of quality, and residual contamination, as compared to synthetic polymers. Recent process developments have focused on extracting rare earth and supply-critical materials present at lower concentrations in the waste stream. The literature on existing and emerging approaches for recycling PCB wastes is reviewed to identify sustainable, economically viable, and environmentally responsible strategies for the recovery and reuse of critical materials from waste streams.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanoscale Three-Dimensional Imaging of Integrated Circuits Using a Scanning Electron Microscope and Transition-Edge Sensor Spectrometer

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but it is difficult to implement due to the competing requirements of X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while addressing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot on a metal target held micrometers away from the sample of interest, while the TES spectrometer isolates target photons with a high signal-to-noise ratio. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enables nanoscale, element-specific X-ray imaging in a compact footprint. The proof of concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in six layers of a Cu-SiO 2 integrated circuit, and a path toward finer resolution and enhanced imaging capabilities is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Investigation of a Multi-Rotor Triboelectric Nanogenerator Using a Modular Flexible Circuit Board Stack

Triboelectric nanogenerators (TENGs) are a nascent class of energy harvester that are being explored for scavenging energy from small ocean waves. To date, they have been integrated in wave energy converters (WECs) designed to capture random motion caused by the perturbations of the ocean surface. Blue economy applications such as ocean observation can benefit greatly from more substantial wave-derived power, as such, the power output of existing TENG WECs must be increased several-fold to become viable. This study describes the conceptualization of a rotary TENG, and the subsequent efforts to increase its power output by stacking multiple stator and rotor pairs. In the latter part of this study, we introduce a novel means of incorporating a friction element into the design of the TENG by employing flexible printed circuit board (PCB) rotors. At rest, these flexible rotors will contact the stator, building static charges due to friction, at speed, these flexible rotors will be decoupled from the stator, reducing friction and allowing faster rotation. Initial results indicate that the power output of the flexible PCB rotor does not produce more power than a rigid, acrylic disk rotor, however the current output of the prototype is boosted, and the prototype is far more compact, allowing for a higher energy density than the rigid rotor prototype.

bench testing↗
DOE OSTI2026

Electrochemical Modeling of PID Leakage Current of PV Modules: Steady-State Current, Transient Current, and RC-Equivalent Circuit

Potential-induced degradation (PID) remains a significant reliability concern for photovoltaic (PV) modules, arising when a voltage difference between the module frame and the solar cells drives unintended leakage current through the glass-encapsulant stack. Although PID ultimately manifests as PID-s, PID-p, or PID-c, the underlying behavior of the leakage current-its magnitude and time dependence-requires clearer electrochemical interpretation. Traditional explanations attribute the initial transient current to bulk capacitive elements of the glass, encapsulant, and antireflection coatings, and the steady-state current according to their effective ohmic resistance. More recent studies, however, indicate that electrochemical charge-transfer processes at the encapsulant-metallization interface can play a dominant role in defining the leakage-current path. This paper develops a unified electrochemical framework for modeling PID leakage current. First, an RC-equivalent circuit is formulated by combining conventional RC elements with a Randles-type interface to capture transient leakage current through double-layer capacitance and faradaic processes at ionic-electronic boundaries. Second, the steady-state current-voltage behavior is explained using a linearized Butler-Volmer relationship, showing that the measured ohmic response corresponds to the low-overpotential limit of charge-transfer kinetics. Analytical results demonstrate that, for typical module materials-3.2-mm soda-lime glass and 0.45-mm encapsulant-the dominant modulators to PID leakage current are the glass surface resistance (under dry-surface conditions), the glass bulk capacitance, and the encapsulant resistance (under wet-surface conditions), with soda lime glass surface and EVA/POE encapsulant resistances primarily governing steady-state current. The proposed electrochemical model is validated against measured leakage-current data, showing good agreement in both the magnitude and the time-dependent evolution of PID leakage current.

14 SOLAR ENERGY↗
DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗
DOE OSTI2024

Autonomous online optimization of a closed-circuit reverse osmosis system

As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Engineering quorum-sensing circuits in Synechococcus elongatus PCC 7942 towards self-inducible systems

Despite significant potential for cyanobacteria as sustainable bioproduction chases, there are limited examples of scaled cyanobacterial bioproduction. In part, this is because most cyanobacterial species are poorly adapted to bioreactor cultivation conditions and lack features that facilitate biomass growth and harvesting at scale. We explored quorum sensing (QS) pathways derived from heterotrophic microbes as a method for autoinduction of gene expression circuits coordinated to population density in cyanobacteria. Here, we integrated genetic modules designed to produce and detect the diffusible QS signal, acyl-homoserine lactones (AHLs), in the cyanobacterial model, Synechococcus elongatus PCC 7942 (S. elongatus). We demonstrate that S. elongatus heterologously produces sufficient AHL signals to activate gene expression in a dose-dependent and population density-responsive manner. A hybrid combination of AHL synthesis enzyme from Vibrio fischeri (Lux system) with the transcription factor receiver from Pseudomonas aeruginosa (Las system) provides an ideal activation ratio and mitigates toxicity observed with some AHL systems. As a proof of concept, we coupled the QS pathway to the expression of a cell division inhibitory gene, cdv3, facilitating late-phase cell elongation, cell sedimentation, and improved biomass recovery. Our findings provide a foundation for the development of auto-induction systems leverageable to improve cyanobacterial biotechnology applications.

Acyl homoserine lactones (AHL)↗
DOE OSTI2025

Clifford Circuit-Based Heuristic Optimization of Fermion-To-Qubit Mappings

Simulation of interacting Fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analyzing Fermionic systems with a quantum computer hinges on the efficiency of Fermion-to-qubit mappings that encode nonlocal Fermionic degrees of freedom in local qubit degrees of freedom. While recent studies have highlighted the importance of designing Fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far either are restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, in this work, we address this challenge by designing a heuristic numerical optimization framework for Fermion-to-qubit mappings. To this end, we first translate the Fermion-to-qubit mapping problem to a Clifford circuit optimization problem and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all Fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% and 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6 × 6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperforms any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific Fermionic Hamiltonian.

Hamiltonians↗
DOE OSTI2025

Adhesively Bonded Copper and Polyimide for Flexible Printed Circuit Boards: A Data-Driven Degradation Study Under Accelerated Aging

The long-term durability of polyimide laminated adhesive based flexible printed circuit boards (PCBs) is critical to the microelectronics industry. The interface of the adhesive layer binding the polyimide and copper layers is particularly vulnerable since decreased bonding strength can lead to deadhesion, performance loss, and premature device failure. Here, in this study, adhesive-bonded polyimide and copper samples are subjected to 1000 h of damp heat exposure (85 °C/85%RH) to evaluate the impact of moisture and copper inclusion on the adhesive bonding performance. Significant copper diffusion through the adhesive layer is observed, which, combined with moisture uptake, is found to substantially weaken interfacial adhesion in copper-containing samples, thereby reducing device lifetime. Observed surface and bulk material changes are correlated to adhesion strength using the network structural equation modeling (netSEM) approach, resulting in a robust predictive model of performance degradation based on measurable materials properties.

Chemistry↗
DOE OSTI2025

Pressure-Tolerant 3D Anodes Enable Short-Circuit Prevention and Low Heat Generation in Argyrodite Solid-State Batteries

Solid-state batteries (SSBs) offer a safer, higher-energy-density alternative to lithium-ion batteries, yet commercialization is hindered by incompatibility with lithium metal. Here, to overcome these challenges, we developed a cost-effective, commercially available prelithiated micro carbon fiber framework (Li-Cf) anode featuring a high-pressure-tolerance, for use with argyrodite solid-state electrolytes (SSEs). This 3D structure accommodates uniform lithium deposition, simplifies cell assembly under elevated pressure, inhibits dendrite growth toward SSEs, reduces heat generation, and enhances overall compatibility. Notably, our architecture enables the cell to tolerate pressures up to 400 MPa without short-circuiting during assembly. Meanwhile, the 3D framework serves as a preferential pathway for lithium deposition, thereby reducing lithium growth toward the SSEs and mitigating the risk of dendrite formation in SSEs. Operando calorimetry and distribution of relaxation times analysis reveal that lithium morphology degradation at the interface with the SSEs is a key failure mechanism in lithium metal argyrodite SSBs, leading to increased diffusion resistance and heat generation. In contrast, the Li-Cf anode mitigates these issues by reducing both heat flux and charge transfer resistance. Full cells with LiNi 0.8 Co 0.1 Mn 0.1 O 2 /Li 6 PS 5 Cl/Li-Cf retain ~79% capacity after 600 cycles, demonstrating significantly improved cycling stability and strong potential for practical energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Single-shot magnon interference in a magnon-superconducting-resonator hybrid circuit

Magnon interference is a hallmark of coherent magnon interactions. In this work, we demonstrate single-shot magnon interference using up to four magnon pulses in two remotely coupled yttrium iron garnet spheres mediated by a coplanar superconducting resonator. By exciting one YIG sphere with injected microwave pulses, we achieve coherent energy exchange between the two spheres, facilitating their interference processes, including Rabi-like oscillation with a single pulse, constructive and destructive interference with two pulses, and interference peak sharpening with up to four pulses—analogous to diffraction grating in optical interference. The resulting interference patterns can be precisely controlled by changing the frequency detuning and time delay of the magnon pulses. The demonstration of time-domain coherent control of remote magnon interference opens new pathways for advancing coherent information processing through multi-operation, circuit-integrated hybrid magnonic networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

A 1-km photonic link connecting superconducting circuits in two dilution refrigerators

Superconducting quantum processors are a leading platform for implementing practical quantum computation algorithms. Although superconducting quantum processors with hundreds of qubits have been demonstrated, their further scale-up is constrained by the physical size and cooling power of dilution refrigerators. This constraint can be overcome by constructing a quantum network to interconnect qubits hosted in different refrigerators, which requires microwave-to-optical transducers to enable low-loss signal transmission over long distances. Although various designs and demonstrations have achieved high-efficiency and low-added-noise transducers, a coherent photonic link between separate refrigerators has not yet been realized. Here, in this work, we experimentally demonstrate coherent signal transfer between two superconducting circuits housed in separate dilution refrigerators, enabled by a pair of frequency-matched aluminium nitride electro-optic transducers connected via a 1-km telecom optical fibre. The optical frequency matching between two transducers is realized by an asymmetric photonic molecule design, and an overall 80 dB improvement in transduction efficiency over commercial electro-optic modulators is achieved, paving the way towards a fully quantum-enabled link. This work provides critical design guidelines for scalable superconducting quantum networks interconnected by photonic links.

nonlinear optics↗
DOE OSTI2024

Circuit quantum electrodynamics detection of induced two-fold anisotropic pairing in a hybrid superconductor–ferromagnet bilayer

Abstract Hybrid systems represent one of the frontiers in the study of unconventional superconductivity and are a promising platform to realize topological superconducting states. These materials are challenging to probe using many conventional measurement techniques because of their mesoscopic dimensions, and therefore require new experimental probes so that they can be successfully characterized. Here, we demonstrate a probe that enables us to measure the superfluid density of micrometre-size superconductors using microwave techniques drawn from circuit quantum electrodynamics. We apply this technique to a superconductor–ferromagnet bilayer and find that the proximity-induced superfluid density is two-fold anisotropic within the plane of the sample. It also exhibits power-law temperature scaling that is indicative of a nodal superconducting state. These experimental results are consistent with the theoretically predicted signatures of induced triplet pairing with a nodal p -wave order parameter. Moreover, we observe modifications to the microwave response at frequencies near the ferromagnetic resonance, suggesting a coupling between the spin dynamics and induced superconducting order in the ferromagnetic layer. Our experimental technique can be employed more widely, for example to study fragile unconventional superconductivity in low-dimensional materials such as van der Waals heterostructures.

Bøttcher, C. G. L. (ORCID:0000000194898461)↗
DOE OSTI2025

Efficient online quantum circuit learning with no upfront training

Optimization is a promising candidate for studying the utility of variational quantum algorithms (VQAs). However, evaluating cost functions using quantum hardware introduces runtime overheads that limit exploration. Surrogate-based methods can reduce calls to a quantum computer, yet existing approaches require hyperparameter pre-training and have been tested only on small problems. Here, we show that surrogate-based methods can enable successful optimization at scale, without pre-training, by using radial basis function interpolation (RBF) to construct an adaptive, hyperparameter-free surrogate. Using the surrogate as an acquisition function drives hardware queries to the vicinity of the true optima. For 16-qubit random 3-regular Max-Cut instances with the Quantum Approximate Optimization Algorithm (QAOA), our method outperforms state-of-the-art approaches, without considering their upfront training costs. Furthermore, we successfully optimize QAOA circuits for 127-qubit random Ising models on an IBM processor using 10 4 −10 5 measurements. Strong empirical performance demonstrates the promise of automated surrogate-based learning for large-scale VQA applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗
DOE OSTI2025

Cyberattack Detection and Mitigation on Central Volt‐VAr Using Circuit Law and Machine Learning

ABSTRACT In a distribution grid, voltage is maintained within a nominal range through a Volt‐VAr function that controls capacitor banks, reactive power of distributed energy resources (DER), and on‐load tap changers (OLTC). Availability of communications helps with the implementation of central Volt‐VAr control; however, it also opens the system to cyberattacks, causing voltage disturbances. Previous work has shown the adverse impacts of false data injection (FDI) on the central Volt‐VAr control; however, very few works have studied methods to detect and mitigate FDI on Volt‐VAr control. This paper addresses gaps in the detection and mitigation of FDI on the measurement packets of a central Volt‐VAr control. This work uses a two‐stage algorithm for cyberattack detection since the accuracy of a single‐stage machine learning (ML)–based detection method decreases while dealing with unseen data. The first stage is based on the verification of measurements against circuit laws, and the second stage utilizes a tree search algorithm and an ML method to detect the falsified data. This paper compares long short‐term memory (LSTM) and bidirectional LSTM (BiLSTM) as the employed ML algorithms. Finally, the mitigation algorithm replaces the falsified data with the estimated output of the ML algorithm. The effectiveness of the proposed method is tested for several cases using the IEEE 13‐bus test system in PSCAD software.

Beikbabaei, Milad [Bradley Department of Electrica↗