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Hydrated sulfate deposits have been detected on Mars. A spaceflight instrument capable of detecting microfossils in these salt deposits is highly important for the search for ancient life on Mars. This study employed a range of analytical methods, including nondestructive optical microscopy and SEM-EDX, as well as spatially resolved laser ablation mass spectrometry (LIMS), the latter being designed for in-situ analyses on planetary surfaces, to comprehensively examine the morphology, texture, mineralogy, and geochemistry of fossil-bearing gypsum deposits from Algeria. These extensive gypsum formations formed during the Messinian Salinity Crisis (MSC) and serve as excellent astrobiological analogs for the large-scale hydrated sulfate deposits detected on Mars. Significant research on Messinian gypsum reveals notable microbial fossil filaments. This study aims to determine whether optical microscopy and LIMS measurements together can detect fossil filaments in the gypsum samples, identify their composition, and decipher their biogenicity and syngeneity. Spatially resolved depth profiling and chemical mapping analysis of one representative fossil filament using LIMS provided detailed mineralogical and compositional variations that correlate with distinctive morphological features. These findings collectively indicate that the fossil filament exhibits distinct composition and diagenetic processes in comparison to the surrounding gypsum host. The microfossil’s syngeneity and biogenicity were established based on the presence of morphological biosignatures, biologically relevant elements, and biologically induced or influenced minerals such as dolomite and clay minerals. The formation of these minerals within the physico-chemical context of ancient Martian lakes was also discussed. The same suite of measurements and techniques could be applied to study microfossil-bearing gypsum formations on Mars and beyond.

We present a sensitive and compact quantum cascade laser-based photoacoustic greenhouse gas sensor for the detection of CO2, CH4 and CO and discuss its applicability toward on-line real-time trace greenhouse gas analysis. Differential photoacoustic resonators with different dimensions were used and optimized to balance sensitivity with signal saturation. The effects of ambient parameters, gas flow rate, pressure and humidity on the photoacoustic signal and the spectral cross-interference were investigated. Thanks to the combined operation of in-house designed laser control and lock-in amplifier, the gas detection sensitivities achieved were 5.6 ppb for CH4, 0.8 ppb for CO and 17.2 ppb for CO2, signal averaging time 1 s and an excellent dynamic range beyond 6 orders of magnitude. A continuous outdoor five-day test was performed in an observation station in China’s Qinling National Botanical Garden (E longitude 108°29’, N latitude 33°43’) which demonstrated the stability and reliability of the greenhouse gas sensor.

ABSTRACTWearable sweat sensors are gaining significant attention due to their unparalleled potential for noninvasive health monitoring. Sweat, as a kind of body fluid, contains informative physiological indicators that are related to personalized health status. Advances in wearable sweat sampling and routing technologies, flexible, and stretchable materials, and wireless digital technologies have led to the development of integrated sweat sensors that are comfortable, flexible, light, and intelligent. Herein, we report a flexible and integrated wearable device via incorporating a microfluidic system and a sensing chip with skin-integrated electronic format toward in-situ monitoring of uric acid (UA) in sweat that associates with gout, cardiovascular, and renal diseases. The microfluidic system validly realizes the real-time capture perspiration from human skin. The obtained detection range is 5–200 μM and the detection limit is 1.79 μM, which offers an importance diagnostic method for clinical relevant lab test. The soft and flexible features of the constructed device allows it to be mounted onto nearly anywhere on the body. We tested the sweat UA in diverse subjects and various body locations during exercise, and similar trends were also observed by using a commercial UA assay kit.

In recent years, large numbers of jellyfish have congregated in marine areas, leading to a decline in other plankton and fisheries. Jellyfish themselves have a certain toxicity and aggression, which have a serious impact on the safety of human life. In order to detect the quantity and distribution of underwater jellyfish, and to be more proactive in the prevention and control of Aurelia outbreaks, this study proposed a method for in-situ detection of underwater jellyfish based on the improved Faster R-CNN network model. Firstly, the real data sets of three species of jellyfish in the Qinhuangdao sea area were established by using underwater high-definition camera. The Multi Scale Retinex with Colour Restoration (MSRCR) algorithm was used to improve the brightness and contrast of the underwater images. Secondly, the residual network Resnet50 was integrated into the backbone network for better feature extraction; then the semi-precision floating-point number FP16 was added to improve the training speed. Finally, comparative experiments were conducted to verify the improved network. The F1 value, the P-R curve, the Loss curve and the AP value of the three detection models were evaluated and compared. The experimental results showed that compared to Vgg16 network and YOLO V3 network, the training speed was improved from 1.85bit/s to 7.35bit/s, and the accuracy was also improved to over 0.98. The experimental results were good, and the research results provided a more accurate and faster method for the in-situ detection of underwater jellyfish.

Carbendazim (CBZ) residues in food are a severe threat to food safety, and their detection is a challenging problem in food science. We introduce here a new method based on laser desorption postionization mass spectrometry imaging (LDPI-MSI) for detecting CBZ residues in carrots. In the novel LDPI-MSI method, two distinct laser beams simultaneously exert dissociation and ionization, which offers several advantages over traditional techniques based on single-photon matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), including simplified sample preparation, streamlined operation workflow, and a lower limit of detection (LOD). The LOD, in the proposed method, has been lowered to 0.019 ppm. Coupled with mass spectrometry imaging (MSI), the LDPI-MS method enabled in situ detection of small molecular compounds, such as chemical pesticides, and provided comprehensive and accurate results. The image obtained from the characteristic mass spectrometric signature of CBZ at m/z 191 illustrated that most of the CBZ could not enter the carrot tubers directly, but a small amount of CBZ entered the carrot root and was mainly concentrated in the central xylem. The results suggest that the proposed method could potentially be used in pesticide analysis.

Dissolved gases in the aquatic environment are critical to understanding the population of aquatic organisms and the ocean. Currently, laser absorption techniques based on membrane separation technology have made great strides in dissolved gas detection. However, the prolonged water–gas separation time of permeable membranes remains a key obstacle to the efficiency of dissolved gas analysis. To mitigate these limitations, we demonstrated direct measurement of dissolved gas using the evanescent-wave absorption spectroscopy of a tapered silica micro-fiber. It enhanced the analysis efficiency of dissolved gases without water–gas separation or sample preparation. The feasibility of this sensor for direct measurement of dissolved gases was verified by taking the detection of dissolved ammonia as an example. With a sensing length of 5 mm and a consumption of ~50 µL, this sensor achieves a system response time of ~11 min and a minimum detection limit (MDL) of 0.015%. Possible strategies are discussed for further performance improvement in in-situ applications requiring fast and highly sensitive dissolved gas sensing.

A flexible Surface-Enhanced Raman Spectroscopy (SERS) substrate based on silver nanoparticles encapsulated in an agar gel has been probed to detect the fungicide thiabendazole (TBZ) reaching a limit of detection (LOD) of 30 ng/cm2. In addition, a simple and sensitive strategy was employed for in-situ detection of TBZ on fruit and vegetable peels. For that purpose, peels of different fruits and vegetables were intentionally contaminated with different amount of TBZ, and the analyte was subsequently extracted within few seconds by gently rubbing the surface with the SERS substrate. The lowest value of TBZ detected on eggplant and green pepper peels was 50 ng/cm2. The values achieved for apple and pear peels were 0.20 μg/cm2 and 40 ng/cm2, respectively. On the other hand, for tomato and strawberry peels the lowest value achieved was 0.50 μg/cm2. The variation in sensitivity can be attributed to differences in the surface properties of the different peels. The above results show that this flexible SERS substrate can be further employed for the detection of contaminants in practical applications for food safety inspection.

At present, many studies have come to the conclusion that the coal seam contains primary CO gas, but the possibility of CO being adsorbed by coal after CO generated in drilling construction is not considered. In order to explore whether there is primary CO in spontaneous combustion coal seam in Northwest China, the original coal seam in-situ drilling detection method is used to detect primary CO. Three test boreholes are arranged in a row along the roadway side in the solid coal area not affected by mining. After the boreholes are sealed, high-purity N2 is used to replace the gas in the closed gas chamber, and the gas in the boreholes is extracted by a special air pump, so as to eliminate the impact of CO generated by coal oxidation on the test results during the construction of in-situ detection boreholes. On the basis of analyzing the source possibility of primary CO in coal seam and its emission theory, the variation characteristics of gas concentration in closed borehole with time are discussed. The results show that volume fraction of O2 and CO in the sealed borehole decrease rapidly with the extension of sealing time, and the volume fraction of O2 is stable below 2% after 12 days. After 12 days, the CO volume fraction is lower than 10−12, and no CO gas is detected by gas chromatograp. The gas in the borehole is mainly N2. It is concluded that there is no primary CO gas in the tested coal seam. The results of coal breaking test in N2 environment and coal sample oxidation test at normal temperature and constant temperature show that CO gas detected at the initial stage of borehole sealing comes from coal breaking operation in drilling construction.

In this paper, a new image analysis method based on an in-situ microscopic imaging system is proposed for detecting micro crystals in cooling crystallization. Due to the limitation of measurement technology, it is a challenge to extract the evolutionary information of micro crystals, which are too small to be precisely analyzed by in-situ images, e.g. crystals at the initial crystallization stage. An improved deep-learning model is used to enhance the image resolution of micro crystals, thus more effectively obtaining the crystal shape and size information. In addition, a valid size calibration method by simulating particle motion is proposed. Consequently, image size measurement can be easily performed for crystals by using an axis-based algorithm. Experimental verifications on β-form L-glutamic acid crystallization were performed to demonstrate the effectiveness of the proposed method for detecting micro crystal information.

Reverse osmosis (RO) is a widely used membrane technology for producing process water or tap water that is receiving increased attention due to water scarcity caused by climate change. A significant challenge in any membrane filtration is the presence of deposits on the membrane surfaces, which negatively affect filtration performance. Biofouling, the formation of biological deposits, poses a significant challenge in RO processes. Early detection and removal of biofouling are essential for effective sanitation and prevention of biological growth in RO-spiral wound modules. This study introduces two methods for the early detection of biofouling, capable of identifying initial stages of biological growth and biofouling in the spacer-filled feed channel. One method utilizes polymer optical fibre sensors that can be easily integrated into standard spiral wound modules. Additionally, image analysis was used to monitor and analyze biofouling in laboratory experiments, providing a complementary approach. To validate the effectiveness of the developed sensing approaches, accelerated biofouling experiments were conducted using a membrane flat module, and the results were compared with common online and offline detection methods. The reported approaches enable the detection of biofouling before known online parameters become indicative, effectively providing an online detection with sensitivities otherwise only achieved through offline characterization methods.

The Meridian Project’s sounding rocket mission uses a mass spectrometer to conduct in-situ atmospheric detection. In order to assess the influence of surface material outgassing and the attitude control jet on the spectrometer’s detection, a sounding rocket platform was modeled and simulated. Using the physical field simulation software COMSOL and the Monte Carlo method, this study investigated whether the gas molecules from the two cases could enter the in-situ atmospheric mass spectrometer’s sensor sampling port after colliding with the background atmosphere. The simulation results show that the influence of surface material outgassing on the in-situ atmospheric detection is very small, even under the conditions of medium solar activity and medium geomagnetic activity, while the influence of the attitude control jet on the in-situ atmospheric detection is large but can be reduced by reducing the low-altitude attitude control operation and decreasing the transmission probability. Through simulation optimization and according to engineering needs, increasing the nozzle outlet cross-sectional area, increasing the temperature of the gas used for attitude control, increasing the nozzle rotation angle, increasing the nozzle outlet angle, or increasing the nozzle center height can reduce the transmission probability. This model can simulate and analyze the influence of both surface material outgassing and attitude control jets on in-situ atmospheric detection, optimize relevant parameters, and provide new ideas for relevant work.

Microplastics (MPs) have become the widespread contaminants, which raises concerns on their ecological hazards. In-situ detection of MP in water bodies is essential for clear assessment of the ecological risks of MPs. The present study proposes a method based on polarized light scattering which measures the polarization parameters of the scattered light at 120° to detect MP in water. This method takes the advantage of in-situ measurement of the individual particles and the experimental setup in principle is used. By use of the measured polarization parameters equipped by machine learning, the standard polystyrene (PS) spheres, natural water sample, and lab-cultured microalgae are explicitly discriminated, and MP with different physical and chemical properties can be differentiated. It can also characterize the weathering of different MP and identify the specific type from multiple types of MP. This study explores the capability of the proposed method to detect the physical and chemical properties, weathering state and concentration of MP in water which promises the future application in water quality sensing and monitoring.

Most in situ tool wear monitoring methods during micro end milling rely on signals captured from the machining process to evaluate tool wear behavior; accurate positioning in the tool wear region and direct measurement of the level of wear are difficult to achieve. In this paper, an in situ monitoring system based on machine vision is designed and established to monitor tool wear behavior in micro end milling of titanium alloy Ti6Al4V. Meanwhile, types of tool wear zones during micro end milling are discussed and analyzed to obtain indicators for evaluating wear behavior. Aiming to measure such indicators, this study proposes image processing algorithms. Furthermore, the accuracy and reliability of these algorithms are verified by processing the template image of tool wear gathered during the experiment. Finally, a micro end milling experiment is performed with the verified micro end milling tool and the main wear type of the tool is understood via in-situ tool wear detection. Analyzing the measurement results of evaluation indicators of wear behavior shows the relationship between the level of wear and varying cutting time; it also gives the main influencing reasons that cause the change in each wear evaluation indicator.

Recently, novel fluorescent probes based on biomaterials and luminescent nanomaterials for metal ions attract tremendous attentions, owing to their advantages of simple operation, high sensitivity and rapid response for metals detection. Immobilized on the optical fiber sensor, fluorescent probes reveal the advantages while facing outdoor detection challenges. Therefore, numerous fluorescent optical fiber sensors for metal ions have been developed for online and in-situ detection to predict and prevent the environmental problems. Differ from refractometer-based fiber sensors, the structures of the fiber sensors based on fluorescent materials are usually simple, and the characters of the materials and the fabrication processes of fiber sensors are more significant to the sensing performances. This paper summarized the studies of optical fiber sensors for metal detection based on novel fluorescent materials to help researchers get the highlights of recent notable advancements and obtain the better potential prospects.

In recent years, the investigation and exploitation of hydrothermal region and polymetallic mineral areas has become a hot topic. The emergence of underwater vehicle platforms has made it possible for new chemical sensors to be applied in marine in-situ detection. Laser-induced breakdown spectroscopy (LIBS), with its advantages of rapid real-time analysis, sampling without pretreatment, simultaneous multi-element detection and stand-off detection, has great potential in marine applications. In this paper, a newly more compact and lighter underwater LIBS system based on the LIBSea system named LIBSea II was developed and tested both in the laboratory and sea trials. The system consists of a Nd:YAG single-pulse laser at 1064 nm, a fiber spectrometer, optical layout, a power supply module and an internal environment sensor. The system is encapsulated in a pressure vessel (Φ 190 mm × L 588 mm) with an optical window on the end cap. Experimental parameters of the system including laser energy and delay time were firstly optimized in the laboratory. Then, field test of the system in nearshore was performed with various samples, including pure metal and alloy samples as well as a manganese nodule sample from deep sea, to verify the detection performance of the LIBSea II system. In 2019, the system was deployed on a remotely operated vehicle (ROV) of Haima for deep sea trial, and atomic lines of K, Na, Ca and strong molecular bands of CaOH from a carbonate rock sample were obtained for the first time at depths of 1400 m. These results show that the LIBSea II system has great potential to be used in deep-sea geological exploration.