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Propellant Mass Gauging in a Spherical Tank under Micro-Gravity Conditions Using Capacitance Plate Arrays and Machine Learning
Propellant mass gauging under micro-gravity conditions is a challenging task due to the unpredictable position and shape of the fuel body inside the tank. Micro-gravity conditions are common for orbiting satellites and rockets that operate on limited fuel supplies. Capacitance sensors have been investigated for this task in recent years; however, the effect of various positions and shapes of the fuel body is not analyzed in detail. In this paper, we investigate this with various fill types, such as annular, core-annular, and stratified fills at different positions. We compare the performance among several curve-fitting-based approaches and a machine-learning-based approach, the latter of which offers superior performance in estimating the fuel content.
Experimental Assessment of a Novel Touchless Interface for Intraprocedural Imaging Review
Purpose: To examine the feasibility of a novel technology platform that enables real-time touchless interaction with radiology images in both a simulated and an actual clinical setting. Materials and Methods: This platform offers three different modes for image interaction. The gesture recognition mode uses a depth camera to detect the user’s hand gestures which are translated to image manipulation commands. The light projection mode uses the same camera to detect finger point-and-tap movements above the icons which are projected on a surface to activate the commands. The capacitive sensing mode is enabled by a handheld, portable device, over which finger movements are detected by capacitive sensors to control the image review. Following initial feedback, light projection and capacitive sensing modes were selected for further testing by comparing with the conventional mode of image interaction in time trials for performing a series of standardized image manipulation tasks. Finally, the usability of the technology platform was examined in actual clinical procedures. Results: The light projection and the capacitive sensing modes were evaluated in the time trials and exhibited 60% and 71% reduction in time, respectively, relative to the control mode (p < 0.001). Clinical feasibility for this platform was demonstrated in three actual interventional radiology cases. Conclusion: Accessing, navigating, and extracting relevant information from patient images intraprocedurally are cumbersome and time-consuming tasks that affect safety, efficiency, and decision-making during image-guided procedures. This study demonstrated that the novel technology addressed this issue by allowing touchless interaction with these images in the sterile field.
Simultaneous moisture content and mass flow measurements in wood chip flows using coupled dielectric and impact sensors
An 8-electrode capacitance tomography (ECT) sensor was built and used to measure moisture content (MC) and mass flow of pine chip flows. The device was capable of directly measuring total water quantity in a sample but was sensitive to both dry matter and moisture, and therefore required a second measurement of mass flow to calculate MC. Two means of calculating the mass flow were used: the first being an impact sensor to measure total mass flow, and the second a volumetric approach based on measuring total area occupied by wood in images generated using the capacitance sensor’s tomographic mode. Tests were made on 109 groups of wood chips ranging in moisture content from 14% to 120% (dry basis) and wet weight of 280 to 1100 g. Sixty groups were randomly selected as a calibration set, and the remaining were used for validation of the sensor’s performance. For the combined capacitance/force transducer system, root mean square errors of prediction (RMSEP) for wet mass flow and moisture content were 13.42% and 16.61%, respectively. RMSEP using the combined volumetric mass flow/capacitance sensor for dry mass flow and moisture content were 22.89% and 24.16%, respectively. Either of the approaches was concluded to be feasible for prediction of moisture content in pine chip flows, but combining the impact and capacitance sensors was easier to implement. As a result, in situations where flows could not be impeded, however, the tomographic approach would likely be more useful.
Evaluation of Three Types of Electric Field Sensors
On June 3-4, 2025, we evaluated three types of electric-field (E-field) sensors: capacitive electrodes, stainless-steel stakes, and porous pots - at two electromagnetic (EM) stations (PWBVI and PWAOF) on Aqueduct Mesa at the Nevada National Security Site. We compared calibrated time series and derived metrics including power spectral density, root-mean-square (RMS) amplitude, signal-to-noise ratio (SNR), and detectability of power line harmonics and Schumann resonance. The objective was to identify an alternative E field sensor with higher SNR than the existing capacitive electrodes. Our data demonstrates that stainless-steel electrodes perform best, with the highest SNR and the most consistent detection of power-line harmonics and Schumann resonance among the three sensor types; they may be used as a supplement to, or replacement for, the existing capacitive electrodes.
Nano-engineering the material structure of preferentially oriented nano-graphitic carbon for making high-performance electrochemical micro-sensors
Direct synthesis of thin-film carbon nanomaterials on oxide-coated silicon substrates provides a viable pathway for building a dense array of miniaturized (micron-scale) electrochemical sensors with high performance. However, material synthesis generally involves many parameters, making material engineering based on trial and error highly inefficient. Here, we report a two-pronged strategy for producing engineered thin-film carbon nanomaterials that have a nano-graphitic structure. First, we introduce a variant of the metal-induced graphitization technique that generates micron-scale islands of nano-graphitic carbon materials directly on oxide-coated silicon substrates. A novel feature of our material synthesis is that, through substrate engineering, the orientation of graphitic planes within the film aligns preferentially with the silicon substrate. This feature allows us to use the Raman spectroscopy for quantifying structural properties of the sensor surface, where the electrochemical processes occur. Second, we find phenomenological models for predicting the amplitudes of the redox current and the sensor capacitance from the material structure, quantified by Raman. Our results indicate that the key to achieving high-performance micro-sensors from nano-graphitic carbon is to increase both the density of point defects and the size of the graphitic crystallites. Our study offers a viable strategy for building planar electrochemical micro-sensors with high-performance.
Predicting critical heat flux using localized sensing at invisible vapor-liquid interfaces
Predicting critical heat flux (CHF) in two-phase electronics cooling systems remains a significant challenge due to the sudden onset of boiling crisis and the difficulty in directly visualizing vapor-liquid interfaces. Existing sensing methods rely on lagging temperature measurements, optically accessible systems, or spatially averaged signals that cannot pinpoint CHF initiation at localized high-heat-flux regions. Here, we report a planar capacitive sensing approach that enables real-time, localized detection of vapor-liquid interface dynamics for CHF prediction in boiling heat transfer. The capacitive sensor exploits the dielectric constant difference between liquid and vapor phases to capture bubble nucleation, growth, and departure dynamics with a temporal resolution down to 2 ms. The capacitive sensing reveals distinct signals across boiling regimes: from high-frequency fluctuations during strong nucleate boiling to low-frequency fluctuations with increased amplitudes when approaching CHF. The multi-sensor array experiments demonstrate real-time localized sensing, where each sensor responds exclusively to boiling in its immediate vicinity without crosstalk from neighboring regions. This non-intrusive sensing approach provides predictive rather than lagging sensing signals of CHF occurrence, offering predictive diagnosis of two-phase liquid cooling for the thermal management of high-power-density electronics.
Characterization of the CMS Endcap Timing Layer readout chip prototype with charge injection
We present the characterization of a readout Application-Specific Integrated Circuit (ASIC) for the CMS Endcap Timing Layer (ETL) of the High-Luminosity LHC upgrade with charge injection. The ASIC, named ETROC and developed in a 65 nm CMOS technology, reads out a 16× 16 pixel matrix of the Low-Gain Avalanche Detector (LGAD). The jitter contribution from ETROC is required to be below 40 ps to achieve the 50 ps overall time resolution per hit. The analog readout circuits in ETROC consist of the preamplifier and the discriminator. The preamplifier handles the LGAD charge signal with the most probable value of around 15 fC. The discriminator generates the digital pulse, which provides the Time-Of-Arrival (TOA, leading edge) and Time-Over-Threshold (TOT, pulse width) information. The prototype of ETROC (ETROC0) that implements a single channel of analog readout circuits has been evaluated with charge injection. The jitter of the analog readout circuits, measured from the discriminator's leading edge, is better than 16 ps for a charge larger than 15 fC with the sensor capacitance. The time walk resulting from different pulse heights can be corrected using the TOT measurement. The time resolution distribution has a standard deviation of 29 ps after the time-walk correction from the charge injection. At room temperature, the preamplifier's power consumption is measured to be 0.74 mW and 1.53 mW per pixel in the low- and high-power mode, respectively. Finally, the measured power consumption of the discriminator is 0.84 mW per pixel. With the ASIC alone or the LGAD sensor, The characterization performances fulfill the ETL's challenging requirements.
High-efficiency frost and ice control via sensing-assisted nanovibrational slippery surfaces
Frost and ice accretions on surfaces pose persistent challenges across numerous industrial, residential and transportation systems. While various removal strategies exist, they often suffer from limited effectiveness or high energy consumption, such as frosting delay, ice crack generation, and Joule heating. Here, in this work, we report a novel integrated approach combining vibrational quasi-liquid surface (QLS) and capacitive sensing for efficient condensate, frost, and ice management. Compared to Joule heating, our approach does not rely on complete melting and evaporation for removal, resulting in 68% and 95% energy savings for frost and ice removal, respectively. Our QLS coating significantly reduces surface retention forces, achieving 91% and 87% less residual mass compared to hydrophilic surfaces for frost and ice removal through surface nanovibration, respectively. The integrated capacitive sensor provides real-time detection of different phase states, enabling on-demand removal in precise timeframes. This sensor-assisted approach showed 3.8 times lower energy consumption compared to conventional Joule heating for defrosting. This synergistic integration of surface engineering, nanovibration, and intelligent sensing represents a significant advancement in phase change processes, offering an energy-efficient solution for frost and ice mitigation in energy-intensive systems.
Optomechanical Design of Compact Laminar Flexure Bending Mechanism for Elliptically Bent Hard X-ray Mirrors
As a part of the Argonne Strategic Partnership Project (SPP) 85E77, collaboration between Argonne National Laboratory (ANL) and Shanghai Institute of Applied Physics (SINAP), has produced designs for a precision compact flexure bending mechanism to provide elliptically shaped 90-mm and 160-mm long hard x-ray mirrors. The design utilizes Argonne's laminar nanopositioning flexure technique. The flexure mirror bending mechanism will be incorporated into the beamline upgrade project at the Shanghai Synchrotron Radiation Facility (SSRF). Additionally, an Argonne Laboratory-Directed Research and Development (LDRD) project at the Advanced Photon Source (APS) has adopted a modified optomechanical design of the precision compact mirror benders for 300-mm-long hard x-ray mirrors with integrated profile monitoring and feedback, which are described in this paper. The mirror benders are designed with configurations for open-loop or closed-loop controls. Capacitive sensors can be applied to the mirror benders to ensure positioning reproducibility. Design specifications as well as finite element analyses results of the compact mirror benders for hard x-ray mirrors with trapezoid and rectangular shapes are discussed in this paper.
A MEMS dynamic mechanical analyzer for in situ viscoelastic characterization of 3D printed nanostructures
Cellular metamaterial structures with sub-micron features have shown the ability to become excellent energy absorbing materials for impact mitigation due to the enhanced mechanical properties of materials at the nanoscale. However, in order to optimize the design of these energy absorbing metamaterial structures we need to be able to measure the dynamic properties of the sub-micron features such as storage and loss moduli and the loss factor. Therefore, at scale testing is required to capture the scale, temperature, and strain rate dependent material properties of these nanoscale materials. This study presents the design, fabrication, and calibration of a MEMS-based dynamic mechanical analyzer (DMA) that can be directly integrated with the two photon lithography (TPL) process commonly used to fabricate metamaterial structures with nanoscale features. The MEMS-based DMA consists of a chevron style thermal actuator used to generate a tensile load on the structure and two differential capacitive sensors on each side of the structure used to measure load and displacement. This design demonstrated 1.5 ± 0.75 nm displacement resolution and 104 ± 52 nN load resolution, respectively. Dynamic mechanical analysis was successfully conducted on a single nanowire feature printed between the load and displacement stages of the MEMS device with testing frequencies ranging between 0.01–10 Hz and testing temperatures ranging between 22 °C–47 °C. These initial tests on an exemplar TPL part demonstrate that the printed nanowire behaves as a viscoelastic material wherein the transition from glassy to viscous behavior has already set in at the room temperature.
Machine learning control of an elliptically bent hard x-ray mirror
This article showcases the high-resolution control of an elliptically bent hard X-ray mirror optics at the Advanced Photon Source. The mirror uses a compact laminar flexure bending mechanism to achieve elliptical shapes covering a large range of focal distances. An array of capacitive sensors are used as a surface profiler for in-situ monitoring of the mirror shape. Machine learning and control techniques were used to change the mirror shape and focus the incident X-ray at predefined focal planes. The mirror surface shape error can be controlled to be within 40 nm rms with high repeatability. This technique gives the capability to focus incident X-ray beam within a range of focal distances corresponding to shape deformation range of a mirror optics. This work would be beneficial for controlling similar adaptive optics for multiple adaptive optics systems.
Tunable Impedance Spectroscopy Sensors via Selective Nanoporous Materials.
Impedance spectroscopy was leveraged to directly detect the sorption of I 2 by selective adsorption into nanoporous metal organic frameworks (MOF). Films of three different types of MOF frameworks, respectively, were drop cast onto platinum interdigitated electrodes, dried, and exposed to gaseous I 2 at 25, 40, or 70 C. The MOF frameworks varied in topology from small pores (equivalent to I 2 diameter) to large pore frameworks. The combination of the chemistry of the framework and pore size dictated quantity and kinetics of I 2 adsorption. Air, argon, methanol, and water were found to produce minimal changes in ZIF-8 impedance. Independent of MOF framework characteristics, all resultant sensors showed high response to I 2 in air. As an example of sensor output, I 2 was readily detected at 25 C in air within 720 s of exposure, using an un-optimized sensor geometry with a small pored MOF. Further optimization of sensor geometry, decreasing MOF film thicknesses and maximizing sensor capacitance, will enable faster detection of trace I 2 .
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.
Passive, Capacitive, Interdigitated Comb Sensors: Towards a Data-Driven, Mechanistic Understanding of Surface Insulation Resistance
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Capacitive Shear Stress Sensor with DC Sensing Capability for Fluid Flow Measurements.
Abstract not provided.
Capacitive Shear Stress Sensor with DC Sensing Capability for Fluid Flow Measurements.
Abstract not provided.
Capacitance-Based Dimensional Change Sensors for In-Pile Materials Measurements
Advanced fuel compositions, such as accident tolerate fuels (ATF), are an active area of developing in the nuclear power industry. The long-term performance of these newly developed fuels is estimated through physics-based simulation models of irradiation-, temperature-, pressure-, etc.-induced material degradation. As these fuels are deployed in test reactors, measurement and characterization of the fuel pin evolution is used to validate prediction models. In-pile material evolution parameters, such as fuel rod pressurization, fuel stack and cladding elongation, and cladding diameter, are commonly measured using a linear voltage differential transformer (LVDT). However, LVDTs are bulky and limited to lower (350-500C) temperature operation. The high power density and small size of most experimental positions in high performance research reactors used for accelerated materials irradiation studies generally precludes the use of LVDTs in these reactors. There is a critical need for sensors that provide real-time data regarding material evolution under highly accelerated irradiation. These sensors would ideally have a small profile and the ability to withstand irradiation at extremely high dose rates and temperatures for extended periods of time. A capacitance-based sensor is currently under development at the University of Tennessee to provide a direct measurement of in-pile dimensional change during irradiation. Sensor response was simulated using AutoCAD Electromagnetic field simulator (EMS) for a variety of sensor materials and configurations and fuel pin swelling conditions. Initial results of these simulations are summarized and areas of ongoing research and development are discussed.