An Automated Microfluidic Analyzer for In Situ Monitoring of Total Alkalinity

Trends development and applications on electrophoresis techniques of slab gel, capillary, microchip/microfluidic capillary, and isotachophoresis

This review describes the various electrophoresis techniques involved in slab gel, capillary, microchip, and isotachophoresis. Each technique offers distinct advantages and limitations in terms of resolution, sensitivity, speed, capacity, and cost of resources. While the manuscript provides an overview of the setup methods for these electrophoresis techniques, it also evaluates their unique characteristics and summarizes a range of analytical applications, including environmental monitoring, proteomics and genomics analysis, clinical diagnostics, pharmaceutical analysis, and biochemical research. This review contributes to the future directions of available electrophoresis techniques and aids knowledge seekers or practitioners in selecting the most appropriate methods for their specific analytical needs. This review highlights the strengths and potential applications of each technique, providing insights into advancing analytical methodologies and exploring emerging trends across scientific disciplines.

New Capability in Autonomous Ocean Carbon Observations Using the Autosub Long-Range AUV Equipped with Novel pH and Total Alkalinity Sensors

The development of marine autonomous platforms has improved our capability to gather ocean observations at fine spatial scales and high temporal frequency, which can be used to better measure, characterize, and model ocean carbon. As part of the OCEANIDS program, novel carbonate sensors were integrated into the Autosub Long-Range (ALR) autonomous underwater vehicle (AUV) and deployed in the Celtic Sea. Autonomous Lab-On-Chip (LOC) sensors measured pH and total alkalinity (TA) while onboard the ALR. Using interpolation, the ALR-sensor data set is compared against CTD co-samples. The average differences between the LOC sensor and co-sample pH range from -0.011 to -0.015. The TA sensor data agrees with co-samples within 1-2 μmol kg-1 on average. Biogeochemical water properties differing between CTD and ALR observations reveal correlations to carbonate parameter variations. The LOC sensors enabled the characterization of the marine carbonate system from autonomous subsurface measurements for the first time. Sensor pH and TA data were used to calculate dissolved inorganic carbon (DIC), partial pressure of CO2 (pCO2), and aragonite saturation state (ΩAr) and are compared with CTD co-samples with mean residuals of 4-7 μmol kg-1, 10-17 μatm, and -0.03 to -0.06, respectively. Future perspectives on sensor deployment and analysis are discussed.

Autonomous Sensor for In Situ Measurements of Total Alkalinity in the Ocean

Total alkalinity (TA) is one of the measurable parameters that characterize the oceanic carbonate system. A high temporal and spatial frequency in TA data can lead to better measurements, modeling, and understanding of the carbon cycle in aquatic systems, providing insights into problems from global climate change to ecosystem functioning. However, there are very few autonomous technologies for in situ TA measurements, and none with field demonstrations below 2 m depth. To meet this need in marine observing capabilities, we present a submersible sensor for autonomous in situ TA measurements to full ocean depths. This sensor uses lab-on-a-chip technology to sample seawater and perform single-point open-cell titration with an optical measurement. It can carry multiple calibration materials on board, allowing for routine recalibration and quality checks in the field. The sensor was characterized in the laboratory and in a pressure testing facility to 600 bar (equivalent to 6 km depth) and deployed in a shallow estuary, on a lander at 120 m depth, and on an autonomous underwater vehicle. With a demonstrated precision and accuracy regularly better than 5 μmol kg-1 in field deployments, this sensor has the potential to dramatically expand our ability to perform long-term autonomous measurements of the marine carbonate system.

Microfluidics for macrofluidics: addressing marine-ecosystem challenges in an era of climate change

Climate change presents a mounting challenge with profound impacts on ocean and marine ecosystems, leading to significant environmental, health, and economic consequences. Microfluidic technologies, with their unique capabilities, play a crucial role in understanding and addressing the marine aspects of the climate crisis. These technologies leverage quantitative, precise, and miniaturized formats that enhance the capabilities of sensing, imaging, and molecular tools. Such advancements are critical for monitoring marine systems under the stress of climate change and elucidating their response mechanisms. This review explores microfluidic technologies employed both in laboratory settings for testing and in the field for monitoring purposes. We delve into the application of miniaturized tools in evaluating ocean-based solutions to climate change, thus offering fresh perspectives from the solution-oriented end of the spectrum. We further aim to synthesize recent developments in technology around critical questions concerning the ocean environment and marine ecosystems, while discussing the potential for future innovations in microfluidic technology. The purpose of this review is to enhance understanding of current capabilities and assist researchers interested in mitigating the effects of climate change to identify new avenues for tackling the pressing issues posed by climate change in marine ecosystems.

Automation and Computerization of (Bio)sensing Systems

Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

Simple microfluidic devices for in situ detection of water contamination: a state-of-art review

Water security is an important global issue that is pivotal in the pursuit of sustainable resources for future generations. It is a multifaceted concept that combines water availability with the quality of the water's chemical, biological, and physical characteristics to ensure its suitability and safety. Water quality is a focal aspect of water security. Quality index data are determined and provided via laboratory testing using expensive instrumentation with high maintenance costs and expertise. Due to increased practices in this sector that can compromise water quality, innovative technologies such as microfluidics are necessary to accelerate the timeline of test procedures. Microfluidic technology demonstrates sophisticated functionality in various applications due to the chip's miniaturization system that can control the movement of fluids in tiny amounts and be used for onsite testing when integrated with smart applications. This review aims to highlight the basics of microfluidic technology starting from the component system to the properties of the chip's fabricated materials. The published research on developing microfluidic sensor devices for monitoring chemical and biological contaminants in water is summarized to understand the obstacles and challenges and explore future opportunities for advancement in water quality monitoring.

Variability of total alkalinity in coastal surface waters determined using an in-situ analyzer in conjunction with the application of a neural network-based prediction model

Total alkalinity (TA) is an important variable of the ocean carbonate system. In coastal oceans, carbonate system dynamics are controlled by a range of processes including photosynthesis and respiration, calcification, mixing of water masses, continental inputs, temperature changes, and seasonal upwelling. Assessments of diel, seasonal and interannual variations in TA are required to understand the carbon cycle in coastal oceans. However, our understanding of these variations remains underdeveloped due to limitations in observational techniques. Autonomous TA measurements are therefore required. In this study, an in situ TA analyzer (ISA-TA) based on a single-point titration with spectrophotometric pH detection was deployed in Tong'an Bay, Xiamen, China, over a five-month period in 2021 to determine diel and seasonal TA variations. The TA observations were combined with an artificial neural network (ANN) model to construct TA prediction models for this area. This provided a simple method to investigate TA variations in this region and was applied to predict surface water TA between March and April 2021. The in situ TA observations showed that TA values in Tong'an Bay varied within a range from 1931 to 2294 μmol kg-1 over the study period, with low TA in late winter, early summer and late summer, and high TA in early winter. The TA variations in late summer and early winter were mainly controlled by mixing of water bodies. The diel variations of TA were greatly determined by tides, with a diel amplitude of 9 to 247 μmol kg-1. The ANN model used temperature, salinity, chlorophyll, and dissolved oxygen to estimate TA, with a root-mean-square error (RMSE) of ∼14 μmol kg-1, with salinity as the input variable with the greatest weight. The approach of combining ISA-TA observations with an ANN model can be extended to study the carbonate system in other coastal regions.

Leaching Behavior of As and Pb in Lead-Zinc Mining Waste Rock under Mine Drainage and Rainwater

At present, the pollution of arsenic (As) and lead (Pb) is becoming increasingly serious. The pollution caused by the release of As and Pb from lead-zinc mines has seriously affected the water and soil environment and threatened human health. It is necessary to reveal the release characteristics of As and Pb. The actual scene of mine drainage (MD) and rainwater (RW) leaching waste rocks is the one of the main reasons for the release of As and Pb. However, the leaching behavior of As and Pb in these waste rocks under MD and RW suffered from a lack of in-depth research. In this study, we investigated the occurrence of As and Pb in waste rocks (S1-S6) by using X-ray diffraction (XRD) and time-of-flight secondary ion mass spectrometry (TOF-SIMS), and then, the changes in As and Pb concentration and the hydrochemical parameter in leaching solution were systematically studied. Furthermore, the correlation between the release of As and Pb and mineral composition was also evaluated. Results showed that these waste rocks were mainly composed of carbonate and sulfide minerals. As and Pb were mainly bounded or associated with sulfide minerals such as arsenopyrite, pyrite, chalcopyrite, and galena in these waste rocks, and small parts of As and Pb were absorbed or encased by clay minerals such as kaolinite and chlorite. Under MD and RW leaching, the pH, redox potential (Eh), and electric conductivity (EC) of each waste rock tended to be consistent due to their buffering ability; the leachate pH of waste rocks with more carbonate minerals was higher than that of sulfide minerals. Both As and Pb were released most under MD leaching in comparison to RW, reaching 6.57 and 60.32 mg/kg, respectively, due to MD's low pH and high Eh value. However, As in waste rock released more under alkaline conditions because part of the arsenic was in the form of arsenate. As and Pb release were mainly positively correlated with the proportions of sulfide minerals in these waste rocks. MD leaching significantly promoted the release of As and Pb from waste rocks, which would cause a great threat to the surrounding environment, and control measures were imperative. This paper not only reveals the As and Pb pollution mechanism around the lead-zinc mining area but also provides a theoretical basis for the prevention and control of As and Pb pollution in the future.

In Situ Drift Monitoring and Calibration of Field-Deployed Potentiometric Sensors Using Temperature Supervision

Potentiometric ion-selective electrodes (ISEs) have broad applications in personalized healthcare, smart agriculture, oil/gas exploration, and environmental monitoring. However, high-precision potentiometric sensing is difficult with field-deployed sensors due to time-dependent voltage drift and the need for frequent calibration. In the laboratory setting, these issues are resolved by repeated calibration by measuring the voltage response at multiple standard solutions at a constant temperature. For field-deployed sensors, it is difficult to frequently interrupt operation and recalibrate with standard solutions. Moreover, the constant surrounding temperature constraint imposed by the traditional calibration process makes it unsuitable for temperature-varying field use. To address the challenges of traditional calibration for field-deployed sensors, in this study, we propose a novel in situ calibration approach in which we use natural/external temperature variation in the field to obtain the time-varying calibration parameters, without having to relocate the sensors or use any complex system. We also develop a temperature-supervised monitoring method to detect the drift of the sensor during operation. Collectively, the temperature-based drift monitoring and in situ calibration methods allow us to monitor the drift of sensors and correct them periodically to achieve high-precision sensing. We demonstrate our approach in three testbeds: (1) under controlled temperature variation in the lab, (2) under natural temperature variation in a greenhouse, and (3) in the field to monitor nitrate activity of an agricultural site. In the laboratory study, we validate that the calibration parameters of printed nitrate ISEs can be reproduced by our proposed calibration process; therefore, it can serve as an alternative to traditional calibration processes. In the greenhouse, we show the use of natural temperature variation to calibrate the sensors and detect the drift in a fixed concentration nitrate solution. Finally, we demonstrate the use of the method to monitor the nitrate activity of an agricultural field within 10% of laboratory-based measurements (i.e., a sensitivity of 0.03 mM) for a period of 22 days. The findings highlight the prospect of temperature-based calibration and drift monitoring for high-precision sensing with field-deployed ISEs.