Improved RF calibration techniques - dc potentiometer microwave insertion loss test set
Dual-channel microwave insertion loss test set which incorporates power meter coaxial thermistors with dc nulling scheme
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Dual-channel microwave insertion loss test set which incorporates power meter coaxial thermistors with dc nulling scheme
Thermistor mount for dc potentiometer insertion loss test set
The temperature stabilization requirements of unchopped thermistor bolometers and thermopile detectors are analyzed.
The next-generation of cryogenic neutrinoless double-beta decay experiments require increasingly fast readout in order to improve background discrimination. These experiments, operated as cryogenic calorimeters at ∼ 10 mK, are usually read out by high-impedance neutron transmutation doped (NTD) thermistors, which provide good energy resolution, but are limited by ∼ 1 ms response times. Superconducting detectors, such as transition-edge sensors (TESs) with a time resolution of ∼ 100 μs, offer superior timing performance over NTD semiconductor bolometers. To make this technology viable for an application to a thousand or more channels, multiplexed readout is necessary in order to minimize the thermal load and radioactive contamination induced by the readout. Frequency-domain multiplexing readout (fMUX) for TESs, previously developed at Berkeley Lab and McGill University, is currently in use for mm-wave telescopes with detector sampling rates in the order of 100 Hz. We demonstrate a new readout system, based on the McGill/Berkeley digital fMux readout, to satisfy the higher bandwidth and noise requirements of the next generation of TES-instrumented cryogenic calorimeters. Each multiplexing readout module comprises 10 superconducting resonators in the 1–5 MHz range and a DC superconducting quantum interference device (DC-SQUID), interfaced to high-speed field programmable gate array (FPGA)-based electronics for digital signal processing and low-latency SQUID feedback. The new readout samples detectors at 156 kHz, three orders of magnitude faster than its cosmology-oriented predecessor, and demonstrates a stable feedback bandwidth of 3 kHz in a real TES-based system.
The Resolve instrument onboard the X-Ray Imaging and Spectroscopy Mission (XRISM) consists of an array of 6 × 6 silicon-thermistor microcalorimeters cooled down to 50 mK and a high-throughput X-ray mirror assembly (XMA) with a focal length of 5.6 m. XRISM is a recovery mission of ASTRO-H/Hitomi, and the Resolve instrument is a rebuild of the ASTRO-H Soft X-ray spectrometer (SXS) and the Soft X-ray Telescope (SXT) that achieved energy resolution of ∼ 5 eV FWHM on orbit, with several important changes based on lessons learned from ASTRO-H. The flight models of the Dewar and the electronics boxes were fabricated, and the instrument test and calibration were conducted in 2021. By tuning the cryocooler frequencies, energy resolution better than 4.9 eV FWHM at 6 keV was demonstrated for all 36 pixels and high-resolution grade events, as well as energy-scale accuracy better than 2 eV up to 30 keV. The immunity of the detectors to microvibration, electrical conduction, and radiation was evaluated. The instrument was delivered to the spacecraft system in April 2022. The XMA was tested and calibrated separately. Its angular resolution is 1.27′, and the effective area of the mirror itself is 570 cm 2 at 1 keV and 424 cm 2 at 6 keV. We report the design and the major changes from the ASTRO-H SXS, the integration, and the results of the instrument test.
This project investigated how clouds and atmosphere-sea ice interactions shape the central Arctic surface energy budget using observations from the MOSAiC expedition and coordinated model experiments. Analyses focused on three themes. First, a new method applied to thermistor string data revealed that snow thermal conductivity is systematically higher than assumed in most models, strongly influencing conductive heat flux and sea ice growth, especially under clear skies. Second, a full annual cycle of surface energy budget observations, combined with detailed cloud microphysical retrievals, demonstrated how cloud regimes regulate radiative, turbulent, and conductive fluxes, driving seasonal contrasts in sea ice energy balance: in winter, radiative forcing elicits strong turbulent and conductive responses, while in summer excess energy is primarily partitioned into surface melt. Third, these observations were used to evaluate and improve regional and global forecast models. While some models captured key Arctic cloud-radiation states, most exhibited persistent deficiencies in representing liquid-containing clouds, snow-on-sea-ice processes, and flux responses to radiative forcing. Together, these results provide unprecedented benchmarks for understanding coupled Arctic processes, improve parameterizations of snow, sea ice, and cloud interactions, and highlight critical pathways by which atmospheric variability drives sea ice change in a rapidly evolving Arctic system. Lastly, the project was a resounding success, resulting in 38 peer-reviewed publications and dozens of presentations, while also supporting an early career scientist.
Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.
A simple transistor circuit uses a thermistor to change the vidicon target potential in relation to temperature differences.
An oscillator circuit and a thermistor, in close proximity to a light bulb, periodically alter the heat output of the bulb by varying the voltage across its filament. Use of this simulator permits checkout tests on pneumographs.
Miniature micropower solid-state circuit measures and telemeters the body temperature of laboratory animals over periods up to two years. The circuit employs a thermistor as a temperature sensing element and an fm transmitter. It is constructed from conventional discrete components or integrated circuits.
Compact, reliable thermostat provides a temperature readout signal and a continuous temperature-control output for temperature monitoring by automatic checkout equipment or telemetry systems. It employs a solid state circuit in a housing rigidly attached to a thermistor probe.
Temperature measurements of grassland, desert and water surfaces using IR radiometer found to compare favorably with miniature thermistors
Electronic circuit, based on the principle of increased thermistor resistance corresponding to decreases in temperature provides an automatic level control for liquid nitrogen cold traps. The electronically controlled apparatus is practically service-free, requiring only occasional reliability checks.
Error computation in radiosonde and rocketsonde atmospheric temperature sensors by using thermistors of different emissivities
Heat transfer telemetry from free flight models in hypersonic wind tunnels, using miniature FM transmitter with thin film thermistor sensor
Radiometric Temperature Reference uses a thermistor as both a heating and sensing element to maintain its resistance at a preselected level to continuously control the power supplying it. The fixed infrared radiation level must be simple, rugged, and capable of high temperature operation.
Dual channel waveguide insertion loss test set for calibrations at 90 GHz in radio astronomy and communication systems, using sprayed thermistor mount
Negative-temperature coefficient device /thermistor/ in series with a lamp filament alleviates high filament surge current during initial application of power. The thermistor should be selected for a cold resistance approximately equal to one fourth of the normal hot resistance of the filaments to be protected.