Real-time, specific, and label-free transistor-based sensing of organophosphates in liquid.

Organophosphates (OP), commonly used in agriculture and as chemical warfare agents, pose significant environmental risks, necessitating real-time, low-cost OP detection methods. In particular, liquid-phase OP sensing with minimal sample volumes is crucial. While several methods allow rapid detection of low concentrations of OP vapors, they are effective only in the short term, while vapors are still being produced. Many OP compounds are semi-volatile, leading to the contamination of water, soil, and surfaces, posing a risk of secondary, long-term exposure. Detecting this contamination requires methods that can be directly applied to droplets of the affected medium. Currently, no method provides the desired combination of ultra-sensitivity, quantitative detection, rapid response, and low-cost for detecting OPs in liquid samples. This study aims to demonstrate quantitative, low-cost, real-time, specific, and label-free OP sensing in ultra-small samples using a transistor-based approach. The current work employs the 2-(4-Aminophenyl)-1,1,1,3,3,3-hexafluoro-2-propanol (aminophenyl-HFIP) functionalized meta-nano-channel field-effect chemical sensor (MNChem sensor) to monitor the organophosphate, diethyl cyanophosphonate (DCNP), in liquid samples. The silicon component of the MNChem is fabricated using a complementary metal-oxide semiconductor (CMOS) process, and the amine-based chemical functionalization of the sensing area is performed post-fabrication. The MNChem sensor provides electrostatic control over the source-drain current (IDS), allowing an optimized channel configuration that efficiently transduces localized OP recognition events into significant IDS variations. Sensing is performed using 0.5 µL buffer solution to simulate a miniature field-deployable sensor for on-site liquid analysis. We report the sensing of DCNP with a limit-of-detection of 100 fg/mL, a dynamic range of 9 orders of magnitude, and excellent linearity (≥0.97) and sensitivity. Control measurements confirm the specificity and reliability of the sensor's response, validating its applicability. This study introduces a novel method for OP detection in contaminated droplets using a low-cost disposable transistor technology.

Digital Fingerprinting of Complex Liquids Using a Reconfigurable Multi-Sensor System with Foundation Models.

Combining chemical sensor arrays with machine learning enables designing intelligent systems to perform complex sensing tasks and unveil properties that are not directly accessible through conventional analytical chemistry. However, personalized and portable sensor systems are typically unsuitable for the generation of extensive data sets, thereby limiting the ability to train large models in the chemical sensing realm. Foundation models have demonstrated unprecedented zero-shot learning capabilities on various data structures and modalities, in particular for language and vision. Transfer learning from such models is explored by providing a framework to create effective data representations for chemical sensors and ultimately describe a novel, generalizable approach for AI-assisted chemical sensing. The translation of signals produced by remarkably simple and portable multi-sensor systems into visual fingerprints of liquid samples under test is demonstrated, and it is illustrated that how a pipeline incorporating pretrained vision models yields > 95 % $>95\%$ average classification accuracy in four unrelated chemical sensing tasks with limited domain-specific training measurements. This approach matches or outperforms expert-curated sensor signal features, thereby providing a generalization of data processing for ultimate ease-of-use and broad applicability to enable interpretation of multi-signal outputs for generic sensing applications.

A disposable fiber-optic plasmonic sensor for chemical sensing.

The integration of fiber optics and plasmonic sensors is promising to improve the practical usability over conventional bulky sensors and systems. To achieve high sensitivity, it typically requires fabrication of well-defined plasmonic nanostructures on optical fibers, which greatly increases the cost and complexity of the sensors. Here, we present a fiber-optic sensor system by using chemical absorption of gold nanoparticles and a replaceable configuration. By functioning gold nanoparticles with aptamers or antibodies, we demonstrate the applications in chemical sensing using two different modes. Measuring shift in resonance wavelength enables the Pb2+ detection with a high linearity and a limit of detection of 0.097 nM, and measuring absorption peak amplitude enables the detection of E. coli in urinary tract infection with a dynamic range between 103 to 108 CFU/mL. The high sensitivity, simple fabrication and disposability of this sensing approach could pave the way for point-of-care testing with fiber-optic plasmonic sensors.

Two-Orders-of-Magnitude Enhancement of SERS Activity via a Simple Surface Engineering of Quasi-Metal Single-Crystal Frameworks.

Beyond noble metals and semiconductors, quasi-metals have recently been shown to be noteworthy substrates for surface enhanced Raman spectroscopy, and their excellent quasi-metal surface-enhanced Raman spectroscopy (SERS) sensing has demonstrated a wider range of application scenarios. However, the underlying mechanism behind the enhanced Raman activity is still unclear. Here, we demonstrate that surface hydroxyls play a crucial role in the enhancement of the SERS activity of quasi-metal nanostructures. As a demonstration material, quasi-metallic MoO2 single-crystal frameworks rich in surface hydroxyls have been shown to have 100 times higher SERS activity than MoO2 single-crystal frameworks without hydroxyl functionalization, with a Raman enhancement factor of up to 7.6 × 107. Experimental and first-principles density-functional theory calculation results show that the enhanced Raman activity can be attributed to an effective interfacial charge transfer within the MoO2/OH/molecule system.

Emission Library and Applications of 2,1,3-Benzothiadiazole and Its Derivative-Based Luminescent Metal-Organic Frameworks.

Organic linker-based luminescent metal-organic frameworks (LMOFs) have received extensive attention due to their promising applications in chemical sensing, energy transfer, solid-state-lighting and heterogeneous catalysis. Benefiting from the virtually unlimited emissive organic linkers and the intrinsic advantages of MOFs, significant progress has been made in constructing LMOFs with specific emission behaviors and outstanding performances. Among these reported organic linkers, 2,1,3-benzothiadiazole and its derivatives, as unique building units with tunable electron-withdrawing abilities, can be used to synthesize numerous emissive linkers with a donor-bridge-acceptor-bridge-donor type structure. These linkers were utilized to coordinate with different metal nodes, forming LMOFs with diverse underlying nets and optical properties. In this Minireview, 2,1,3-benzothiadiazole and its derivative-based organic linkers and their corresponding LMOFs are summarized with which an emission library is built between the linker structures and the emission behaviors of constructed LMOFs. In particular, the preparation of LMOFs with customized emission properties ranging from deep-blue to near-infrared and sizes from dozens to hundreds of nanometers is discussed in detail. The applications of these LMOFs, including chemical sensing, energy harvesting and transfer, and catalysis, are then highlighted. Key perspectives and challenges for the future development of LMOFs are also addressed.

Room-Temperature (RT) Extended Short-Wave Infrared (e-SWIR) Avalanche Photodiode (APD) with a 2.6 µm Cutoff Wavelength.

Highly sensitive infrared photodetectors are needed in numerous sensing and imaging applications. In this paper, we report on extended short-wave infrared (e-SWIR) avalanche photodiodes (APDs) capable of operating at room temperature (RT). To extend the detection wavelength, the e-SWIR APD utilizes a higher indium (In) composition, specifically In0.3Ga0.7As0.25Sb0.75/GaSb heterostructures. The detection cut-off wavelength is successfully extended to 2.6 µm at RT, as verified by the Fourier Transform Infrared Spectrometer (FTIR) detection spectrum measurement at RT. The In0.3Ga0.7As0.25Sb0.75/GaSb heterostructures are lattice-matched to GaSb substrates, ensuring high material quality. The noise current at RT is analyzed and found to be the shot noise-limited at RT. The e-SWIR APD achieves a high multiplication gain of M~190 at a low bias of Vbias=- 2.5 V under illumination of a distributed feedback laser (DFB) with an emission wavelength of 2.3 µm. A high photoresponsivity of R>140 A/W is also achieved at the low bias of Vbias=-2.5 V. This type of highly sensitive e-SWIR APD, with a high internal gain capable of RT operation, provides enabling technology for e-SWIR sensing and imaging while significantly reducing size, weight, and power consumption (SWaP).

Soft, Multifunctional MXene-Coated Fiber Microelectrodes for Biointerfacing.

Flexible fiber-based microelectrodes allow safe and chronic investigation and modulation of electrically active cells and tissues. Compared to planar electrodes, they enhance targeting precision while minimizing side effects from the device-tissue mechanical mismatch. However, the current manufacturing methods face scalability, reproducibility, and handling challenges, hindering large-scale deployment. Furthermore, only a few designs can record electrical and biochemical signals necessary for understanding and interacting with complex biological systems. In this study, we present a method that utilizes the electrical conductivity and easy processability of MXenes, a diverse family of two-dimensional nanomaterials, to apply a thin layer of MXene coating continuously to commercial nylon filaments (30-300 µm in diameter) at a rapid speed (up to 15 mm/s), achieving a linear resistance below 10 Ω/cm. The MXene-coated filaments are then batch-processed into free-standing fiber microelectrodes with excellent flexibility, durability, and consistent performance even when knotted. We demonstrate the electrochemical properties of these fiber electrodes and their hydrogen peroxide (H2O2) sensing capability and showcase their applications in vivo (rodent) and ex vivo (bladder tissue). This scalable process fabricates high-performance microfiber electrodes that can be easily customized and deployed in diverse bioelectronic monitoring and stimulation studies, contributing to a deeper understanding of health and disease.

Multipressure Sampling for Improving the Performance of MOF-based Electronic Noses.

Metal-organic frameworks (MOFs) are a promising class of porous materials for the design of gas sensing arrays, which are often called electronic noses. Due to their chemical and structural tunability, MOFs are a highly diverse class of materials that align well with the similarly diverse class of volatile organic compounds (VOCs) of interest in many gas detection applications. In principle, by choosing the right combination of cross-sensitive MOFs, layered on appropriate signal transducers, one can design an array that yields detailed information about the composition of a complex gas mixture. However, despite the vast number of MOFs from which one can choose, gas sensing arrays that rely too heavily on distinct chemistries can be impractical from the cost and complexity perspective. On the other hand, it is difficult for small arrays to have the desired selectivity and sensitivity for challenging sensing applications, such as detecting weakly adsorbing gases with weak signals, or conversely, strongly adsorbing gases that readily saturate MOF pores. In this work, we employed gas adsorption simulations to explore the use of a variable pressure sensing array as a means of improving both sensitivity and selectivity as well as increasing the information content provided by each array. We studied nine different MOFs (HKUST-1, IRMOF-1, MgMOF-74, MOF-177, MOF-801, NU-100, NU-125, UiO-66, and ZIF-8) and four different gas mixtures, each containing nitrogen, oxygen, carbon dioxide, and exactly one of the hydrogen, methane, hydrogen sulfide, or benzene. We found that by lowering the pressure, we can limit the saturation of MOFs, and by raising the pressure, we can concentrate weakly adsorbing gases, in both cases, improving gas detection with the resulting arrays. In many cases, changing the system pressure yielded a better improvement in performance (as measured by the Kullback-Liebler divergence of gas composition probability distributions) than including additional MOFs. We thus demonstrated and quantified how sensing at multiple pressures can increase information content and cross-sensitivity in MOF-based arrays while limiting the number of unique materials needed in the device.

Reconstruction of the Chemical Gas Concentration Distribution Using Partial Convolution-Based Image Inpainting.

An interpolation method, which estimates unknown values with constrained information, is based on mathematical calculations. In this study, we addressed interpolation from an image-based perspective and expanded the use of image inpainting to estimate values at unknown points. When chemical gas is dispersed through a chemical attack or terrorism, it is possible to determine the concentration of the gas at each location by utilizing the deployed sensors. By interpolating the concentrations, we can obtain the contours of gas concentration. Accurately distinguishing the contours of a contaminated region from a map enables the optimal response to minimize damage. However, areas with an insufficient number of sensors have less accurate contours than other areas. In order to achieve more accurate contour data, an image inpainting-based method is proposed to enhance reliability by erasing and reconstructing low-accuracy areas in the contour. Partial convolution is used as the machine learning approach for image-inpainting, with the modified loss function for optimization. In order to train the model, we developed a gas diffusion simulation model and generated a gas concentration contour dataset comprising 100,000 contour images. The results of the model were compared to those of Kriging interpolation, one of the conventional spatial interpolation methods, finally demonstrating 13.21% higher accuracy. This suggests that interpolation from an image-based perspective can achieve higher accuracy than numerical interpolation on well-trained data. The proposed method was validated using gas concentration contour data from the verified gas dispersion modeling software Nuclear Biological Chemical Reporting And Modeling System (NBC_RAMS), which was developed by the Agency for Defense Development, South Korea.

A Ratiometric Fluorescent Probe Dye-Functionalized MOFs Integrated with Logic Gate Operation for Efficient Detection of Acetaldehyde.

Volatile organic compounds (VOCs) are a class of hazardous gases that are widely present in the atmosphere and cause great harm to human health. In this paper, a ratiometric fluorescent probe (Dye@Eu-MOFs) based on a dye-functionalized metal-organic framework was designed to detect VOCs, which showed high sensitivity and specificity for acetaldehyde solution and vapor. A linear correlation between the integrated fluorescence intensity (I510/I616) and the concentration of acetaldehyde was investigated, enabling a quantitative analysis of acetaldehyde in the ranges of 1 × 10-4~10-5 µL/mL, with a low detection limit of 8.12 × 10-4 mg/L. The selective recognition of acetaldehyde could be clearly distinguished by the naked eye under the excitation of UV light. The potential sensing mechanism was also discussed. Significantly, a molecular logic gate was constructed based on the whole system, and finally, a molecular logic network system for acetaldehyde detection connecting basic and integrated logic operations was realized. This strategy provided an effective guiding method for constructing a molecular-level logic gate for acetaldehyde detection on a simple platform.

Selective and Sensitive Detection of Fe3+ Ions Using a Red-Emissive Fluorescent Probe Based on Triphenylamine and Perylene-Linked Conjugated Microporous Polymer.

The Expansion of modern industry underscores the urgent need to address heavy metal pollution, which is a threat to human-health and environment. Efforts are underwent to develop precise technologies for detecting heavy metal ions (M+-ion). One promising approach involves the use of Conjugated Microporous Polymers (CMPs) modified with Triphenylamine (TPA) anderylene (Peryl), known as TPA-Peryl-CMP, which emits strong refluorescence. Various analytical techniques, such as Brunauer-Emmett-Teller analysis, Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and thermogravimetric analysis (TGA), are utilized to characterize the synthesized TPA-Peryl-CMP and understand its functional properties. In addition to its remarkable fluorescence behavior, TPA-Peryl-CMP shows promise as a sensor for Fe3+ ions using a turn-off strategy. Due to its exceptional stability and robust π-electron system, this platform demonstrates remarkable sensitivity and selectivity, significantly improving detection capabilities for specific analytes. Detailed procedures related to the mechanism for detecting Fe3+ ions are outlined for sensing Fe3+ ions, revealing a notably strong linear correlation within the concentration range of 0-3 µM, with a correlation coefficient of 0.9936 and the Limit of detection (LOD) 20 nM. It is anticipated that development of such a kind of TPA-Peryl-CMP will observe broader applications in detecting various analytes related to environmental and biological systems.

Paper-based optical sensor arrays for simultaneous detection of multi-targets in aqueous media: A review.

Sensor arrays, which draw inspiration from the mammalian olfactory system, are fundamental concepts in high-throughput analysis based on pattern recognition. Although numerous optical sensor arrays for various targets in aqueous media have demonstrated their diverse applications in a wide range of research fields, practical device platforms for on-site analysis have not been satisfactorily established. The significant limitations of these sensor arrays lie in their solution-based platforms, which require stationary spectrophotometers to record the optical responses in chemical sensing. To address this, this review focuses on paper substrates as device components for solid-state sensor arrays. Paper-based sensor arrays (PSADs) embedded with multiple detection sites having cross-reactivity allow rapid and simultaneous chemical sensing using portable recording apparatuses and powerful data-processing techniques. The applicability of office printing technologies has promoted the realization of PSADs in real-world scenarios, including environmental monitoring, healthcare diagnostics, food safety, and other relevant fields. In this review, we discuss the methodologies of device fabrication and imaging analysis technologies for pattern recognition-driven chemical sensing in aqueous media.

Gas-Induced Electrical and Magnetic Modulation of Two-Dimensional Conductive Metal-Organic Framework.

Controlled modulation of electronic and magnetic properties in stimuli-responsive materials provides valuable insights for the design of magnetoelectric or multiferroic devices. This paper demonstrates the modulation of electrical and magnetic properties of a semiconductive, paramagnetic metal-organic framework (MOF) Cu3(C6O6)2 with small gaseous molecules, NH3, H2S, and NO. This study merges chemiresistive and magnetic tests to reveal that the MOF undergoes simultaneous changes in electrical conductance and magnetization that are uniquely modulated by each gas. The features of response, including direction, magnitude, and kinetics, are modulated by the physicochemical properties of the gaseous molecules. This study advances the design of multifunctional materials capable of undergoing simultaneous changes in electrical and magnetic properties in response to chemical stimuli.

Estimation of Environmental Effects and Response Time in Gas-Phase Explosives Detection Using Photoluminescence Quenching Method.

Detecting the presence of explosives is important to protect human lives during military conflicts and peacetime. Gas-phase detection of explosives can make use of the change of material properties, which can be sensitive to environmental conditions such as temperature and humidity. This paper describes a remote-controlled automatic shutter method for the environmental impact assessment of photoluminescence (PL) sensors under near-open conditions. Utilizing the remote-sensing method, we obtained environmental effects without being exposed to sensing vapor molecules and explained how PL intensity was influenced by the temperature, humidity, and exposure time. We also developed a theoretical model including the effect of exciton diffusion for PL quenching, which worked well under limited molecular diffusions. Incomplete recovery of PL intensity or the degradation effect was considered as an additional factor in the model.

Ultrafast Dynamics, Optical Nonlinearities, and Chemical Sensing Application of Free-Standing Porous Silicon-Based Optical Microcavities.

The present work demonstrates the ultrafast carrier dynamics and third-order nonlinear optical properties of electrochemically fabricated free-standing porous silicon (FS-PSi)-based optical microcavities via femtosecond transient absorption spectroscopy (TAS) and single-beam Z-scan techniques, respectively. The TAS (pump: 400 nm, probe: 430-780 nm, ∼70 fs, 1 kHz) decay dynamics are dominated by the photoinduced absorption (PIA, lifetime range: 4.7-156 ps) as well as photoinduced bleaching (PIB, 4.3-324 ps) for the cavity mode (λc) and the band edges. A fascinating switching behavior from the PIB (-ve) to the PIA (+ve) has been observed in the cavity mode, which shows the potential in ultrafast switching applications. The third-order optical nonlinearities revealed an enhanced two-photon absorption coefficient (ß) in the order of 10-10 mW-1 along with the nonlinear refractive index (n2) in the range of 10-17 m2 W-1. Furthermore, a real-time sensing application of such FS-PSi microcavities has been demonstrated for detecting organic solvents by simultaneously monitoring the kinetics in reflection and transmission mode.

Powders to Thin Films: Advances in Conjugated Microporous Polymer Chemical Sensors.

Chemical sensing of harmful species released either from natural or anthropogenic activities is critical to ensuring human safety and health. Over the last decade, conjugated microporous polymers (CMPs) have been proven to be potential sensor materials with the possibility of realizing sensing devices for practical applications. CMPs found to be unique among other porous materials such as metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) due to their high chemical/thermal stability, high surface area, microporosity, efficient host-guest interactions with the analyte, efficient exciton migration along the π-conjugated chains, and tailorable structure to target specific analytes. Several CMP-based optical, electrochemical, colorimetric, and ratiometric sensors with excellent selectivity and sensing performance were reported. This review comprehensively discusses the advances in CMP chemical sensors (powders and thin films) in the detection of nitroaromatic explosives, chemical warfare agents, anions, metal ions, biomolecules, iodine, and volatile organic compounds (VOCs), with simultaneous delineation of design strategy principles guiding the selectivity and sensitivity of CMP. Preceding this, various photophysical mechanisms responsible for chemical sensing are discussed in detail for convenience. Finally, future challenges to be addressed in the field of CMP chemical sensors are discussed.

Exploring the Fate of Copper Ions in the Synthesis of Graphdiyne.

Copper is a crucial catalyst in the synthesis of graphdiyne (GDY). However, as catalysts, the final fate of the copper ions has hardly been concerned, which are usually treated as impurities. Here, it is observed that after simple washing with water and ethanol, GDY still contains a certain amount of copper ions, and demonstrated that the copper ions are adsorbed at the atomic layers of GDY. Furthermore, we transformed in situ the copper ions into ultrathin Cu nanocrystals, and the obtained Cu/GDY hybrids can be generally converted into a series of metal/GDY hybrid materials, such as Ag/GDY, Au/GDY, Pt/GDY, Pd/GDY, and Rh/GDY. The Cu/GDY hybrids exhibit extraordinary surface enhanced Raman scattering effect and can be applied in pollutant efficient enrichment and detection.

Colloidal Chiral Carbon Dots: An Emerging System for Chiroptical Applications.

Chiral CDots (c-CDots) not only inherit those merits from CDots but also exhibit chiral effects in optical, electric, and bio-properties. Therefore, c-CDots have received significant interest from a wide range of research communities including chemistry, physics, biology, and device engineers. They have already made decent progress in terms of synthesis, together with the exploration of their optical properties and applications. In this review, the chiroptical properties and chirality origin in extinction circular dichroism (ECD) and circularly polarized luminescence (CPL) of c-CDots is briefly discussed. Then, the synthetic strategies of c-CDots is summarized, including one-pot synthesis, post-functionalization of CDots with chiral ligands, and assembly of CDots into chiral architectures with soft chiral templates. Afterward, the chiral effects on the applications of c-CDots are elaborated. Research domains such as drug delivery, bio- or chemical sensing, regulation of enzyme-like catalysis, and others are covered. Finally, the perspective on the challenges associated with the synthetic strategies, understanding the origin of chirality, and potential applications is provided. This review not only discusses the latest developments of c-CDots but also helps toward a better understanding of the structure-property relationship along with their respective applications.

Hydrogels for Chemical Sensing and Biosensing.

The development and synthesis of hydrogels for chemical and biosensing are of great value. Hydrogels can be tailored to its own physical structure, chemical properties, biocompatibility, and sensitivity to external stimuli when being used in a specific environment. Herein, hydrogels and their applications in chemical and biosensing are mainly covered. In particular, it is focused on the manner in which hydrogels serve as sensing materials to a specific analyte. Different types of responsive hydrogels are hence introduced and summarized. Researchers can modify different chemical groups on the skeleton of the hydrogels, which make them as good chemical and biosensing materials. Hydrogels have great application potential for chemical and biosensing in the biomedical field and some emerging fields, such as wearable devices.

Application and Prospect of Pre-transfusion Detection Technology / 生物化学与生物物理进展

Blood transfusion accuracy is crucial for disease treatment and emergency rescue. Prior to a blood transfusion, it is essential to perform a number of tests to assure proper clinical treatment and reduce the risk of complications. Pre-transfusion testing refers primarily to the blood group, coagulation, and infection to assure transfusion safety and prevent cross-infection. Blood type, cross-matching blood, fibrinogen, viral hepatitis, human immunodeficiency virus, and syphilis are routine pre-transfusion tests. Immunoassay is the traditional clinical pretransfusion detection method. With the expansion of clinical treatment requirements from hospital to on-site treatment, new technologies, such as electrochemical sensing, microfluidics, and spectroscopy technology, are being developed gradually for rapid detection prior to blood transfusion. The development of technologies including colloidal gold immunity and biochips has facilitated the shift from large-scale laboratory equipment to portable testing for pre-transfusion screening. Further, the introduction of artificial intelligence technologies such as machine learning, biometric technology, and computer vision has contributed to the advancement of intelligent pre-transfusion testing. This article reviews the various application scenarios, benefits, and drawbacks of different pre-transfusion detection technologies, analyzes the application of a series of new technologies in pre-transfusion detection and its future development trend, and provides a reference for promoting the development of pre-transfusion detection and even rapid disease marker detection.