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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 19 records

A prototype cooling blanket for mitigating occupant overheating risk in a hot indoor environment: Modeling and assessments

Conventional ways of cooling a room or an entire house for occupant thermal comfort during summer consume a significant amount of energy and are vulnerable to overheating risk during power outages that lead to loss of cooling system operations. This study investigates a low-power cooling blanket, as a Personal Cooling System (PCS), that covers the upper human body for direct cooling during a five-day heat wave in a single-family house. A modeling framework is developed for evaluating the thermal and energy performance of the cooling blanket, which builds upon the co-simulation of three models: a house energy model, a personal thermal comfort model, and a cooling blanket model. Simulation results show that under the power outage scenario, the cooling blanket can greatly reduce the occupant heat stress with a reduction of daily hours of exceedance (discomfort hours defined as TSV>2) by up to 17.2 h (a 95.3 % improvement from the baseline power outage without the blanket). The cooling blanket, equipped with an innovative electrocaloric heat pump (COP as high as 10.1) consumes 6.31 W and can be operated by a portable battery for several days. The cooling blanket consumes only 0.28 % of the electricity of a central air-conditioning system running to provide cooling for the whole house during the five-day heatwave period. The findings justify further research of electrocaloric wearable PCS as low-power effective cooling to ensure thermal survivability of occupants during extreme indoor environments.

Electrocaloric heat pump↗

ObstacleSense: Low-Power Neuromorphic Vision for Corridor Obstacle Awareness in Low-Level ADAS

The automotive industry’s pursuit of Level 5 autonomy is constrained by substantial perception-compute power requirements, often reaching 1, 000 + watts in full autonomy stacks. Reducing this energy burden requires rethinking perception not only at the high-end autonomy level, but also at the foundational Advanced Driver Assistance Systems (ADAS) level where low-power, safety-critical sensing can have broad impact. Neuromorphic vision provides a promising starting point: HD Dynamic Vision Sensors (DVS) can operate below 100 mW at the sensor level by reporting only asynchronous brightness changes. However, low-power sensing alone is insufficient if downstream perception reintroduces dense, energy-intensive computation. In particular, many event-driven object-detection pipelines still rely on CNN backbones, while purely spiking alternatives often trade away accuracy or ignore deployment constraints. We introduce ObstacleSense, a highly compact, CNN-free hybrid ANN–SNN framework for Level 0–1 forward-corridor obstacle awareness. Instead of performing full-scene object detection with a convolutional feature backbone, ObstacleSense targets the safety-critical question of whether the ego corridor is occupied and how far the nearest obstacle is. The architecture combines polarity-conditioned event encoding, lightweight temporal spiking dynamics, axial spatial mixing, and coarse-to-fine range estimation within a regular fixed-grid compute pattern. This design avoids the dense CNN backbone commonly used in event-based detection while maintaining a small state footprint suitable for eventual small-FPGA deployment. Before hardware mapping, we evaluate the software implementation using a model-side power proxy derived from MACs, weight and activation traffic, and spiking state updates under shared FP16 assumptions. On simulated CARLA event corpora, the deployment-oriented model achieves 0.9464 objectness F1, 0.9978 grid-level mAP, and 0.8987 m distance Mean Absolute Error at an estimated 1.92 mW proxy cost, while maintaining performance on unseen generalization test sequences.

Johnson-Scott, Zac [ORNL]↗

Event-Driven Neuromorphic Accelerator (Caspian)

Software repository for the Caspian neuromorphic system. In order to deploy small, low-power spiking neural networks at the edge, there needs to be 1) an FPGA design for an event simulator to evaluate these neural networks as well as 2) a high-performance cycle-accurate simulator for training these spiking neural networks. This software package solves these problems by providing the Caspian simulator and the µCaspian hardware design in SystemVerilog.

Mitchell, JohnParker [Microsoft Corporation, Redmo↗

Cryogenic growth of aluminum: Structural morphology, optical properties, superconductivity, and microwave dielectric loss

We explore the molecular beam epitaxy synthesis of superconducting aluminum thin films grown on c-plane sapphire substrates at cryogenic temperatures of 6 K and compare their behavior with films synthesized at room temperature. We demonstrate that cryogenic growth increases structural disorder, producing crystalline grains that modify the optical, electrical, and superconducting properties of aluminum. We observe that cryogenic deposition changes the color of aluminum from fully reflective to yellow and correlate the pseudodielectric function and reflectance with structural changes in the film. We find that smaller grain sizes enhance the superconductivity of aluminum, increasing its critical temperature and critical field. We then estimate the superconducting gap and coherence length of Cooper pairs in aluminum in the presence of disorder. In conclusion, we fabricate superconducting microwave resonators on these films and find that, independently of the growth temperature, the system is dominated by two-level system loss with similar quality factors in the high- and low-power regimes. We further measure a higher kinetic inductance in the cryogenically grown films.

36 MATERIALS SCIENCE↗

Low-Power, Load-Balancing Whole Home Electrification Solution: Cooperative Research and Development (Final Report)

Testing was conducted at the Systems Performance Laboratory in NREL’s Energy Systems Integration Facility to test the performance of 120V wall-mounted heat pumps, 120V heat pump water heaters (HPWH), Electric Vehicle Supply Equipment (EVSE), and other plug-in loads, using NeoCharge Smart Splitters and whole home energy software as appropriate. Four different simulated occupancy scenarios were used to evaluate the package of technology and controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗

AI-Powered Knowledge Graphs for Neuromorphic and Energy-Efficient Computing

The surge in scientific literature obscures breakthroughs and hinders the discovery of new research paths. We propose an artificial intelligence (AI) powered framework using large language models (LLMs) and knowledge graphs (KGs) to automate parts of scientific discovery, focusing on energy-efficient AI circuits. Our hybrid approach combines LLMs, structured data, and ontology-based reasoning to construct a comprehensive knowledge graph that integrates insights across computational neuroscience, spiking neuron models, learning rules, architectural motifs, and neuromorphic device technologies. This multi-domain representation enables the generation of hypotheses that connect biological function with implementable, energy-efficient hardware architectures. Using KG embeddings and graph neural networks, the framework generates hypotheses for novel circuits, validates them through optimization on exascale HPC systems, and with tools like SuperNeuro and Fugu, the most promising designs will be prototyped in hardware. This open-source system aims to accelerate discoveries and bridging neuroscience with hardware innovation, drive collaboration, and unlock new opportunities in low-power AI computing.

Gautam, Ashish [ORNL]↗

Innovating Distributed Embedded Energy Prize (InDEEP): A Lessons Learned Report

The U.S. Department of Energy's Water Power Technologies Office (WPTO) launched the Innovating Distributed Embedded Energy Prize (InDEEP) in March 2023 to accelerate innovation in Distributed Embedded Energy Conversion Technologies (DEEC-Tec) for ocean wave energy. Administered by the National Laboratory of the Rockies (NLR) with technical support from Sandia National Laboratories (SNL), InDEEP focused on the development of small, distributed, and embeddable energy converters (DEECs) and their integration into scalable DEEC-Tec metamaterials for marine renewable energy applications. Spanning three phases over two years, InDEEP awarded approximately $2.3 million to teams from academia, industry, and startups. Phase I emphasized conceptual design. Phase II moved into the prototyping of individual DEECs. Phase III required integration into functional DEEC-Tec metamaterial prototypes. Across 60 submissions, teams explored a wide range of energy conversion mechanisms - including piezoelectric, variable-capacitance, ionic, and inductive methods. Note, the prize did not include the design nor demonstration of ocean wave energy conversion systems. Rather, the prize only required participants to design and demonstrate individual DEECs and corresponding DEEC-Tec metamaterials. This prize utilized a mix of novel and proven techniques to attract participants from outside marine energy, including an engagement leaderboard, robust recruitment, technical expert mentorship, and a suite of technical trainings. Key insights from the competition emphasized that DEEC-Tec metamaterials must be intentionally designed to produce beneficial emergent behaviors - advantages that go beyond simply combining multiple DEEC units. Top-performing teams showed that thoughtful design of system architecture, coordinated deformation, and systems adaptabilities could unlock meaningful performance gains both at the DEEC system level and DEEC-Tec metamaterial system level. A critical realization was that many DEEC-Tec metamaterials could benefit from being designed to accept lower-frequency energy inputs and shift those into higher-frequencies per each DEEC making up the respective DEEC-Tec metamaterial. Other important takeaways included the need for rigorous and quantitative performance testing, effective integration of power conditioning electronics, and the pivotal role of material science in enabling innovative, adaptive DEEC-Tec-based energy conversion designs. InDEEP also helped establish a growing DEEC-Tec community of practitioners, attracting participants from beyond traditional marine energy sectors. Through a strong support infrastructure, InDEEP fostered early-stage innovation and laid a foundation for future DEEC-Tec-based ocean wave energy conversion solutions - positioning DEEC-Tec as a promising pathway toward scalable, resilient ocean wave energy conversion. Through focused R&D of individual DEECs and their integration into DEEC-Tec metamaterials, alongside a growing, multidisciplinary community catalyzed by InDEEP, there is a strong opportunity to drive a disruptive shift in ocean wave energy conversion design and development. This convergence of novel architectures, emergent behaviors, and collaborative innovation positions DEEC-Tec as a transformative approach, moving the field from rigid, centralized energy conversion-based designs to resilient, modular systems highly adaptable for real-world ocean wave energy conversion applications.

16 TIDAL AND WAVE POWER↗

Designs for scalable construction of hybrid quantum photonic cavities

Nanophotonic resonators are central to numerous applications, from efficient spin–photon interfaces to laser oscillators and precision sensing. A leading approach consists of photonic crystal (PhC) cavities, which have been realized in a wide range of dielectric materials. However, translating proof-of-concept devices into a functional system entails a number of additional challenges, inspiring new approaches that combine resonators with wavelength-scale confinement and high quality factors; scalable integration with integrated circuits and photonic circuits; electrical or mechanical cavity tuning; and, in many cases, a need for heterogeneous integration with functional materials such as III–V semiconductors or diamond color centers for spin–photon interfaces. Here we introduce a concept that generates a finely tunable PhC cavity at a selected wavelength between two heterogeneous optical materials whose properties satisfy the above requirements. The cavity is formed by stamping a hard-to-process material with simple waveguide geometries on top of an easy-to-process material consisting of dielectric grating mirrors and active tuning capability. We simulate our concept for the particularly challenging design problem of multiplexed quantum repeaters based on arrays of cavity-coupled diamond color centers, achieving theoretically calculated unloaded quality factors of 106, mode volumes as small as 1.2(λ/neff)3, and maintaining >60% total on-chip collection efficiency of fluorescent photons. We further introduce a method of low-power piezoelectric tuning of these hybrid diamond cavities, simulating optical resonance shifts up to ∼760 GHz and color center fluorescence tuning of 5 GHz independent of cavity tuning. These results will motivate integrated photonic cavities toward larger scale systems-compatible designs.

Greenspon, Andrew S. (ORCID:0000000296317568)↗

Assessment of Thin Plastic Scintillation Detectors for Beta-Particle Measurements at the Advanced Test Reactor Critical Facility

The Fission Wire Measurement System is a custom measurement system designed in the 1960s to measure the beta-particle activity of irradiated uranium-aluminum fission wires. This measurement is conducted to determine the fission rate profile of the Advanced Reactor Test Critical facility. The Advanced Test Reactor Critical facility is an open-pool, low-power test reactor used to qualify experiment configurations and verify core models prior to full-power experiment irradiations in the Advanced Test Reactor. Power distribution measurements in ATR-C use uranium-aluminum wires that are distributed throughout the core to validate simulation and modeling results. These measurements require from 340 to 1500 wires to be irradiated and measured within a 12-hour window. The system consists of 4 measurement channels and one reference channel, each with a 2-pi proportional gas flow detector and the measurement channels each have an automated sample changer. The gas flow detectors are of a custom design for this detector system that use methane gas with a large anode wire compared to modern proportional counters. These detectors, which are nearly 60 years old are irreplaceable. The measurements from these gas detectors are affected by the gas flow rate, atmospheric and line pressure, and are very sensitive to the applied high voltage. Recent improvements have been made to the control and data acquisition system, but the detectors have remained the same. The nature of the measurement of the fission product decay activity is such that the energy spectrum of the signal is changing with time. Thin, 250-um thick, plastic scintillators were commercially obtained as a potential replacement for the gas flow detectors. The original calibration of the uranium-aluminum fission wires was conducted in 1965 using a series of irradiations of gold foils and the wires in a well-characterized thermal neutron field. These measurements provided a time-dependent fission rate conversion factor from the gold foil data to calibrate the fission wires based on the response from the 2-pi proportional gas detectors. Transitioning to the new detectors requires qualification and testing. The sensitivity of the scintillators to changes in the energy spectrum of the fission wires and translation of the calibration factor have been completed. These measurements indicated that the sensitivity of the scintillators over time changes at a different rate than the sensitivity of the gas flow detectors. However, the inverse activity of measurements of both detector types is linear with time. Initial results indicate that the scintillator detectors will be a sufficient replacement for the gas detectors with minor adjustments to the fission rate conversion factor. Replacement of the detectors will improve the fission wire measurements and provide a more stable and reliable measurement system.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Ecobuoys for Scalable Oceanography

An approach to scalable surface-drifting buoys is needed to enable the high spatial and temporal resolution of oceanographic data that the science and meteorological communities are asking for. With the number of active buoys predicted to increase by a factor of 100 or more, the impact on the environment becomes even more important. Here, we present a pathway to a scalable and sustainable generation of buoys. We identify the main criteria to be used when developing such buoys to be low cost, with reliable data and neutral or even positive environmental impact. For each buoy subsystem—hull, electronics, energy generation and storage, sensors, and communication system—cutting-edge technological solutions are presented, many of them from emerging research in marine or other disciplines. We then assess the potential solutions against the design criteria and plot a path toward small, environmentally friendly, low-cost, and low-power buoys.

54 ENVIRONMENTAL SCIENCES↗

Photo-Swing CO2 Capture Using a Branched Polyethylenimine As Sorbents and TiN Light Absorber

Using branched polyethylenimine as the sorbent material for dilute CO2 capture, a photo-swing method is demonstrated in an industrially relevant support architecture using titanium nitride (TiN) nanosized light absorbers coupled with low-power LEDs with irradiances up to 420 mW cm-2. The photo-swing desorption process is applied to dry and humid streams of 400 ppm CO2 diluted in N2. Consistent with known sorption mechanisms for aminopolymers, humid CO2 streams increased the CO2 uptake, in our case by ~30%. The photo-swing CO2 capture desorbed ~83% and ~100% CO2 compared to thermally-driven desorption over the same period for a dry and humid CO2 stream, respectively. The photo-swing CO2 capture exhibits robust performance over >90 cycles without significant signs of photo(thermal) induced sorbent degradation. This work lays the groundwork for photo-swing DAC technology as a scalable, energy-efficient solution for CO2 capture, well-suited for modular systems in remote locations utilizing intermittent renewable energy sources.

36 MATERIALS SCIENCE↗

Heteroepitaxial control of thickness, strain, and domain architecture in few-layer ferroelectric tin monochalcogenides

Thin-film epitaxy and epitaxial strain have been widely exploited to tune domain configurations, switching behavior, and ferroic properties in conventional three-dimensional ferroelectric thin films; however, its application to controlling the properties of two-dimensional (2D) ferroelectrics has remained largely unexplored. Here, using SnX (X = Se, S) as a model system, we demonstrate heteroepitaxial control of thickness, strain state, and domain architecture in few-layer ferroelectric SnX via growth on monolayer MoS2 van der Waals (vdW) templates. Compared with conventional growth, MoS2-templated heteroepitaxy promotes epitaxial alignment, yielding ultrathin SnSe films with improved crystalline quality, full areal coverage, and enlarged lateral dimensions. Strong interfacial epitaxial coupling induces pronounced in-plane strain and stabilizes a hierarchical ferroelastic domain architecture, in which long-range 90° stripe domains are further subdivided into nanoscale rotational variants, as revealed by scanning transmission electron microscopy and synchrotron X-ray microscopy. Piezoresponse force microscopy and second-harmonic polarimetry confirm robust in-plane polarization, while ferroelectricity in SnSe is established through polarization-electric field hysteresis and nonvolatile ferroelectric resistive switching with on/off ratios approaching 1000. A nonvolatile, switchable ferroelectric diode effect further evidences direct coupling between polarization and charge transport. Notably, ferroelectric switchability exhibits a strong thickness dependence and is preserved only below ∼10 layers. This vdW heteroepitaxial strategy is further extended to ferroelectric SnS. The seamless heteroepitaxial integration of 2D ferroelectrics with CMOS-compatible, wafer-scale MoS2 templates provides a general and scalable route for strain-enabled structural and ferroelectric engineering in emerging memory and low-power optoelectronic applications.

Wang, Yueyin↗

Analog-to-digital converter based on voltage-controlled superconducting devices

The increasing demand for cryogenic electronics in superconducting and quantum computing systems calls for ultra-energy-efficient data conversion architectures that remain functional at deep cryogenic temperatures. Here, in this work, we present the first design of a voltage-controlled superconducting flash analog-to-digital converter (ADC) based on a voltage-controlled quantum-enhanced Josephson junction field-effect transistor (JJFET). Exploiting its strong gate tunability and transistor-like behavior, the JJFET offers a scalable alternative to conventional current-controlled superconducting devices while aligning naturally with CMOS-style design methodologies. Building on our previously developed Verilog-A compact model calibrated to experimental data, we design and simulate a three-bit JJFET-based flash ADC targeted for integration within cryogenic control and readout circuitry in quantum computing. The core comparator block is realized through careful bias current selection and augmented with a three-terminal nanocryotron to precisely define reference voltages. Cascaded JJFET comparators ensure robust voltage gain, cascadability, and logic-level restoration across stages. Simulation results demonstrate accurate quantization behavior with ultra-low power dissipation, underscoring the feasibility of voltage-driven superconducting mixed-signal circuits. This work establishes a critical step toward unifying superconducting logic and data conversion, paving the way for scalable cryogenic architectures in quantum–classical co-processors, low-power artificial intelligence accelerators, and next-generation energy-constrained computing platforms.

Analog-to-digital converter↗

Numerical Simulation of a Natural Convection–Driven Air-Cooled Reactor Cavity Cooling System Experiment

Ensuring the efficient removal of decay heat from the reactor vessel is essential for the safety of advanced reactor technologies. Several Generation-IV concepts incorporate variations in the reactor vessel cooling systems to achieve this objective. High-temperature gas-cooled reactors utilize a reactor cavity cooling system (RCCS), a passive ex-vessel system designed to operate without active components or external power during accident conditions. The RCCS removes decay heat primarily through radiative and convective heat transfer mechanisms. Here, this study presents a comprehensive validation of a computational fluid dynamics Reynolds-averaged Navier-Stokes model for the University of Wisconsin-Madison air-cooled RCCS facility. Validation was conducted for both high- and low-power natural convection cases under a uniform heating profile. Near-wall resolution was found to be critical for accurately modeling natural convection in the RCCS; employing an all-𝑦 + wall treatment resulted in wall temperature discrepancies exceeding 50 °⁢𝐶 compared to a wall-resolved mesh. Thermal-hydraulic behaviors under natural and forced convection conditions were compared within the heated cavity and RCCS. A turbulence model sensitivity analysis indicated that low-Reynolds number k-ɛ, k-ω shear stress transport (SST), and Reynolds stress transport models produce similar wall temperature predictions. A buoyancy modeling sensitivity study revealed that the Boussinesq approximation significantly underpredicted thermal-hydraulic behavior in the RCCS. Based on these findings, modeling recommendations are provided. The validated data set along with identified sensitivities refine the modeling of natural convection in the RCCS. The information produced by this study supports RCCS design, optimization, and safety evaluations, enabling the calibration and verification of reduced-order thermal-hydraulic models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

High-speed fiber-coupled terahertz time-domain spectroscopy system using a bias-free plasmonic source

We demonstrate a high-speed fiber-coupled terahertz time-domain spectroscopy (THz-TDS) system using a bias-free plasmonic terahertz source. The system is powered by a compact, low-power femtosecond fiber laser oscillator that drives a dual-branch fiber amplifier to pump and probe a plasmonic terahertz source and detector, respectively. A polarization-maintaining, fiber-coupled optical delay line is employed to precisely control the temporal offset between the pump and probe beams through a compact, robust platform. Operating in the self-similar amplification regime, the fiber amplifiers are engineered to mitigate nonlinear pulse distortion and dispersion while delivering robust, high-energy pulses at a 1560-nm wavelength, with an output power exceeding 326 mW. In reflection mode, the THz-TDS system achieves a peak dynamic range of 81 dB and a bandwidth greater than 3.5 THz at a scan rate of 3.75 Hz. The utility of the system for rapid sensing is further demonstrated by quantifying the porosity and density of pharmaceutical tablets through measurements of their physical thickness and effective refractive index.

Jiang, Xinghe [University of California, Los Angel↗

Improved Charge Sensing on a SiMOS Double Quantum Dot using a Cryogenic Skipper Readout ASIC (Quandarum)

Major outstanding questions in high-energy physics such as the nature of dark matter and the existence of interactions beyond the standard model require new measurement techniques which are extremely sensitive to minute electromagnetic fields. An array of entangled spin qubits is a promising system for building novel detectors due to its combination of sensitivity and controllability. CMOS-based electron spin qubits, which have demonstrated the operational requirements for fault-tolerant quantum computing [1], offer a particular opportunity due to their compatibility with classical electronics, which allows the leveraging of decades of development of low-noise cryogenic detectors for physics. In this work, we combine a SiMOS double-quantum dot device architecture with a state-of-the-art cryoelectronic readout circuit [2-3] aimed to demonstrate improved charge readout using a single-electron transistor (SET). We identify the design characteristics for an SET that facilitate the use of on-chip classical electronics as a low-power, high-bandwidth first amplification stage and explore opportunities for sensor-readout co-design to minimize noise. This is the first of a series of steps to demonstrate high-fidelity readout of a large array of spin qubit with enough sensitivity to probe processes of interest for the investigation of beyond-standard-model physics.

Quinn, Adam [Fermilab]↗

Dielectric Resonator Design for Low Power and Low Temperature Microwave Plasma

Waveguide-based microwave plasmas generally operate at high temperatures (2000 - 6000K)[1], making it difficult to directly interface solid materials with the plasma without significant thermal damage. Dielectric microwave resonators (DMRs), long studied for wave-based manipulation of electromagnetic radiation for telecom and optics, can focus radiation to extremely small mode volumes, creating intense localized fields with low-power input.[2] This phenomenon can be used for applications ranging from efficient plasma electronics to near-ambient plasma-materials interactions. Such DMR-based plasmas have been demonstrated a handful of times in the literature, but the majority of research towards this utilize the lowest frequency resonance mode.[3], [4], [5] By carefully controlling the geometry of cylindrical resonators, a variety of electromagnetic modes can be excited. In this work, COMSOL Multiphysics simulations are used to study the electric field enhancement and absorption properties of CaTiO3 DMRs as a function of geometry and excitation frequency. Whereas previous studies have utilized the HEM111 resonance frequency to drive low power plasma excitation, we find that higher order resonance frequencies are more effective at field enhancement and result in less power loss within the dielectric material, hence less wasted heating. The effectiveness of these modes is also geometry dependent and can be computationally optimized for plasma generation. Complementing these computational efforts, we demonstrate a new closed-system reactor design built in a WR-650 waveguide and experimentally demonstrate the formation of atmospheric argon microwave plasma using < 30 W input power on DMR dimers. We observe a shifting resonance frequency as the DMRs heat in response to microwave excitation and develop a Python-based lock-in mechanism to effectively track the DMR resonance over time, leading to stable plasma operation. We use infrared thermal imaging to monitor the temperature of the DMR dimers and surrounding quartz chamber, demonstrating thermal temperatures < 60 degreesC. Finally, we utilize optical emission spectroscopy (OES) to probe the plasma properties as a function of the resonance mode.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗