Sensor Package Research Articles

Wafer-level chip-scale packaging of MEMS environmental sensors by functionalized porous PowderMEMS® micro-filters

Abstract MEMS environmental sensors, including pressure, gas, and humidity sensors, require protection from mechanical damage, particle exposure, and condensing moisture, while maintaining their ability to exchange gases with the environment. This work introduces a novel packaging approach for MEMS environmental sensors using substrate-embedded filters made from microfine powders through PowderMEMS® microfabrication technology. The study demonstrates the successful fabrication of gas permeable, functionalized PowderMEMS® filters on 200 mm Si-wafers for wafer-level packaging of MEMS environmental sensors. 
Utilizing complete Si-wafers allows for all MEMS sensors on a device wafer to be packaged in a single substrate bonding step, followed by die singulation. The processed wafers are shown to be compatible with high-temperature glass-frit substrate bonding. Alternatively, individual chips with PowderMEMS® filters can be assembled discretely onto standard semiconductor packages to serve as gas-permeable filters.
Successful hydrophobation of the inherently hydrophilic PowderMEMS® structures by deposition of hydrophobic nanofilms is demonstrated and resistance to water ingress is evaluated by immersion testing. Given that many MEMS gas sensors are cross-reactive to oxidizing gases like ozone, this study also explores the integration of ozone-degrading catalytic powder into the PowderMEMS® filters. As a proof-of-concept, commercial MEMS ozone sensors are modified with catalytic PowderMEMS® caps, and successful ozone degradation is demonstrated.
While PowderMEMS® processing is typically conducted on 200 mm Si-wafers, other suitable substrates include glass and (fiber-reinforced) polymers.

The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM)

This paper accompanies the initial public release of the EDI multi-modal SLAM dataset, a collection of long tracks recorded with a portable sensor package. These include two global shutter RGB camera feeds, LiDAR scans, as well as inertial and GNSS data from an RTK-enabled IMU-GNSS positioning module—both as satellite fixes and internally fused interpolated pose estimates. The tracks are formatted as ROS1 and ROS2 bags, with separately available calibration and ground truth data. In addition to the filtered positioning module outputs, a second form of sparse ground truth pose annotation is provided using independently surveyed visual fiducial markers as a reference. This enables the meaningful evaluation of systems that directly utilize data from the positioning module into their localization estimates, and serves as an alternative when the GNSS reference is disrupted by intermittent signals or multipath scattering. In this paper, we describe the methods used to collect the dataset, its contents, and its intended use.

Design of a Low-cost Radiation Weather Station.

Combining a traditional weather station with radiation monitors draws the public's attention to the magnitude of background radiation and its typical variation while providing early indications of unplanned radiological releases, such as nuclear power plant accidents or terrorist acts. Several networks of combined weather and radiation monitoring sensors exist, but these fail to be affordable for broad distribution. This work involves creating an affordable system to accumulate data from multiple locations into a single open-source database. The data collected should thus serve as a friendly database for high school students. The system is designed around an inexpensive sensor package featuring a cup anemometer, wind direction vane, and tip bucket rain gauge. A Raspberry Pi 4 microcomputer interfaces through RJ11 and RJ45 connectors to these and other sensors. Custom-designed circuits were implemented on printed circuit boards supporting sensor chips for temperature, pressure, humidity, and air electrical resistance. The outdoor board communicates with ultraviolet light, soil moisture, and temperature sensors, relaying data using wired connections indoors where a Raspberry Pi 4 and indoor circuit board are located. The indoor board employs wireless internet protocol to communicate with a homemade Geiger-Mueller counter and a consumer-grade temporal radon monitor. The system employs an internet connection to transfer data to a cloud-based storage system. This enables a website with continuously updated pages dedicated to each established system to display collected data. Weatherproofed fused filament fabricated indoor and outdoor cases were designed. Sensor functions were tested for functionality and accuracy.

Electrospinning - A Potential Bio-Fabrication Method for Developing Various Tissue Engineering Scaffolds

Scaffolds in tissue engineering provide essential support for new tissue growth. Such scaffolds could be fabricated from materials like natural and synthetic polymers with prime properties such as biocompatibility and mechanical strength. Among other developments made, electrospinning has been a significant factor in making intricate scaffolds that imitate the extracellular matrix of tissue. It gives various properties in the fibers for specific applications by the controlled parameter conditions like voltage and flow rate. It is innovations like multi-component fibers and 3D structures that assist in the problem of uniformity and mechanical strength. Electrospinning research still is on the front line in increasing its potential applications in tissue engineering, filtration, and drug delivery. Process parameters optimization is among the strategies deployed to lessen the electrospinning problem of bending instabilities. The modified setups offer fiber production versatility. The setups introduced include far-field electrospinning that provides long, directed nanofibers and near-field electrospinning that gives good fiber deposition. Electromechanical spinning unifies electrical and mechanical aspects to have controlled fiber properties. In the area of applications of electrospun nanofibers, so far, the areas like biomedical, environmental, energy, textile, sensor, agriculture, cosmetic, and food packaging industries come as a real versatile bunch. This potential of the technology in divergent fields is ever-growing, in ongoing research continues to enhance its effectiveness toward tissue engineering solutions.

The Effect of Metal Shielding Layer on Electrostatic Attraction Issue in Glass-Silicon Anodic Bonding.

Silicon-glass anode bonding is the key technology in the process of wafer-level packaging for MEMS sensors. During the anodic bonding process, the device may experience adhesion failure due to the influence of electric field forces. A common solution is to add a metal shielding layer between the glass substrate and the device. In order to solve the problem of device failure caused by the electrostatic attraction phenomenon, this paper designed a double-ended solidly supported cantilever beam parallel plate capacitor structure, focusing on the study of the critical size of the window opening in the metal layer for the electric field shielding effect. The metal shield consists of 400 Å of Cr and 3400 Å of Au. Based on theoretical calculations, simulation analysis, and experimental testing, it was determined that the critical size for an individual opening in the metal layer is 180 μm × 180 μm, with the movable part positioned 5 μm from the bottom, which does not lead to failure caused by stiction due to electrostatic pull-in of the detection structure. It was proven that the metal shielding layer is effective in avoiding suction problems in secondary anode bonding.

Test Flight of a Stratospheric Sonic Anemometer Prototype

Abstract Stratospheric sonic anemometers are an emerging technology for making wind velocity measurements in low pressure environments. This paper explores the challenges, design, and high-altitude testing of a digital sonic anemometer for applications including high-altitude balloon navigation, atmospheric gravity wave research, solar activity research, and planetary science on Mars. The system was flown on NASA’s Sensor Package for Attitude, Rotation, and Relative Observable Winds (SPARROW-3) balloon test flight out of Fort Sumner, New Mexico, in August 2022. The mission recorded relative wind data throughout the flight at temperatures as low as −40°C and at the balloon’s float altitude of 38 km (3.8-mb pressure; 1 mb = 1 hPa). The device surpassed all previous sonic anemometers regarding maximum operational altitude. However, only two of the three axes operated well above 32 km, leading to some validation challenges. The system achieved a velocity resolution of 0.1 m s−1 (standard deviation) and recorded three-dimensional wind measurement every 2.25 s. Future plans anticipate addressing the faulty axis and increasing performance to a resolution of 0.01 m s−1 and a wind sampling rate of 10 Hz.

A Passive-Source Ocean-Bottom Seismic Experiment in the South China Sea: Evaluations of Data Quality and Instrument Performance

Abstract This study presents a passive-source ocean-bottom seismograph (OBS) experiment conducted in the southwest subbasin of the South China Sea (SCS) aimed at exploring the geodynamic processes shaping this short-lived oceanic basin. The successful deployment and recovery of 24 passive-source OBS units, including 14 I-7C types and 10 Pankun OBS units, resulted in the acquisition of one of the most extensive passive-source seismic data sets ever recorded in the SCS. We provide comprehensive details of the experiment, with a focus on evaluating the data quality and performance of the Pankun OBS units. This evaluation includes assessments of horizontal orientation determination, leveling system effectiveness, timing accuracy, and ambient noise spectrum. In addition, we compared the waveforms recorded by the Pankun OBS units with those from land stations and I-7C units, as well as the noise spectra between Pankun and global OBSs using the same seismometer. Although these comparisons suggest that the Pankun OBS achieves satisfactory performance, we identified a few inadequacies with this new instrument, such as issues with the differential pressure gauge, clock shifts, and sensor package calibration.

Inertial Measurement Unit Self-Calibration by Quantization-Aware and Memory-Parsimonious Neural Networks

This paper introduces a methodology to compensate inertial Micro-Electro-Mechanical System (IMU-MEMS) time-varying calibration loss, induced by stress and aging. The approach relies on a periodic assessment of the sensor through specific stimuli, producing outputs which are compared with the response of a high-precision sensor, used as ground truth. At any re-calibration iteration, differences with respect to the ground truth are approximated by quantization-aware trained tiny neural networks, allowing calibration-loss compensations. Due to the unavailability of aging IMU-MEMS datasets, a synthetic dataset has been produced, taking into account aging effects with both linear and nonlinear calibration loss. Also, field-collected data in conditions of thermal stress have been used. A model relying on Dense and 1D Convolution layers was devised and compensated for an average of 1.97 g and a variance of 1.07 g2, with only 903 represented with 16 bit parameters. The proposed model can be executed on an intelligent signal processing inertial sensor in 126.4 ms. This work represents a step forward toward in-sensor machine learning computing through integrating the computing capabilities into the sensor package that hosts the accelerometer and gyroscope sensing elements.

Accessible Trail Tourism: Trail Accessibility and Difficulty Rating Approach Designed for Individuals, Including With Mobility Impairments

ABSTRACTThis study introduces a novel approach to trail accessibility and difficulty rating tailored specifically for individuals, including those with mobility impairments, aiming to promote accessible trail tourism. Grounded in theoretical frameworks of inclusive outdoor recreation, equality, and complex adaptive systems, the proposed rating system incorporates criteria addressing physical access, terrain challenges, and amenities to accommodate diverse user needs. This study employed a sensor technology, called wheeled instrumentation sensor package (WISP) within the framework of the high‐efficiency trail assessment process (HETAP) to develop a new quantitatively based trail classification scheme. A case study trail and two hypothetical synthetic data trails were used to demonstrate both the trail wheelchair accessibility binary classification approach and the proposed trail difficulty classification approach. This research pioneers trail accessibility and difficulty rating and underscores the importance of integrating accessibility considerations into trail management practices to create truly inclusive outdoor recreational experiences.

Remote detection of water stress in cotton using a center pivot irrigation system-mounted sensor package.

Much research has been invested in infrared temperature (IRT)-based methods for cotton (Gossypium hirsutism L.) water stress detection using in-field sensors, but adoption of these is low, perhaps due to logistical challenges. Alternatively, the Water Deficit Index (WDI) was developed for crop water stress assessment using remote sensors not embedded in the canopy. The objective of this research was to evaluate the performance of a sensor package-including modern IRT and normalized difference vegetation index (NDVI) sensors facing downward at 45˚, and a mini weather station-attached unintrusively to a center pivot irrigation system for detecting cotton water stress using WDI. Sensor packages were evaluated in a two-year field study that included four irrigation treatments (0, 30, 60, and 90% ET replacement) and in two production cotton fields. Overall, the tested system was effective at distinguishing crop water stress among irrigation rates. Comparison of the results to a ground-based station and simulations indicated that WDI overestimated water stress at the highest irrigation rate, but performed well otherwise. Accuracy of the system could be improved by measuring canopy coverage (Fc) from the same vantage point as the IRT and NDVI sensors (from the pivot, downward at a 45˚ angle).

Frugal infrasound: Low-cost, low-power, low-weight, and low-effort

It is possible to acquire high fidelity array infrasound data at low cost. Recording infrasound economically requires sensors and acquisition systems that are inexpensive to buy or build, and efficient to transport, power, deploy, and maintain. A variety of engineering tools and design practices can help scientists economize on cost and effort from design to data collection. The design and prototyping process is streamlined by clearly defining design priorities and intended applications, selecting user-friendly components, libraries, and platforms, and using free CAD software and low-volume manufacturers for printed circuit boards. Custom enclosures built with 3-D printing and off-the-shelf watertight boxes facilitate production of sensor packages at any production scale. The cost and effort of fieldwork can be reduced by designing for portability (to reduce cost of transport and the number of field assistants needed), ease of use (facilitating use by new field assistants), and low power (to make power systems simpler, more portable, and requiring fewer maintenance visits). We describe how all of these frugal practices were implemented in the Gem infrasound logger and how they helped support new infrasound practitioners and applications that would be impractical with other infrasound systems.

Unmanned aerial vehicles equipped with sensor packages to study spatiotemporal variations of air pollutants in industry parks.

Unmanned aerial vehicles (UAVs) equipped with a miniaturized sensor package were developed for aerial observations, which realizes aerial observations affordable to scientists in atmospheric science and achieves aerial measurements in high spatial resolution. UAVs are deployed to a variety of aerial detecting tasks in different scientific scenarios including chemical industry parks (CIPs) with hazardous gases emissions, and some places difficult for humans to reach. In this study, UAV sensing technology was deployed to detect air pollutants in a suburb, a CIP and a natural gas plant, respectively. The effects of atmospheric conditions such as the atmospheric boundary layer height, long-distance transport and atmospheric stability on the spatiotemporal variations of the air pollutants vertical profiles were investigated by the UAV. The UAV with the sensor package was deployed to capture the methane (CH4) leakages in a natural gas plant. The spatiotemporal variations of CH4 in both vertical and horizontal directions studied by UAV were employed to calculate accurate CH4 emissions, which is crucial to reducing the emissions of greenhouse gases. The low-cost UAV sensing technology for air pollutants was developed by Dr. Xiaobing Pang, who was funded by the Newton Fellowship in 2009 and worked in the University of York. This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

Assessment of a pH optode for oceanographic moored and profiling applications

AbstractAs global ocean monitoring programs and marine carbon dioxide removal methods expand, so does the need for scalable biogeochemical sensors. Currently, pH sensors are widely used to measure the ocean carbonate system on a variety of autonomous platforms. This paper assesses a commercially available optical pH sensor (optode) distributed by PyroScience GmbH for oceanographic applications. Results from this study show that the small, solid‐state pH optode demonstrates a precision of 0.001 pH and relative accuracy of 0.01 pH using an improved calibration routine outlined in the manuscript. A consistent pressure coefficient of 0.029 pH/1000 dbar is observed across multiple pH optodes tested in this study. The response time is investigated for standard and fast‐response versions over a range of temperatures and flow rates. Field deployments include direct comparison to ISFET‐based pH sensor packages for both moored and profiling platforms where the pH optodes experience sensor‐specific drift rates up to 0.006 pH d−1. In its current state, the pH optode potentially offers a viable and scalable option for short‐term field deployments and laboratory mesocosm studies, but not for long term deployments with no possibility for recalibration like on profiling floats.

Design and FEA verification of high dimensional and multi-field smart soft material

Abstract We designed a sophisticated smart soft tissue material that simulates the properties of biological soft tissue and detects three-dimensional force. Inspired by electronic skin, this material uses capacitive pressure sensors and multi-layer sensor packaging. Finite element analysis and multi-field simulation were employed for structural design and verification. The study evaluated the theory and practicality of a flexible capacitive 3D force sensor for detecting pressure and shear force. Mechanical and electrical properties were confirmed through force and electric field simulations. The 3D force detection method proved feasible, achieving sensitivity levels of 10−4 kPa −1 in the X and Y directions, and 10−3 kPa −1 in the Z direction, demonstrating the effectiveness of our design.

A Hermetic Package Technique for Multi-Functional Fiber Sensors through Pressure Boundary of Energy Systems Based on Glass Sealants

This paper presents a hermitic fiber sensor packaging technique that enables fiber sensors to be embedded in energy systems for performing multi-parameter measurements in high-temperature and strong radiation environments. A high-temperature, stable Intrinsic Fabry–Perot interferometer (IFPI) array, inscribed by a femtosecond laser direct writing scheme, is used to measure both temperature and pressure induced strain changes. To address the large disparity in thermo-expansion coefficients (TECs) between silica fibers and metal parts, glass sealants with TEC between silica optical fibers and metals were used to hermetically seal optical fiber sensors inside stainless steel metal tubes. The hermetically sealed package is validated for helium leakages between 1 MPa and 10 MPa using a helium leak detector. An IFPI sensor embedded in glass sealant was used to measure pressure. The paper demonstrates an effective technique to deploy fiber sensors to perform multi-parameter measurements in a wide range of energy systems that utilize high temperatures and strong radiation environments to achieve efficient energy production.

Proprioceptive swarms for celestial body exploration

Proprioceptive swarms for celestial body exploration

Analysis of PM2.5, black carbon, and trace metals measurements from the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS)

ABSTRACT Communities near transportation sources can be impacted by higher concentrations of particulate matter (PM) and other air pollutants. Few studies have reported on air quality in complex urban environments with multiple transportation sources. To better understand these environments, the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS) was conducted in three neighborhoods in Southeast Kansas City, Kansas. This area has several emissions sources including transportation (railyards, vehicles, diesel trucks), light industry, commercial facilities, and residential areas. Stationary samples were collected for 1-year (October 24, 2017, to October 31, 2018) at six sites using traditional sampling methods and lower-cost air sensor packages. This work examines PM less than 2.5 μm in diameter (PM2.5), black carbon (BC), and trace metals data collected during KC-TRAQS. PM2.5 filter samples showed the highest 24-h mean concentrations (9.34 μg/m3) at the sites located within 20–50 m of the railyard. Mean 24-h PM2.5 concentrations, ranging from 7.96 to 9.34 μg/m3, at all sites were lower than that of the nearby regulatory site (9.83 μg/m3). Daily maximum PM2.5 concentrations were higher at the KC-TRAQS sites (ranging from 25.31 to 43.76 μg/m3) compared to the regulatory site (20.50 μg/m3), suggesting short-duration impacts of localized emissions sources. Across the KC-TRAQS sites, 24-h averaged PM2.5 concentrations from the sensor package (P-POD) ranged from 3.24 to 5.69 µg/m3 showing that, out-of-the-box, the PM sensor underestimated the reference concentrations. KC-TRAQS was supplemented by elemental and organic carbon (EC/OC) and trace metal analysis of filter samples. The EC/OC data suggested the presence of secondary organic aerosol formation, with the highest mean concentrations observed at the site within 20 m of the railyard. Trace metals data showed daily, monthly, and seasonal variations for iron, copper, zinc, chromium, and nickel, with elevated concentrations occurring during the summer at most of the sites. Implications: This work reports on findings from a year-long air quality study in Southeast Kansas City, Kansas to understand micro-scale air quality in neighborhoods impacted by multiple emissions sources such as transportation sources (including a large railyard operation), light industry, commercial facilities, and residential areas. While dozens of studies have reported on air quality near roadways, this work will provide more information on PM2.5, black carbon, and trace metals concentrations near other transportation sources in particular railyards. This work can also inform additional field studies near railyards.

Sensor data : Understanding how real estate occupiers can transform their space and generate effective outcomes

This paper introduces sensors and their utilisation in commercial real estate for enhanced business outcomes. The paper explores the types of sensor packages prevalent in the property technology sector, and the various information streams they generate. The use of sensors in various setups to enhance space optimisation, tenant experience and operational efficiency of an estate is also considered. Finally, the paper examines the case of a globally prominent professional services company and its utilisation of a sensor solution to improve enterprise outcomes.

High resolution depth profile scanning of plankton organisms—VERTILICE

High resolution depth profile scanning of plankton organisms—VERTILICE

A novel sensor with excellent high-temperature performance for in-situ temperature measurement

Real-time access to critical information about system temperature variations is essential for evaluating system performance in some of the high-temperature and harsh environments. Given the technical difficulty of accurately obtaining the temperature of a high-temperature and harsh environment, a new sensor package structure is proposed. Combining ceramic sintering and isostatic pressure molding methods, the thermal junction is fixed in the temperature measurement end face of the alumina ceramic substrate, while the shell design threads play a role in fixing the sensor and preventing loosening. This paper conducted repeatability, upper-temperature limit, and high-temperature serviceability assessment tests on the sensor. The results show that the sensor maximum repeatability error is 2.4%. The sensor can continue to operate at 1200°C for more than 6 hours with no signal interruption and the upper limit of temperature measurement is 1307°C. The results demonstrate the feasibility and practicality of temperature measurement by this sensor in high-temperature and harsh environments.