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DOE OSTI2024

An Impedance Humidity Sensor Based on CVD Grown WSe 2 2D Films

2D materials-based planar devices have been sought after for gas and humidity sensor applications owing to their high sensitivity due to their ultrathin nature and increased surface area. Herein, 2D WSe 2 films-based planner devices were fabricated to evaluate their performance for potential application in humidity sensors. The structure and morphology of the WSe 2 sensing films were studied by Raman spectroscopy, photoluminescence, optical microscopy, and scanning electron microscopy (SEM) techniques. The relative humidity-dependent sensing performances of the 2D WSe 2 films were evaluated using current–voltage (I–V), relative impedance, and complex total impedance (electrochemical impedance spectroscopy, EIS) techniques. This sensor showed a very stable and repeatable performance investigated over the period of 18 months. The response and recovery times of the WSe 2 -based impedance sensors were found to be 40 and 30 s, respectively. The WSe 2 sensor exhibits a 2 ± 1% minimum hysteresis at a lower humidity level (50% RH) and around 8 ± 2% maximum hysteresis at relative humidity level (70% RH). This value of hysteresis is in the acceptable range during the initial investigation of any material to explore its potential for application in humidity sensors. The density functional theory (DFT) analysis was performed with the interaction from water molecules of the WSe 2 sample for a better understanding of the sensing mechanism of devices.

2D- WSe2↗

DOE OSTI2020

Cybersecurity Attacks in Vehicular Sensors

Today's modern vehicles contain anywhere from sixty to one-hundred sensors and exhibit the characteristics of Cyber-Physical-Systems (CPS). There is a high degree of coupling, cohesiveness, and interactions among vehicle's CPS components (e.g., sensors, devices, systems, systems-of-systems) across sensing, communication, and control layers. Cyber-attacks in the sensing or communication layers can compromise the security of the control layer. This paper provides a detailed review of potential cyber threats related to the sensing layer. Notably, the focus is mainly towards two categories of sensors: vehicle dynamics sensors (e.g., Tire Pressure Monitoring Systems (TPMS), magnetic encoders, and inertial sensors) and environment sensors (e.g., Light Detection and Ranging (LiDAR), ultrasonic, camera, Radio Detection and Ranging (Radar) systems, and Global Positioning System (GPS) units). Furthermore, the paper also offers perspectives through existing countermeasures from literature and stresses the need for data-driven cybersecurity solutions.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2024

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity↗

DOE OSTI2019

Rational Design of Capacitive Pressure Sensors Based on Pyramidal Microstructures for Specialized Monitoring of Biosignals

Abstract There is an increasing demand for specialized pressure sensors in various applications. Previously, capacitive pressure sensors have been shown to have wide versatility in use, with a high degree of potential tuning possible through manipulating the geometry or material selection of the dielectric layer. However, in order to make sensors that are tunable and predictable, the design and fabrication method first needs to be developed. Presented here is an improved fabrication method to achieve tunable, consistent, and reproducible pressure sensors by using a pyramid microstructured dielectric layer along with a lamination layer. The as‐produced sensor performance is able to match predicted trends. Further, a simple model based on this system is developed and its efficacy is experimentally confirmed. Then, the model to predict a wide range of material and microstructure geometric properties prior to device fabrication is used to provide trends on sensor performance. Finally, it is demonstrated that the new method can be used to targetedly design a pressure sensor for a specific application—in vitro pulse sensing.

Ruth, Sara Rachel Arussy↗

DOE OSTI2018

A Novel RFID-Based Strain Sensor for Wireless Structural Health Monitoring

Conventional tools for deformation measurement are widely used for structural health monitoring—i.e. strain gauges and fiber optic sensors—due to their relative low cost and efficiency. However, these techniques still present some drawbacks particularly in limited access locations, since their usage requires some sort of cabling or battery-driven electronics. Thus, in a few situations there may be room for new technologies for deformation monitoring of structures. One of the options are passive radio frequency identification (RFID)-based sensors. In synthesis, like conventional methods, these sensors are attached to the surface a test-piece, but are then remotely interrogated and powered by a transmitter. The solidarity of the sensor to the underlying material means that the detected signal is modified in a way that can be correlated to sample strain in a given direction. This paper encompasses the project of a wireless deformation sensor based on an inverted-F antenna focusing on its miniaturization and performance optimization. For this purpose, such an antenna was designed with the help of finite element modelling tools for operation on a 2.0 mm-thick aluminium sheet, and then experimentally validated through static loading tests. Finally, even though sensors of this kind are still in early developments, results show that RFID sensors represents a promising method for remote deformation assessment in components.

42 ENGINEERING↗

DOE OSTI2026

Ten questions concerning low-cost indoor air quality sensors: Perspectives from research and practice

Low-cost indoor air quality (IAQ) sensors are increasingly being used in homes and commercial and public buildings, driven by growing concerns about the impact of air on health, cognitive performance, and occupant wellbeing. These sensors offer a potentially transformative opportunity to increase spatial and temporal coverage of IAQ monitoring at a fraction of the cost of conventional reference instruments. However, their widespread use raises questions around accuracy, calibration, placement, data handling and interpretation, and integration into existing standards and workflows. This paper presents ten critical questions concerning the use of low-cost IAQ sensors in buildings, drawing on the latest empirical research, field deployments, and emerging practice. It discusses potential frameworks for deployment and evaluation, examines current sensor capabilities for measuring common pollutants, identifies methodological gaps in validation and uncertainty quantification, and outlines the extent to which existing IAQ standards can accommodate sensor-based evidence. The paper also explores how monitoring needs and deployment models vary by building type, the potential of real-time IAQ data to support building operations, and the ethical and legal implications of widespread sensor use. While significant challenges remain in ensuring data quality and building stakeholder trust, new applications are emerging through open data initiatives and advances in analytics and visualization. As the technology, science, and standards co-evolve, low-cost IAQ sensors are poised to become integral to routine building operation, building science, and environmental health research.

Parkinson, Thomas↗

DOE OSTI2023

Entanglement-enhanced optomechanical sensor array with application to dark matter searches

Abstract Squeezed light has long been used to enhance the precision of a single optomechanical sensor. An emerging set of proposals seeks to use arrays of optomechanical sensors to detect weak distributed forces, for applications ranging from gravity-based subterranean imaging to dark matter searches; however, a detailed investigation into the quantum-enhancement of this approach remains outstanding. Here, we propose an array of entanglement-enhanced optomechanical sensors to improve the broadband sensitivity of distributed force sensing. By coherently operating the optomechanical sensor array and distributing squeezing to entangle the optical fields, the array of sensors has a scaling advantage over independent sensors (i.e., $$\sqrt{M}\to M$$ M → M , where M is the number of sensors) due to coherence as well as joint noise suppression due to multi-partite entanglement. As an illustration, we consider entanglement-enhancement of an optomechanical accelerometer array to search for dark matter, and elucidate the challenge of realizing a quantum advantage in this context.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Evaluation of a fish-friendly self-cleaning horizontal irrigation screen using autonomous sensors

Irrigation modernisation is booming globally because of the increasing demand on water and food. However, irrigation infrastructures can injure fish or entrain them into irrigation water. Screening is an effective method to mitigate fish entrainment. In this study, two autonomous sensor devices, developed and manufactured at Pacific Northwest National Laboratory (Sensor Fish and its miniaturised version, Sensor Fish Mini) were deployed to evaluate the physical and fish passage conditions of a unique horizontal, flat-plate fish and debris screen (known as the Farmers Screen) that was installed in Oregon, USA. Only 1 of the 27 Sensor Fish Mini releases had a severe acceleration event, whereas 0 of the 37 Sensor Fish releases had severe events. The rates of severe events and amplitudes of accelerations at the Farmers Screen were significantly lower than those at other hydraulic structures, including a fish-friendly surface weir that recorded nearly 100% fish survival. Overall, the results indicated that the Farmers Screens can provide safe downstream passage for fish at irrigation diversions. This study also demonstrated that the Sensor Fish technology, including Sensor Fish Mini, is a suitable technology for evaluating irrigation structures and providing important information for the development of sustainable irrigation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Modeling active control of resistive wall mode with power saturation and sensor noise on HL-2M

The resistive wall mode (RWM) control on the HL-2M tokamak is simulated with the MARS-F code (Liu et al 2000 Phys. Plasmas 7 3681), aiming at quantifying control current and voltage requirements when more realistic issues are taken into account, i.e. the control power saturation and the sensor signal noise. The fluid model predicts a narrow stability region for the n = 1 RWM without magnetic feedback, in the 2D parameter space of the plasma pressure versus the toroidal flow speed. Magnetic feedback can fully stabilize the RWM on HL-2M. Without considering the voltage limitation and the sensor signal noise, it is found that plasma flow helps active control of the mode, by reducing the required critical feedback gain for both flux-to-current and flux-to-voltage control schemes. In the absence of the sensor signal noise, the lowest control voltage saturation level, below which the RWM control is lost, is found to roughly satisfy a linear relation to the plasma flow frequency, indicating that subsonic plasma flow is effective in relaxing the control power requirement for the RWM feedback stabilization. The presence of the sensor signal noise substantially modifies the feedback results. A statistical study finds that the sensor signal noise, with the standard deviation of 0.1 G on HL-2M, roughly doubles the required control voltage for successful mode control. The synergistic stabilization effect due to plasma flow is somewhat weakened by the presence of the sensor signal noise. At a given rotation, the tolerable voltage limit generally increases with increasing feedback gain due to the sensor signal noise.

Physics↗

DOE OSTI2022

Tunable polyvinyl chloride (PVC) and thermoplastic polyurethane (TPU)-based soft polymer gel sensors

Abstract Polyvinyl chloride (PVC) gels have recently been found to exhibit mechanoelectrical transduction under mechanical deformation. These mechanoelectrical properties of PVC gels are largely uncharacterized and the underlying transduction mechanisms are currently unknown. These soft electroactive polymers have tunable properties such as modulus and response voltage based on physical dimensions and the amount of plasticizer content within the material making them ideal candidates for complaint sensors. This study aims to investigate PVC gels comprised of various plasticizers to further investigate underlying mechanisms of mechanoelectrical transduction and broaden possible sensing applications. Plasticizers used in this study include dibutyl adipate, dibutyl phthalate, dioctyl phthalate, otherwise known as bis(2-ethylhexyl) phthalate, diisodecyl adipate, and the environmentally friendly biodegradable plasticizer acetyl tributyl citrate (ATBC). ATBC is often used in cosmetics and food packaging applications and is even used as a food additive which may lead to future biocompatibility for these gel sensors. These plasticizers are used to produce PVC gel sensors that are experimentally tested for mechanoelectrical transduction properties and sensing performance. In this study, a Langmuir adsorptive model is fit to the collected mechanoelectrical transduction data. These results are also nondimensionalized and compared to the characteristic dimensionless Langmuir adsorptive model. This simple model agrees very well with the experimental data. Additionally, a study on the mechanoelectrical transduction of an alternative polymer lattice structure, thermoplastic polyurethane (TPU), is discussed. This is a novel electroactive polymer investigated for mechanoelectrical transduction properties. This portion of the study aims to further knowledge of underlying mechanisms of mechanoelectrical transduction as well as show feasibility of additional lattices for soft polymer gel sensors. These TPU gel sensors show strikingly similar mechanoelectrical transduction properties to analogous PVC gels, insinuating that the polymer structure has a limited role in the underlying sensing mechanism and PVC itself is not unique to polymer gel sensing. The TPU-based soft polymer gel sensors however do display some level of mechanoelectrical hysteresis which may be attributed to viscoelastic properties and display a small amount of fatigue possibly due to exudation of liquid plasticizer. This study provides further characterization of mechanoelectrical response for varying plasticizers, provides a theoretical framework for underlying mechanisms, and displays the potential for further polymeric gel sensors.

Instruments & Instrumentation↗

DOE OSTI2021

Femtosecond laser fabrication of nanograting-based distributed fiber sensors for extreme environmental applications

Abstract The femtosecond laser has emerged as a powerful tool for micro- and nanoscale device fabrication. Through nonlinear ionization processes, nanometer-sized material modifications can be inscribed in transparent materials for device fabrication. This paper describes femtosecond precision inscription of nanograting in silica fiber cores to form both distributed and point fiber sensors for sensing applications in extreme environmental conditions. Through the use of scanning electron microscope imaging and laser processing optimization, high-temperature stable, Type II femtosecond laser modifications were continuously inscribed, point by point, with only an insertion loss at 1 dB m −1 or 0.001 dB per point sensor device. High-temperature performance of fiber sensors was tested at 1000 °C, which showed a temperature fluctuation of ±5.5 °C over 5 days. The low laser-induced insertion loss in optical fibers enabled the fabrication of a 1.4 m, radiation-resilient distributed fiber sensor. The in-pile testing of the distributed fiber sensor further showed that fiber sensors can execute stable and distributed temperature measurements in extreme radiation environments. Overall, this paper demonstrates that femtosecond-laser-fabricated fiber sensors are suitable measurement devices for applications in extreme environments.

Wang, Mohan (ORCID:0000000166784993)↗

DOE OSTI2021

An Active Detection Scheme for Sensor Spoofing in Grid-tied PV Systems

In this paper an active detection scheme for sensor spoofing (manipulated externally via a cyber attack) in grid-tied PV systems is discussed. The core of the proposed active detection scheme is to introduce a private (secret) watermarking signal into the control inputs of the DC-DC converter and DC-AC inverter stages to detect any malicious spoofing (manipulation) of voltage/current sensor measurements controlling both the DC-DC converter maximum power point tracking (MPPT) stage and the DC-AC inverter of the grid-tied PV system. Several types of possible spoofing mechanisms (attack models) are discussed. The proposed sensor spoofing attack detector system consists of injecting a small magnitude of digital watermarking signal (DWS) and conduct three statistical watermark tests on the reported sensor measurements to determine if a) the proposed system is healthy and operating as expected b) if sensor signals were spoofed (manipulated) externally or c) if a particular sensor is malfunctioning due to a faulty hardware. It is shown via extensive simulations that the proposed DWS approach is robust in detecting malicious external manipulation of sensors controlling the grid tied PV system. A testing platform is currently under development and the experimental results will be discussed in the conference presentation.

Ibrahim, Hasan↗

DOE OSTI2025

Digital Filter Design for Point-on-Wave Sensors: Highlighting Frequency Response Limitations and Enhancing Grid Simulation Accuracy

Data is proving to be the backbone of today's and, more importantly, tomorrow's grid. As the system changes and introduces fast-acting devices like power electronics, overall observability tends to decrease from the utility point-of-view. This can be mitigated by adding more high-fidelity sensors onto the grid, although this incurs a cost. These sensors are never ideal, and each have unique frequency responses that may influence the data produced. This may, in turn, impact the protection and control of the power grid. This paper presents a methodology of representing these point-on-wave sensors digitally by estimating digital-filter representations of them, thereby introducing means of improving the sensor models used in electromagnetic-transient (EMT) simulations. This may help with identifying potential high-frequency, sensor-induced distortions, and system resonance compensation. Three commercial-grade medium-voltage point-on-wave sensors are utilized in a lab environment to obtain experimental frequency responses with a frequency sweep, and it is shown that both Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filter representations may approximate these responses with varying degrees of accuracy, though each has their own strengths and weaknesses. It is found that, in general, FIR estimation better approximates these sensors than IIR estimation does.

Wilson, Aaron [ORNL] (ORCID:0000000327331697)↗

DOE OSTI2019

A method for estimating the amplitude response of smartphone built-in microphone sensors below 4 kHz

A method for estimating the amplitude response of built-in smartphone microphone sensors is pre- sented. The method is intended to be accessible to the general public, and comparison calibration measurements are performed in a non-isolated environment using conventional consumer products. A double reference sensor scheme is set up, consisting of a MB3 digital microbarometer (reference over the 0.5–2 Hz octave bands) and the iPrecisionMic smartphone microphone (reference above the 2 Hz octave band). The amplitude response of the iPrecisionMic sensor is first evaluated over the 1–2000 Hz octave bands. The amplitude response of three Samsung Galaxy S8 built-in smart- phone microphone sensors is then measured over the 0.5–2000 Hz octave bands. The Redvox Infrasound Recorder application (app) for Android is used to measure acoustic signals with the built-in smartphone microphone sensors. Amplitude response models in terms of digital gain are estimated for the test sensors based on the results. Last, self-noise levels for the iPrecisionMic and Samsung Galaxy S8 microphones are estimated and compared to infrasound ambient noise models. Results show an experimental capability for estimating the amplitude response of built-in smartphone microphone sensors in a non-isolated environment with conventional consumer products.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Review—Electrolytic Metal Atoms Enabled Manufacturing of Nanostructured Sensor Electrodes

Sensing materials play a key role in the successful implementation of electrochemical sensors, and nanotechnology has emerged as an important and rapidly growing field for stimulating the innovation of high-performance sensors. The fabrication, characterization, and evaluation of the nanostructured electrodes are therefore a focus of this field. Compared to a variety of dry and wet technologies which have been extensively developed for this purpose, electrochemical methods are typically convenient, highly effective, and potentially low-cost for the production of different nanostructures. This minireview is designed to introduce a unique electrochemical method - electrolytic metal-atom enabled manufacturing (EM 2 ) and its application in electrochemical sensors. The EM 2 technique employs electrolytic metal atoms generated from their corresponding salt precursor as a tool to nanostructure a wide range of substrate electrodes used in electrochemical sensors, based on a one-pot electrochemical deposition and dissolution of the metal atoms in the same electrolyte bath. Briefly, the metal atoms are electrodeposited on a substrate electrode during the cathode reduction, and they are selectively removed from the substrate during the subsequent anode oxidation. Because of the interactions between the electrolytic metal atoms and the substrate atoms, the repetitive electrodeposition and dissolution of the former on the substrate enable the nanostructuration of the substrate, particularly within its surface layers. The nanostructured electrodes have demonstrated very attractive performance for the determination of numerous analytes, such as high sensitivity and selectivity, high interference tolerance, and low detection limits. However, the EM 2 technique and the application of the resulting nanostructured electrodes in electrochemical sensors and beyond have still been very limitedly investigated. In order to bring the community from academic, industries, agencies, and customers together to develop the EM 2 technique and advance electrochemical sensor systems, this minireview will introduce the thermodynamic and kinetic fundamentals of this technique, the characterization of resulting nanostructures, the analysis of their electrochemical behavior, and the implementation of this technique for the development of advanced sensor electrodes. Finally, an outlook with a focus on further research areas is provided.

Jiang, Junhua (ORCID:0000000324379812)↗

DOE OSTI2021

A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

In this article, the coverage area prediction of piezoelectric sensor network for detecting a specific type of under-surface crack in plate-like structures is addressed. In particular, this article proposes a simplified framework to estimate the coverage of any given sensor network arrangement when a critical defect is known. Based on numerical results from finite element methods (FEM), a simplified framework to estimate coverage area of any given network arrangement is developed. Using such a simplified framework, one can avoid time-consuming procedure of evaluating numerous FEM models in estimating sensor network coverage. Back-scatter fields of partial cracks are estimated using a proposed function, whose parameters are estimated from the results of a limited number of FEM simulations. The proposed function efficiently predicts the back-scattered field of any combination of transmitters and receivers for a given crack geometry. Superposition is used to estimate the coverage area of an arbitrary piezoelectric (e.g., PZT) sensor network. It is shown that the coverage area of a sensor network depends on both sensor network geometry and defect properties (e.g., crack inclination) and it is not necessarily a linear function of the number of sensors. Furthermore, it is shown that the network arrangement has an important effect on the geometry of the coverage area. Experimental results of a network of 14 PZTs in two clusters confirm the accuracy of the method.

Engineering↗

DOE OSTI2024

Zero-crosstalk silicon photonic refractive index sensor with subwavelength gratings

Abstract Silicon photonic index sensors have received significant attention for label-free bio and gas-sensing applications, offering cost-effective and scalable solutions. Here, we introduce an ultra-compact silicon photonic refractive index sensor that leverages zero-crosstalk singularity responses enabled by subwavelength gratings. The subwavelength gratings are precisely engineered to achieve an anisotropic perturbation-led zero-crosstalk, resulting in a single transmission dip singularity in the spectrum that is independent of device length. The sensor is optimized for the transverse magnetic mode operation, where the subwavelength gratings are arranged perpendicular to the propagation direction to support a leaky-like mode and maximize the evanescent field interaction with the analyte space. Experimental results demonstrate a high wavelength sensitivity of − 410 nm/RIU and an intensity sensitivity of 395 dB/RIU, with a compact device footprint of approximately 82.8 μm 2 . Distinct from other resonant and interferometric sensors, our approach provides an FSR-free single-dip spectral response on a small device footprint, overcoming common challenges faced by traditional sensors, such as signal/phase ambiguity, sensitivity fading, limited detection range, and the necessity for large device footprints. This makes our sensor ideal for simplified intensity interrogation. The proposed sensor holds promise for a range of on-chip refractive index sensing applications, from gas to biochemical detection, representing a significant step towards efficient and miniaturized photonic sensing solutions. Graphical Abstract

Materials Science↗

DOE OSTI2023

Schneider Springs Fire Study 2023 for Ecosystem Respiration Rates: Surface Water Chemistry and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.

54 ENVIRONMENTAL SCIENCES↗