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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

An Integrated FDD System for HVAC&R Based on Virtual Sensors

According to the U.S Department of Energy, space heating, ventilation and air conditioning system account for 40% of residential primary energy use and for 30% of primary energy use in commercial buildings. A study released by the Energy Information Administration indicated that packaged air conditioners are widely used in 46% of all commercial buildings in the U.S. This study indicates that the annual cooling energy consumption related to the packaged air conditioner is about 160 trillion Btus. Therefore, an automated FDD system that can automatically detect and diagnose faults and evaluate fault impacts has the potential for improving energy efficiency along with reducing service costs and comfort complaints. The primary bottlenecks to diagnostic implementation in the field are the high initial costs of additional sensors. To prevent those limitations, virtual sensors with low cost measurements and simple models are developed to estimate quantities that would be expensive and or difficult to measure directly. The use of virtual sensors can reduce costs compared to the use of real sensors and provide additional information for economic assessment. The virtual sensor can be embedded in a permanently installed control or monitoring system and continuous monitoring potentially leads to early detection of faults. The virtual sensors of individual equipment components can be integrated to estimate overall diagnostic information using the output of each virtual sensor.

Kim, Woohyun↗
DOE OSTI2018

Thermoelectric Generator Powered Wireless Sensor Node Prototype for Nuclear Applications

This report presents the development a TEG-powered WSN prototype that could be used in nuclear applications. Different design considerations that are important in assembling different components of a WSN were carefully taken into consideration. In designed WSN is compatible to operate with low-power generating TEG and high-power generating TEG based on application requirements. Also, to maintain appropriate power level across different sensor node components, direct current-to-direct current converter with maximum peak power tracking algorithm is implemented. Storage device with real-time clock is embedded to enable local data storage and real-time time stamping. The wireless communication module selected and implemented is Zig Bee protocol. To accommodate different operating conditions and any loss of power from TEG due to unforeseen reasons, backup battery system is also implemented. Entire assembly is performed on a 2-layer printed circuit board and tested for operation. The outcome was successful and it also provided data to validate the mathematical model developed to estimate average power consumption of a WSN under different operating conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Signal Processing of Multiplexed Optical PWM Signals for Sensor Arrays in Nuclear Environments

Safe and effective generation of terrestrial nuclear power greatly benefits from the actionable data provided by the array of sensors located throughout a plant to provide a holistic online indication of reactor operation. This array includes sensors for monitoring coolant flow and pressure, temperature and heat transfer, radiation levels, structure health monitoring, and other critical parameters for reactor operation. While sensors capable of measuring these parameters have been developed, the electronics used in the pre-amplification and analog-to-digital conversion of the small signals they produce are extremely sensitive and susceptible to damage by high-temperatures and radiation environments nuclear reactors encounter while generating power. The small signals from sensors in nuclear power plants (NPPs) are transmitted over long cable runs which introduce dispersion artifacts into the signals of interest as well as electromagnetic interference (EMI) from lighting fixtures, pumps, mains electricity, and other equipment. To overcome these challenges, a front-end digitization (FREND) platform has been developed to use radiation-tolerant electronics to multiplex, amplify, and optically encode signals from an array of sensors for transmission over an optical fiber to mitigate dispersion and EMI artifacts from long runs of electrical cabling. To recover the optically transmitted data, a signal processing scheme based on 1-dimensional template matching to an indexing channel is described herein and demonstrated to have an effective bit-depth of 9.2 bits (1%). This scheme has been validated in proof-of-concept, non-nuclear testing and preliminary experimental results show good agreement between the measured optical output and and sensor input signals. The FREND system represents a low-loss data link between sensors in nuclear environments and data acquisition hardware which is aimed at improving the signal-to-noise ratio of the data acquired from these sensors to provide better information to operators and researchers.

Sweeney, Dan↗
DOE OSTI2024

Hot, cold, or just right? An infrared biometric sensor to improve occupant comfort and reduce overcooling in buildings via closed-loop control

To improve occupant comfort and save energy in buildings, we have developed a closed-loop air conditioning (AC) sensor-controller that predicts occupant thermal sensation from the thermographic measurement of skin temperature distribution, then uses this information to reduce overcooling (cooling-energy overuse that discomforts occupants) by regulating AC output. Taking measures to protect privacy, it combines thermal-infrared (TIR) and color (visible spectrum) cameras with machine vision to measure the skin-surface temperature profile. Since the human thermoregulation system uses skin blood flow to maintain thermoneutrality, the distribution of skin temperature can be used to predict warm, neutral, and cool thermal states. We conducted a series of human-subject thermal-sensation trials in cold-to-hot environments, measuring skin temperatures and recording thermal sensation votes. We then trained random-forest classification machine-learning models (classifiers) to estimate thermal sensation from skin temperatures or skin-temperature differences. The estimated thermal sensation was input to a proportional integral (PI) control algorithm for the AC, targeting a sensation level between neutral and warm. Our sensor-controller includes a sensor assembly, server software, and client software. The server software orients the cameras and transmits images to the client software, which in turn assesses occupant skin temperature distribution, estimates occupant thermal sensation, and controls AC operation. A demonstration conducted in a conference room in an office building near Houston, TX showed that our system reduced overcooling, decreasing AC load by 42% when the room was occupied while improving occupant comfort (fraction of “comfortable” votes) by 15 percentage points.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Harnessing the Quantum Zeno Effect in superconducting qubits for particle detection

Superconducting qubits, originally developed for quantum computing, are emerging as a potentially powerful tool for detecting low-energy particle interactions, such as dark matter and neutrinos. These devices can register energy deposits as small as a few meV, dramatically lowering the detection threshold compared to conventional sensors. However, their deployment in rare-event searches is hampered by a critical and unresolved background: Two-Level Systems (TLSes). TLSes are material defects that can scramble qubit frequencies and coherence times in a way that resembles particle energy deposits. Such false signals can critically limit the sensitivity and extend experimental runtimes for qubit-based sensors by years. This talk introduces a novel method to eliminate TLSes as a background source in superconducting qubit-based detectors. By harnessing the Quantum Zeno Effect (QZE), a well-established quantum phenomenon where frequent observation inhibits system evolution, I will discuss the possibility of “freezing” these TLS defects in place. This effectively suppresses their interference, stabilizes qubit behavior, and opens the door to using TLSes themselves as auxiliary sensors. I have already identified target TLSes and observed early signs of QZE-like dynamics in Fermilab-fabricated devices. The method builds on my existing collaborations at Fermilab’s Quantum Information Testbed (QUIET), with access to low muon flux cryogenic facilities 100 meters underground, control electronics, and expert mentors across multiple institutions. By removing a key bottleneck to superconducting sensor deployment, this research targets advancing the development of a general-purpose technique to enhance sensitivity, reduce false positives, and accelerate discovery in searches for dark matter, neutrinos, and other rare phenomena.

Seidel, Olivia [Texas U., Arlington]↗
DOE OSTI2018

Test beam measurement of ams H35 HV-CMOS capacitively coupled pixel sensor prototypes with high-resistivity substrate

In the context of the studies of the ATLAS High Luminosity LHC programme, radiation tolerant pixel detectors in CMOS technologies are investigated. To evaluate the effects of substrate resistivity on CMOS sensor performance, the H35DEMO demonstrator, containing different diode and amplifier designs, was produced in ams H35 HV-CMOS technology using four different substrate resistivities spanning from 80 cm to 1000 cm. A glueing process using a high-precision flip-chip machine was developed in order to capacitively couple the sensors to FE-I4 Readout ASIC using a thin layer of epoxy glue with good uniformity over a large surface. The resulting assemblies were measured in beam test at the Fermilab Test Beam Facilities with 120 GeV protons and CERN SPS H8 beamline using 180 GeV pions. Furthermore, the in-time efficiency and tracking properties measured for the different sensor types are shown to be compatible with the ATLAS ITk requirements for its pixel sensors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

A data-driven CO 2 leakage detection using seismic data and spatial–temporal densely connected convolutional neural networks

In carbon capture and sequestration (also known as carbon capture and storage, or CCS), developing effective monitoring methods is needed to detect and respond to CO 2 leakage. CO 2 leakage detection methods rely on geophysical observations and monitoring sensor network. However, traditional methods usually require the development of site-specific physical models and expert interpretation, and the effectiveness of these methods can be limited to different application locations, operational scenarios, and conditions. Here, we developed a novel data-driven leakage detection method based on densely connected convolutional neural networks. Our method is an end-to-end detection approach, that differs from conventional leakage monitoring methods by directly learning a mapping relationship between seismic data and the CO 2 leakage mass. To account for the spatial and temporal characteristics of seismic data, our novel networks architecture combines 1D and 2D convolutional neural networks. To overcome the computational expense of solving optimization problems, we apply a densely-connecting strategy in our network architecture that reduces the number of network parameters. Based on the features generated by our convolutional neural networks, we further incorporate a long short-term memory network to utilize time-sequential information, which further improves the detection accuracy. Lastly, we employ our detection method to synthetic seismic datasets generated based on flow simulations of a hypothetical CO 2 storage scenario with injection into a partially compartmentalized sandstone storage reservoir. To evaluate method performance, we conducted multiple experiments including a random leakage test, a sequential test, and a robustness test. Numerical results show that our CO 2 leakage detection method successfully detects the leakage and accurately predicts the leakage mass, suggesting that it has the potential for application in monitoring of real CO 2 storage sites.

58 GEOSCIENCES↗
DOE OSTI2020

High Temperature Gas Sensor for Coal Combustion System

Robust gas sensors that offer real-time feedback about combustion in coal-fired power plants promise greater energy efficiency with fewer harmful emissions while also improving the bottom line for power generators. Currently, no technology meets this objective. Therefore, the objectives of this project are to develop an accurate, robust, reliable, high temperature sensor offering near real-time feedback to plant operators using a novel catalytic/non-catalytic sensor design to detect target gases available for oxidization. Such a sensor would inform power plant operators how to adjust the amount of fuel and air for an optimal performance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Integration of sensors through additive manufacturing leading to increased efficiencies of gas turbines for power generation and propulsion

To realize the full capability of additively manufactured components in complex energy systems, it is imperative to minimize early component failures during development phases and during operation. Traditional field feedback timelines and offline inspection protocols significantly reduce the design-manufacturing iteration times. To address this specific question, the project developed and demonstrated a method for the integration of sensors into complex components through additive manufacturing. The team used gas turbine engines as a platform, which meets the need of both power generation and propulsion and offer opportunities for cost reductions and efficiency increases. The innovation of this intelligent integration of sensors into complex components uniquely customized to address questions of integrity and durability for additively manufactured components. With real-time sensing data from additively manufactured components, turbine manufacturers will realize higher efficiencies, reduced component failures, and a 30-50% acceleration in product deployment of high efficiency gas turbine components due to a faster reduction in component risk assessment under actual operating conditions. This is a transformative shift towards a data-driven design and qualification of additively manufactured gas turbine components. To directly integrate sensors into additively manufactured components with all the complexities of actual hardware, powder bed fusion (direct metal laser sintering) and laser metal deposition technologies was developed. Validation took take place in two university laboratories both of which contain actual engine hardware and closely simulate a gas turbine prior to demonstrating the technology in a turbine development test. Indeed, two major technologies from this research cold impact turbine systems in the near future: (1) higher efficiency materials and designs enabled by additive manufacturing with 50% faster design to manufacturing cycle time, to enable faster time-to-market targets; and (2) integration of sensors into additively manufactured components enabling broad health and condition based prognostics for faster component and engine risk reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Workshop on Integrated Sensor Systems for Manufacturing Applications (Workshop Report)

On January 25th and 26th, the Department of Energy’s Advanced Manufacturing Office (AMO) held the first in a series of workshops on different topics related to semiconductor research and development (R&D). This workshop focused on integrated sensor system R&D for manufacturing applications. As AMO is housed within the office of Energy Efficiency and Renewable Energy (EERE), the workshop addressed not only industry needs and R&D opportunities, but also the impacts that improvements in sensor systems can have on energy efficiency and greenhouse gas production. The output of this workshop will inform AMO’s future portfolio of R&D investments, provide perspectives on trends, drivers, and challenges for next generation semiconductor sensor systems, and help the stakeholder community understand the opportunities on the horizon.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Engineering Scale Testing of Robotic Inspection Tools for Double Shell Tanks at Hanford - 18349

Waste found in the annulus of the AY-102 double-shell tank (DST) at Hanford has prompted the need for the development of inspection tools that are able to access confined spaces around and underneath the tanks. During the last year, Florida International University (FIU) has been developing inspection tools that are capable of accessing the tank floors through the air supply line, the air refractory channels and the drain lines. This effort has led to the development of a pneumatic pipe crawler and a miniature rover. In this paper, updates to the inspection tool designs and the full scale testing of both systems are presented. The tools provide visual feedback for the operator, carrying with them onboard cameras and light sources. The images are streamed back live via a tether, which also provides power to the devices. To increase the sensing capabilities of both tools, temperature, humidity and radiation sensor modules are being integrated onto the developed systems, and can be interchanged depending on the inspection objectives. The miniature rover measures 7 cm in length and 3.8 cm in width, and travels upside down on the bottom of the tank to avoid debris accumulated in the channels. The video is also being processed real-time to provide control of the unit semi-autonomously. The pipe crawler measures approximately 76 cm in length and 6.4 cm in diameter, and travels using pneumatic actuators that emulate the peristaltic movement contractions typical of worm type robots. A full-scale sectional mock-up of the DST foundation, refractory system and annulus is currently being developed as a test-bed for the testing of the inspection tools. The intention of the test-bed is to demonstrate the viability of using both inspection tools in configurations similar to the actual tank. The test-bed includes a 2.43 m wide section of both tank liners, refractory channels and concrete foundation with drain slots. The test-bed is designed to be modular so that various plate thicknesses can be easily utilized and different refractory configurations can be incorporated. Currently, the refractory channels are of the tree type structure with turns that are approximately 30 degrees. Both inspection tools were demonstrated in the mock-up facility. The miniature rover ran successfully through the drain slots from the annulus to central plenum and had no issues making the 90-degree turns. The peristaltic crawler was able to navigate through the 7.62 cm air supply line from the annulus to the central plenum. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Final Scientific/Technical Report, Multi-Sensor Inspection and Robotic Systems for Dry Storage Casks

Once removed from service, fuel rod assemblies are cooled in a pool and then placed in dry storage until they can be transported to a repository for disposal. The extended duration that used nuclear fuel spends in dry storage makes it prudent to be able to nondestructively inspect the dry storage casks. The degradation mechanisms of most concern are chloride-induced stress corrosion cracking of the stainless steel canister that confines the spent fuel and distributed cracking of the concrete in the overpack structure. Multi-sensor inspection and robotic systems were researched, developed, built, and tested. One system operates completely outside the cask to inspect the concrete. The other system, known as the PRINSE system, for Proactive Robotic Inspection of Nuclear Storage Enclosures, enters the cask through an outlet vent and navigates around the outer surface of the stainless steel canister. The PRINSE system delivers sensors for: (i) real-time characterization of the canister surface in order to assess whether chlorides are present, (ii) detecting the presence of cracks using shear-horizontal ultrasonic guided waves, (iii) measuring the temperature of the canister surface, and (iv) a gamma radiation counter. The four sensing modalities are applicable to any cask containing a stainless steel canister, however the robotic delivery system is designed specifically for Holtec’s HI-STORM family of casks. Horizontal axis casks have exposed concrete surfaces. A fully contactless air-coupled scanning ultrasonic test platform and a frequency-wavenumber domain data analysis method are used for these concrete structures. Analysis, numerical simulation and experimental results demonstrate that distributed cracks in concrete can be detected and cracked regions localized within a scanned region of concrete. Vertical axis casks (like the HI-STORM family) have steel-clad concrete overpacks. In a separate effort, a semi-coupled test platform and a guided wave attenuation-based data analysis method are used for disbond detection. Analysis, numerical simulation and experimental results show that the bonding conditions of steel-concrete interfaces can be quantitatively characterized using the guided wave signal analysis scheme. The PRINSE system is designed for vertical axis dry storage casks, specifically the HI-STORM family. The double pulse laser-induced breakdown spectroscopy (LIBS) system takes advantage of an optical fiber to deliver intense light to the canister surface that enables surface composition characterization in-situ in real time. Chlorine concentrations as low as 10 mg/m2 were detected on stainless steel. Additionally, a simpler laser setup was created to detect sodium as a surrogate for chlorine, and sodium was detectable when the chlorine concentration was as low as 0.5 mg/m2. The electromagnetic acoustic transducers (EMATs) enable detection of stress corrosion cracks. The EMATs generate shear-horizontal waves that propagate around the canister and are reflected by cracks enabling 100% of the canister weld lines to be inspected. The EMAT-based crack detection system was tested at the Pacific Northwest National Laboratory on a canister containing blind defects and was shown to detect the crack sizes it was designed to detect. The PRINSE system is a novel marsupial robot. The command center and winch outside the cask control the delivery arm and train of cars that traverse the outside of the canister from the cask ventilation system. The sensors are housed in the cargo bays of three cars that comprise the train, which is lowered to the bottom of the canister by the winch. Encoders on the winch enable the sensors to be delivered to a prescribed location, e.g., for re-inspection of a problem area. The PRINSE system does not mar the canister surface, can be extracted manually in the case of a power failure, and is designed for an elevated temperature and gamma radiation environment, although not all components of the prototype are made from the final materials. The PRINSE system was tested on a full canister that was placed inside a HI-STORM cask at the Holtec Manufacturing Division. It was also demonstrated on a full-height mockup at Penn State to a live audience.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Post-hazard condition assessment of nuclear piping-equipment systems: Novel approach to feature extraction and deep learning

Over the past decade, the use of artificial intelligence techniques in the field of health-monitoring has gained significant interest, especially for structures such as building and bridges. However, applications to industrial systems such as equipment-piping systems in nuclear plants have not been explored. Here, in this paper, it is shown that the existing techniques developed for buildings and bridges cannot be extended directly to equipment-piping systems as the response of such systems is governed by multiple localized modes unlike that in buildings and bridges. This paper proposes a new approach that consists of three key aspects: (i) a novel vector of degradation-sensitive features extracted from measured data, (ii) using a deep Artificial Neural Network (ANN) for diagnosis of degradation location and degradation severity, and (iii) consideration of uncertainty in degradation severity when training the ANN. Degradation in piping-equipment systems can occur due to flow-accelerated erosion and corrosion. These locations can potentially exhibit damage such as localized yielding or initiation of cracking due to an external event such as an earthquake. Moreover, such locations can at times go undetected by current inspection techniques. Therefore, a robust framework is needed for detection of degradation after a seismic event. This manuscript proposes a proof-of-concept framework, which utilizes data collected from sensors to generate a deep ANN database for predicting degraded locations and severity in a piping-equipment system. Degradation severity is classified as minor, moderate, and severe. In the suggested methodology, a novel vector of degradation-sensitive features is extracted from the sensor data to train the ANN. A simple piping-equipment system is selected to demonstrate feature extraction as a means to simplify pattern recognition, explore the design and parameters of an ANN, and develop a sensor placement strategy. The effectiveness of the proposed framework is demonstrated on a realistic primary safety system of a two-loop nuclear reactor. It is shown that the proposed post-hazard condition assessment framework is able to detect degraded locations along with the severity levels, including minor degradation, with considerably higher accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

A Chimeric LBT-GFP Biosensor Exhibits Antithetical Fluorescence Responses to Ca 2+ and Dy 3+ Binding

Rare earth elements (REEs) are critical components in emerging technologies, but their mining and refining processes are often laborious, costly, and environmentally damaging. Developing green and efficient separation methods for REEs is crucial. Biomolecular approaches using lanthanide-binding proteins and peptides show promise for selective REE extraction and separation. In this study, we present the design and characterization of a genetically encoded fluorescence indicator (GEFI) construct that combines a superfolder green fluorescent protein (sfGFP) with a dual lanthanide-binding tag (2×dLBT). The 2×dLBT insert induces conformational changes in sfGFP upon lanthanide binding, modulating the fluorescence intensity. The sfGFP-2×dLBT biosensor exhibited distinct fluorescence responses to different lanthanide ions, with the highest dynamic range observed for heavy REEs like dysprosium (Dy 3+ ). Interestingly, the sensor displayed an antithetical response, where low concentrations of lanthanides initially quenched the fluorescence, but higher concentrations led to a significant fluorescence increase (1.5-fold). The Ca 2+ ion on the other hand showed only a dose-dependent quenching of the fluorescence response. Based on these observations, the biphasic response of the biosensor to lanthanides was eliminated by pretreating the sensor with calcium, which further expanded the dynamic range up to 3-fold for Dy 3+ . The lanthanide-selective and concentration-dependent fluorescence changes of the sfGFP-2×dLBT biosensor demonstrate its potential as a platform for developing specific sensors for various REEs. These sensors could enable rapid and cost-effective determination of REE composition in complex mixtures, facilitating the separation and recovery of critical REEs from electronic waste and other REE-containing sources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Fast broad-band photon detector based on quantum well devices and charge-integrating electronics for non-invasive FEL monitoring

The recent evolution of free-electron lasers has not been matched by the development of adequate beam-monitoring instrumentation. However, for both experimental and diagnostics purposes, it is crucial to keep such photon beams under control, avoiding at the same time the absorption of the beam and the possible destruction of the detector. These requirements can be fulfilled by utilizing fast and non-invasive photon detectors operated in situ, upstream from the experimental station. From this perspective, sensors based on Quantum Well (QW) devices can be the key to detecting ultra-short light pulses. In fact, owing to their high electron mobility, InGaAs/InAlAs QW devices operated at room temperature exhibit sub-nanosecond response times. Their direct, low-energy band gap renders them capable of detecting photons ranging from visible to X-ray. Furthermore, the 2D electron gas forming inside the QW is responsible for a charge amplification mechanism, which increases the charge collection efficiency of these devices. In order to acquire the signals produced by these QW sensors, a novel readout electronics has been developed. It is based on a high-speed charge integrator, which allows short, low-intensity current pulses to be read within a 50-ns window. The integrated signal is acquired through an ADC and the entire process can be performed at a 10-MHz repetition rate. This work provides a detailed description of the development of the QW detectors and the acquisition electronics, as well as reporting the main experimental results, which show how these tools are well suited for the realization of fast, broad-band beam monitors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗