RSS 1.0Sensors Lab
For more information visit: https://cemse.kaust.edu.sa/sensors
Recent Submissions
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Polyoxometalate-cyclodextrin supramolecular entities for real-time in situ monitoring of dopamine released from neuroblastoma cells(Biosensors & bioelectronics, Elsevier BV, 2023-03-23) [Article]Optimized and sensitive biomarker detection has recently been shown to have a critical impact on quality of diagnosis and medical care options. In this research study, polyoxometalate-γ-cyclodextrin metal-organic framework (POM-γCD MOF) was utilized as an electrocatalyst to fabricate highly selective sensors to detect in-situ released dopamine. The POM-γCD MOF produced multiple modes of signals for dopamine including electrochemical, colorimetric, and smartphone read-outs. Real-time quantitative monitoring of SH-SY5Y neuroblastoma cellular dopamine production was successfully demonstrated under various stimuli at different time intervals. The POM-CD MOF sensor and linear regression model were used to develop a smartphone read-out platform, which converts dopamine visual signals to digital signals within a few seconds. Ultimately, POM-γCD MOFs can play a significant role in the diagnosis and treatment of various diseases that involve dopamine as a significant biomarker.
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Supervised Local Training with Backward Links for Deep Neural Networks(IEEE Transactions on Artificial Intelligence, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-02) [Article]The restricted training pattern in the standard BP requires end-to-end error propagation, causing large memory costs and prohibiting model parallelization. Existing local training methods aim to resolve the training obstacles by completely cutting off the backward path between modules and isolating their gradients. These methods prevent information exchange between modules and result in inferior performance. This work proposes a novel local training algorithm, BackLink, which introduces inter-module backward dependency and facilitates information to flow backward along with the network. To preserve the computational advantage of local training, BackLink restricts the error propagation length within the module. Extensive experiments performed in various deep convolutional neural networks demonstrate that our method consistently improves the classification performance of local training algorithms over other methods. For example, our method can surpass the conventional greedy local training method by 6.45% in accuracy in ResNet32 classifying CIFAR100 and recent work by 2.58% in ResNet110 classifying STL-10 with much lower complexity, respectively. Analysis of computational costs reveals that small overheads are incurred in GPU memory costs and runtime on multiple GPUs. Our method can lead up to a 79% reduction in memory cost and 52% in simulation runtime in ResNet110 compared to the standard BP. Therefore, our method could create new opportunities for improving training algorithms towards better efficiency for real-time learning applications.
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Iron Single-Atom Catalysts on MXenes for Ultrasensitive Monitoring of Adrenal Tumor Markers and Cellular Dopamine(Advanced Materials Technologies, Wiley, 2023-02-02) [Article]Neuroblastoma and pheochromocytoma are the most prevalent malignancies of the adrenal medulla. They are currently diagnosed by measuring urinary catecholamines using high-performance liquid chromatography-mass spectrometry, which is expensive, bulky, and tedious. Electrochemical detectors stand out as low-cost alternatives; however, further development of functional materials with adequate sensitivity is still required to attain clinically useful diagnostic devices. Here, Ti3C2Tx MXene nanosheets stabilized with iron single-atom catalysts (Fe-SACs), anchored on the surface, are synthesized and utilized as efficient electrocatalysts for the determination of catecholamine (dopamine (DA)) and its end-products (vanillylmandelic acid (VMA) and homovanillic acid (HVA)). The Fe-SACs/Ti3C2Tx exhibits low oxidation overpotentials with high signal amplifications up to 610%, 290%, and 420%, and sensitive detection limits of 1.0, 5.0, and 10 nM for DA, VMA, and HVA, respectively. The presence of the atomic Fe elements on the Ti3C2Tx nanosheets is confirmed using high-resolution scanning transmission electron microscopy and X-ray photoelectron spectroscopy. The Fe-SACs/Ti3C2Tx sensor tracks the in situ production of DA in PC12 cells and found practically useful in analyzing human urine samples. The Fe-SACs/Ti3C2Tx stands out as a sensitive diagnostic platform for evaluating the progression of tumors and the quality of cellular DA communications
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Institution of Metal–Organic Frameworks as a Highly Sensitive and Selective Layer In-Field Integrated Soil-Moisture Capacitive Sensor(ACS Applied Materials & Interfaces, American Chemical Society (ACS), 2023-01-20) [Article]The ongoing global industrialization along with the notable world population growth is projected to challenge the global environment as well as pose greater pressure on water and food needs. Foreseeably, an improved irrigation management system is essential and the quest for refined chemical sensors for soil-moisture monitoring is of tremendous importance. Nevertheless, the persisting challenge is to design and construct stable materials with the requisite sensitivity, selectivity, and high performance. Here, we report the introduction of porous metal–organic frameworks (MOFs), as the receptor layer, in capacitive sensors to efficiently sense moisture in two types of soil. Namely, our study unveiled that Cr-soc-MOF-1 offers the best sensitivity (≈24,000 pF) among the other tested MOFs for any given range of soil-moisture content, outperforming several well-known oxide materials. The corresponding increase in the sensitivities for tested MOFs at 500 Hz are ≈450, ≈200, and ≈30% for Cr-soc-MOF-1, Al-ABTC-soc-MOF, and Zr-fum-fcu-MOF, respectively. Markedly, Cr-soc-MOF-1, with its well-known water capacity, manifests an excellent sensitivity of ≈450% in clayey soil, and the analogous response time was 500 s. The noted unique sensing properties of Cr-soc-MOF-1 unveils the great potential of MOFs for soil-moisture sensing application.
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Effect of combining UV-C irradiation and vacuum sealing on the shelf life of fresh strawberries and tomatoes(Journal of Food Science, Wiley, 2023-01-09) [Article]This research presents the effect of combining UV-C irradiation and vacuum sealing on the shelf life of strawberries and quartered tomatoes and compares it with the effect of the sole use of UV-C irradiation or vacuum sealing. A constant UV-C dose of 360 J/m<sup>2</sup> was used for the samples' irradiation, and all the vacuum-sealed samples were stored at a reduced pressure of 40 kPa. Organoleptic analysis, microbial population quantification of yeast and mold, Pseudomonas sp., weight loss, and pH measurements were obtained to identify the spoilage occurrence, monitor the samples' quality, and quantify the shelf life. Sensory evaluation was conducted by 12 consumer panelists to evaluate the aroma, taste, color, texture, and the overall acceptance of the samples. The results revealed that the combination of UV-C irradiation and vacuum sealing prolongs the shelf life of perishables more than the sole use of UV-C irradiation or vacuum sealing. The achieved shelf-life increase using this combination was 124.41% and 54.41% for strawberries and quartered tomatoes, respectively, while acceptable sensory characteristics were maintained throughout the storage period. Hence, this food preservation method can be further improved and integrated in the daily life of modern consumers and the operations of fresh produce retailers, as it could effectively reduce the spoilage rates of fresh produce and help achieve the UN SDG 12.3, which aims to reduce food loss and waste by 50% by 2030 at the consumer and retail levels. PRACTICAL APPLICATION: The system can be further developed and introduced to the market as a kitchen appliance for households or as a predistribution step for fresh produce distribution centers. The shelf-life extension capability of this system, which does not involve any use of chemical substances, would make it an attractive solution for households and food retailers.
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Synergistic multi-source ambient RF and thermal energy harvester for green IoT applications(Energy Reports, Elsevier BV, 2023-01-09) [Article]In a future green Internet of Things (IoT) reality, billions of devices of the IoT infrastructure should be self-powered. Harvesting ambient energy to power IoT devices is an attractive solution that can extend battery life or can completely replace batteries. Considering the global applications of IoT, ubiquitous and continuous availability is an important requirement for ambient energy sources. Radio frequency (RF) energy from mobile phone towers and thermal energy from diurnal cycle temperature fluctuations are good candidates. In this study, we present a synergistic multi-source energy harvester (MSEH) comprising an RF energy harvester (RFEH) and a thermal energy harvester (TEH) integrated through a dual-function component, heatsink antenna. Both harvesters collect ambient energy 24 h a day and are not location specific. The TEH, which is in the shape of a box, collects energy using heatsinks on its sidewalls. The same heatsinks are optimized to also serve as receiving antennas of the RFEH, which collects energy from the GSM900, GSM1800, and 3G bands. Due to the synergistic integration, radiation efficiency of the antenna doubled from 40% to 80% which resulted in ∼10% increase in power conversion efficiency of the RFEH. Similarly, the average power of the TEH without heatsinks 120 μW is doubled to 240 μW for TEH with heatsinks. Field tests have shown that the outputs of the TEH and RFEH have increased 4 and 3 times compared to the independent TEH and RFEH respectively. A temperature and humidity sensor based IoT node has been successfully powered through this energy harvesting system. Overall, the MSEH can collect 3680 μWh of energy per day which is sufficient to obtain the sensors data with a time interval of 3.5 s.
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Live Demonstration: KAUSTat — A Compact Reconfigurable Electrochemical Station(IEEE, 2022-12-08) [Conference Paper]This live demonstration presents a novel compact reconfigurable electrochemical station that can be used with different types of screen-printed electrodes (SPE) and laser-scribed graphene-based (LSG) sensors. The device presented here is named as KAUSTat. The proposed system includes rich circuit architecture that allows the reconfiguration of its output pins to be used for different purposes. The device can be used to read electrochemical sensors by applying voltammetry and amperometry techniques, and it also can be used to modify the surface of SPEs and LSGs.
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Impact of layer thickness on the operating characteristics of In2O3/ZnO heterojunction thin-film transistors featured(Applied Physics Letters, AIP Publishing, 2022-12-05) [Article]Combining low-dimensional layers of dissimilar metal oxide materials to form a heterojunction structure offers a potent strategy to improve the performance and stability of thin-film transistors (TFTs). Here, we study the impact of channel layer thicknesses on the operating characteristics of In2O3/ZnO heterojunction TFTs prepared via sputtering. The conduction band offset present at the In2O3/ZnO heterointerface affects the device's operating characteristics, as is the thickness of the individual oxide layers. The latter is investigated using a variety of experimental and computational modeling techniques. An average field-effect mobility (μFE) of >50 cm2 V−1 s−1, accompanied by a low threshold voltage and a high on/off ratio (∼108), is achieved using an optimal channel configuration. The high μFE in these TFTs is found to correlate with the presence of a quasi-two-dimensional electron gas at the In2O3/ZnO interface. This work provides important insight into the operating principles of heterojunction metal oxide TFTs, which can aid further developments.
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Experimental Identification of the Second-Order Non-Hermitian Skin Effect with Physics-Graph-Informed Machine Learning.(Advanced science (Weinheim, Baden-Wurttemberg, Germany), Wiley, 2022-11-13) [Article]Topological phases of matter are conventionally characterized by the bulk-boundary correspondence in Hermitian systems. The topological invariant of the bulk in d dimensions corresponds to the number of (d - 1)-dimensional boundary states. By extension, higher-order topological insulators reveal a bulk-edge-corner correspondence, such that nth order topological phases feature (d - n)-dimensional boundary states. The advent of non-Hermitian topological systems sheds new light on the emergence of the non-Hermitian skin effect (NHSE) with an extensive number of boundary modes under open boundary conditions. Still, the higher-order NHSE remains largely unexplored, particularly in the experiment. An unsupervised approach-physics-graph-informed machine learning (PGIML)-to enhance the data mining ability of machine learning with limited domain knowledge is introduced. Through PGIML, the second-order NHSE in a 2D non-Hermitian topoelectrical circuit is experimentally demonstrated. The admittance spectra of the circuit exhibit an extensive number of corner skin modes and extreme sensitivity of the spectral flow to the boundary conditions. The violation of the conventional bulk-boundary correspondence in the second-order NHSE implies that modification of the topological band theory is inevitable in higher dimensional non-Hermitian systems.
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A Compact Reconfigurable Resonator-Based Direct Current Sensing System(Journal of Microelectromechanical Systems, Institute of Electrical and Electronics Engineers (IEEE), 2022-11-07) [Article]A compact and reconfigurable current readout system is presented that is based on microelectromechanical system (MEMS) resonators. The proposed system generates analog and digital outputs by electrothermally tuning the microbeam resonant frequency according to variations in the input current signal. A single resonator is utilized to generate the analog output, while a resonator array operating at different frequencies is utilized to generate a digital one-hot output. Experiments showed that the frequency shift is linearly proportional to the square of the current. The single resonator has a detection limit of 1.16 μ A, and the resonator array offers good static linearity with a maximum differential/integral non-linearity of 0.55/0.23 least significant bits. The single resonator is suitable for applications requiring high-resolution measurements. The proposed resonator sensing system has a small footprint, is compatible with large-scale integration, and provides considerable flexibility for reconfiguration.
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Architectural Trade-Off Analysis for Accelerating LSTM Network Using Radix- r OBC Scheme(IEEE Transactions on Circuits and Systems I: Regular Papers, Institute of Electrical and Electronics Engineers (IEEE), 2022-11-03) [Article]This paper presents architectural trade-off analysis for accelerating two (Type I, II) fixed-point long short-term memory (LSTM) network based on circulant matrix-vector multiplications (MVMs) using radix- r offset binary coding (OBC) scheme. Type I MVM architecture rotates the weights with the proposed modulo-cum interleaver and uses partial product generators (PPGs) with a single generation unit across a column. It is hardware-optimized using a single adder tree through time-multiplexing. Meanwhile, Type II MVM architecture rotates the inputs with the proposed store-cum interleaver and uses single PPGs with a single generation unit across a row. It is time-optimized by unfolding shift-accumulate unit to a shift-add tree followed by pipelining. A new design for element-wise multiplication using radix- r PPG is also presented. Both the designs are extended to their block-circulant variants for certain accuracy requirements. Post-synthesis of Type I and II architectures for a different model, kernel, radix sizes and clock frequencies result in several efficient designs. Compared with the prior scheme, Type I architecture for 128×128 with r=2 on 28 nm FDSOI technology at 800 MHz occupies 32.27% lesser area, consumes 67.89% lesser power at the same throughput, while Type II architecture at the expense of area and power provides 40× higher throughput.
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Metal–Organic Frameworks Meet Molecularly Imprinted Polymers: Insights and Prospects for Sensor Applications(ACS Applied Materials & Interfaces, American Chemical Society (ACS), 2022-10-31) [Article]The use of porous materials as the core for synthesizing molecularly imprinted polymers (MIPs) adds significant value to the resulting sensing system. This review covers in detail the current progress and achievements regarding the synergistic combination of MIPs and porous materials, namely metal/covalent–organic frameworks (MOFs/COFs), including the application of such frameworks in the development of upgraded sensor platforms. The different processes involved in the synthesis of MOF/COF-MIPs are outlined, along with their intrinsic properties. Special attention is paid to debriefing the impact of the morphological changes that occur through the synergistic combination compared to those that occur due to the individual entities. Thereafter, the strategies used for building the sensors, as well as the transduction modes, are overviewed and discussed. This is followed by a full description of research advances for various types of MOF/COF-MIP-based (bio)sensors and their applications in the fields of environmental monitoring, food safety, and pharmaceutical analysis. Finally, the challenges/drawbacks, as well as the prospects of this research field, are discussed in detail.
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Graphitic Carbon Nitride and IGZO Bio-FET for Rapid Diagnosis of Myocardial Infarction(Biosensors, MDPI AG, 2022-10-07) [Article]Acute myocardial infarction (AMI), commonly known as a heart attack, is a life-threatening condition that causes millions of deaths every year. In this study, a transistor-based biosensor is developed for rapid and sensitive detection of cardiac troponin-I (cTnI), a diagnostic biomarker of AMI. A biosensing technique based on a field effect transistor (FET), which uses indium gallium zinc oxide (IGZO) as an excellent semiconducting channel, is integrated with nanosheet materials to detect cTnI. Porous carbon nitride (PCN) decorated with gold nanoparticles (Au NPs) is used as a bridge between the solid-state device and the biorecognition element. We demonstrate that this biosensor is highly sensitive and has an experimental limit of detection of 0.0066 ng/mL and a dynamic range of 0.01 ng/mL–1000 ng/mL. This is the first report of a semiconducting metal oxide FET cardiac biomarker sensor combined with PCN for the detection of cTnI. The reported compact microsystem paves the way for rapid and inexpensive detection of cardiac biomarkers.
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Efficient Neuromorphic Hardware Through Spiking Temporal Online Local Learning(IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Institute of Electrical and Electronics Engineers (IEEE), 2022-09-30) [Article]Local learning schemes have shown promising performance in spiking neural networks (SNNs) training and are considered a step toward more biologically plausible learning. Despite many efforts to design high-performance neuromorphic systems, a fast and efficient on-chip training algorithm is still missing, which limits the deployment of neuromorphic systems in many real-time applications. This work proposes a scalable, fast, and efficient spiking neuromorphic hardware system with on-chip local learning capability. We introduce an effective hardware-friendly local training algorithm compatible with sparse temporal input coding and binary random classification weights. The algorithm is demonstrated to deliver competitive accuracy in different tasks. The proposed digital system explores spike sparsity in communication, parallelism in vector–matrix operations and process-level dataflow, and locality of training errors, which leads to low cost and fast training speed. The system is optimized under various performance metrics. Taking into consideration energy, speed, resources, and accuracy, the proposed method shows around 10 × efficiency over a recent work with a direct feedback alignment (DFA) method and 4.5 × efficiency over the spike-timing-dependent plasticity (STDP) method. Moreover, our hardware architecture can easily scale up with the network size at a linear rate. Thus, our method has demonstrated great potential for use in various applications, especially those demanding low latency.
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Ruthenium and Nickel Molybdate-Decorated 2D Porous Graphitic Carbon Nitrides for Highly Sensitive Cardiac Troponin Biosensor(Biosensors, MDPI AG, 2022-09-22) [Article]Two-dimensional (2D) layered materials functionalized with monometallic or bimetallic dopants are excellent materials to fabricate clinically useful biosensors. Herein, we report the synthesis of ruthenium nanoparticles (RuNPs) and nickel molybdate nanorods (NiMoO4 NRs) functionalized porous graphitic carbon nitrides (PCN) for the fabrication of sensitive and selective biosensors for cardiac troponin I (cTn-I). A wet chemical synthesis route was designed to synthesize PCN-RuNPs and PCN-NiMoO4 NRs. Morphological, elemental, spectroscopic, and electrochemical investigations confirmed the successful formation of these materials. PCN-RuNPs and PCN-NiMoO4 NRs interfaces showed significantly enhanced electrochemically active surface areas, abundant sites for immobilizing bioreceptors, porosity, and excellent aptamer capturing capacity. Both PCN-RuNPs and PCN-NiMoO4 NRs materials were used to develop cTn-I sensitive biosensors, which showed a working range of 0.1–10,000 ng/mL and LODs of 70.0 pg/mL and 50.0 pg/mL, respectively. In addition, the biosensors were highly selective and practically applicable. The functionalized 2D PCN materials are thus potential candidates to develop biosensors for detecting acute myocardial infractions.
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Porous graphitic carbon nitrides integrated biosensor for sensitive detection of cardiac troponin I(Biosensors and Bioelectronics: X, Elsevier BV, 2022-09-12) [Article]Early diagnosis of cardiovascular diseases (CVDs) has the potential to save millions of lives each year. Sensitive quantitative measurement of blood cardiac troponin I (cTnI) is required for early diagnosis of CVDs. Porous graphitic carbon nitride (PCN) nanomaterials integrated biosensor that detects picogram/mL concentrations of cTnI is reported. PCN is an updated version of graphitic carbon nitride (GCN) with improved porosity and electronic structure. A rapid two-step chemical method was described to synthesize PCN and gold nanoparticles functionalized PCN (PCN-AuNPs). The modification of the electrode surface with PCN materials had a significant impact on the electrochemically active surface area (EASA), interfacial electron transport, aptamer immobilization, and biosensing performance. The use of PCN nanomaterial in cTnI aptasensing resulted in a 3.2-fold increase in signal amplification. PCN-AuNPs found practically applicable in human blood serum (cTnI-spiked). Furthermore, a low-cost and user-friendly sensing platform has been demonstrated by integrating a PCN-AuNPs aptasensor, a custom-made miniaturized potentiostat, and a smartphone, which provided rapid, sensitive point-of-care (PoC) analysis of cTnI. Highly sensitive detection limit (0.01 pg/mL), rapid analysis time (2 min), and small sample volume (20 μL) are the other advantages of this nano-biosensor.
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Efficient Hardware Implementation for Online Local Learning in Spiking Neural Networks(IEEE, 2022-09-05) [Conference Paper]Local learning schemes have shown promising performance in spiking neural networks and are considered as a step towards more biologically plausible learning. Despite many efforts to design high-performance neuromorphic systems, a fast and efficient neuromorphic hardware system is still missing. This work proposes a scalable, fast, and efficient spiking neuromorphic hardware system with on-chip local learning capability that can achieve competitive classification accuracy. We introduce an effective hardware-friendly local training algorithm that is compatible with sparse temporal input coding and binary random classification weights. The algorithm is demonstrated to deliver competitive accuracy. The proposed digital system explores spike sparsity in communication, parallelism in vector-matrix operations, and locality of training errors, which leads to low cost and fast training speed. Taking into consideration energy, speed, resource, and accuracy, our design shows 7.7× efficiency over a recent spiking direct feedback alignment method and 2.7× efficiency over the spike-timing-dependent plasticity method.
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Multiplexed sensing techniques for cardiovascular disease biomarkers - A review(Biosensors and Bioelectronics, Elsevier BV, 2022-09-03) [Article]Cardiovascular diseases (CVDs) are the number one cause of death worldwide, taking 17.9 million lives each year. The rapid, sensitive, and accurate determination of cardiac biomarkers is vital for the timely diagnosis of CVDs. For accurate diagnosis, dependence on a single biomarker is unreliable because each one has also been linked to other diseases. To overcome this problem, the multiplexed determination of two or more markers has emerged as a promising alternative to single-marker analysis. Over the last 5 years, research interest in the development of biosensors for targeting multiple cardiac markers has increased. In this study, we critically reviewed the various multiplexed biosensing approaches reported during the last 5 years, categorizing them by signal readouts. Prospective detection configurations, capture probes, electrode design strategies, electrode types, nanomaterials, reporter tags, and assay types were reviewed, tabulated, and critically discussed. Then, their advantages and limitations were highlighted. For each category, we provided our perspective as well as the overall critical discussion. Lastly, we summarized potential commercial multiplexed cardiac biosensors and commented on the challenges and future prospects for such sensors.
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Smartphone-Based Multiplexed Biosensing Tools for Health Monitoring(Biosensors, MDPI AG, 2022-07-29) [Article]Many emerging technologies have the potential to improve health care by providing more personalized approaches or early diagnostic methods. In this review, we cover smartphone-based multiplexed sensors as affordable and portable sensing platforms for point-of-care devices. Multiplexing has been gaining attention recently for clinical diagnosis considering certain diseases require analysis of complex biological networks instead of single-marker analysis. Smartphones offer tremendous possibilities for on-site detection analysis due to their portability, high accessibility, fast sample processing, and robust imaging capabilities. Straightforward digital analysis and convenient user interfaces support networked health care systems and individualized health monitoring. Detailed biomarker profiling provides fast and accurate analysis for disease diagnosis for limited sample volume collection. Here, multiplexed smartphone-based assays with optical and electrochemical components are covered. Possible wireless or wired communication actuators and portable and wearable sensing integration for various sensing applications are discussed. The crucial features and the weaknesses of these devices are critically evaluated.
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Minimally-invasive, real-time, non-destructive, species-independent phytohormone biosensor for precision farming(Biosensors and Bioelectronics, Elsevier BV, 2022-07-06) [Article]To keep up with population growth, precision farming technologies must be implemented to sustainably increase agricultural output. The impact of such technologies can be expanded by monitoring phytohormones, such as salicylic acid. In this study, we present a plant-wearable electrochemical sensor for in situ detection of salicylic acid. The sensor utilizes microneedle-based electrodes that are functionalized with a layer of salicylic acid selective magnetic molecularly imprinted polymers. The sensor's capability to detect the phytohormone is demonstrated both in vitro and in vivo with a limit of detection of 2.74 μM and a range of detection that can reach as high as 150 μM. Furthermore, the selectivity of the sensor is verified by testing the sensor on commonly occurring phytohormones. Finally, we demonstrate the capability of the sensor to detect the onset of fungal infestation in Tobacco 5 min post-inoculation. This work shows that the sensor could serve as a promising platform for continuous and non-destructive monitoring in the field and as a fundamental research tool when coupled with a portable potentiostat.
