Recent progress in lanthanide-based fluorescent nanomaterials for tetracycline detection and removal.

Tetracycline (TC) has been widely used in clinical medicine and animal growth promotion due to its broad-spectrum antibacterial properties and affordable prices. Unfortunately, the high toxicity and difficult degradation rate of TC molecules make them easy to accumulate in the environment, which breaks the ecological balance and seriously threatens human health. Rapid and accurate detection of TC residue levels is important for ensuring water quality and food safety. Recently, fluorescence detection technology of TC residues has developed rapidly. Lanthanide nanomaterials, based on the high luminescence properties of lanthanide ions and the high matching with TC energy levels, are favored in the real-time trace detection of TC due to their advantages of high sensitivity, rapidity, and high selectivity. Therefore, they are considered potential substitutes for traditional detection methods. This review summarizes the synthesis strategy, TC response mechanism, removal mechanism, and applications in intelligent sensing. Finally, the development of lanthanide nanomaterials for TC fluorescence detection and removal is reasonably summarized and prospected. This review provides a reference for the establishment of a method for the accurate determination of TC content in complex food matrices.

Biomimetic Octopus Suction Cup with Attachment Force Self-Sensing Capability for Cardiac Adhesion.

This study develops a biomimetic soft octopus suction device with integrated self-sensing capabilities designed to enhance the precision and safety of cardiac surgeries. The device draws inspiration from the octopus's exceptional ability to adhere to various surfaces and its sophisticated proprioceptive system, allowing for real-time adjustment of adhesive force. The research integrates thin-film pressure sensors into the soft suction cup design, emulating the tactile capabilities of an octopus's sucker to convey information about the contact environment in real time. Signals from sensors within soft materials exhibiting complex strain characteristics are processed and interpreted using the grey wolf optimizer-back propagation (GWO-BP) algorithm. The tissue stabilizer is endowed with the self-sensing capabilities of biomimetic octopus suckers, and real-time feedback on the adhesion state is provided. The embedding location of the thin-film pressure sensors is determined through foundational experiments with flexible substrates, standard spherical tests, and biological tissue trials. The newly fabricated suction cups undergo compression pull-off tests to collect data. The GWO-BP algorithm model accurately identifies and predicts the suction cup's adhesion force in real time, with an error rate below 0.97% and a mean prediction time of 0.0027 s. Integrating this technology offers a novel approach to intelligent monitoring and attachment assurance during cardiac surgeries. Hence, the probability of potential cardiac tissue damage is reduced, with future applications for integrating intelligent biomimetic adhesive soft robotics.

Improving urinary incontinence management and sleep quality with wetness sensing technology in absorbent products.

Using absorbent products to manage the urinary incontinence (UI) of dependent residents in care facilities (such as nursing homes, and hospitals) requires frequent routine checks throughout the day and night to see if products need changing. Timely changes of saturated products are necessary to avoid long-lasting skin exposure to wet absorbent products, unpleasant odor, leaking of such products and embarrassing moments for the users. Limited staffing, high workload, and peaks on the demand for caregiving are challenges that hamper swift support for the care dependent population. This paper describes novel sensing technology that has been developed for monitoring the wet state of absorbent products remotely. The Orizon system by Ontex enables caregivers to prioritize care routines, avoid sleep disturbance at night and achieve effective leakage prevention. Moreover, the monitoring data can be used to understand the individual product usage and incontinence pattern of individuals, helping incontinence specialists to choose the optimal product and implement appropriate toilet training for each user.

Dual-mode fluorescence and colorimetric smartphone-based sensing platform with oxidation-induced self-assembled nanoflowers for sarcosine detection.

BACKGROUND: Early prostatic cancer (PCa) diagnosis significantly improves the chances of successful treatment and enhances patient survival rates. Traditional enzyme cascade-based early cancer detection methods offer efficiency and signal amplification but are limited by cost, complexity, and enzyme dependency, affecting stability and practicality. Meanwhile, sarcosine (Sar) is commonly considered a biomarker for PCa development. It is essential to develop a Sar detection method based on cascade reactions, which should be efficient, low skill requirement, and suitable for on-site testing. RESULTS: To address this, our study introduces the synthesis of organic-inorganic self-assembled nanoflowers to optimize existing detection methods. The Sar oxidase (SOX)-inorganic hybrid nanoflowers (Cu3(PO4)2:Ce@SOX) possess inherent fluorescent properties and excellent peroxidase activity, coupled with efficient enzyme loading. Based on this, we have developed a dual-mode multi-enzyme cascade nanoplatform combining fluorescence and colorimetric methods for the detection of Sar. The encapsulation yield of Cu3(PO4)2:Ce@SOX reaches 84.5 %, exhibiting a remarkable enhancement in catalytic activity by 1.26-1.29 fold compared to free SOX. The present study employing a dual-signal mechanism encompasses 'turn-off' fluorescence signals ranging from 0.5 µM to 60 µM, with a detection limit of 0.226 µM, and 'turn-on' colorimetric signals ranging from 0.18 µM to 60 µM, with a detection limit of 0.120 µM. SIGNIFICANCE: Furthermore, our study developed an intelligent smartphone sensor system utilizing cotton swabs for real-time analysis of Sar without additional instruments. The nano-platform exhibits exceptional repeatability and stability, rendering it well-suited for detecting Sar in authentic human urine samples. This innovation allows for immediate analysis, offering valuable insights for portable and efficient biosensors applicable to Sar and other analytes.

[Research Progress in Data Acquisition and Intelligent Sensing Methods for Lumbar Electromyographic Signals].

Population aging trend is taking place in our country, and low back pain is a symptom of neuromuscular diseases of concern in the elderly. Accurately analyzing the disease of low back pain is important for both timely intervention and rehabilitation of patients. As a kind of bioelectrical signal, the acquisition and analysis of lumbar electromyography (EMG) signal is an important direction for the study of low back pain. The study reviews the acquisition of lumbar EMG by different types of sensors, introduces the signal characteristics of needle electrodes, surface electromyography electrodes and array electrodes, describes the use of signal algorithms, points out that wireless sensors and the use of deep learning algorithms are the direction of development, and puts forward prospects for its further development.

Application of Deep Learning and Intelligent Sensing Analysis in Smart Home.

Deep learning technology can improve sensing efficiency and has the ability to discover potential patterns in data; the efficiency of user behavior recognition in the field of smart homes has been further improved, making the recognition process more intelligent and humanized. This paper analyzes the optical sensors commonly used in smart homes and their working principles through case studies and explores the technical framework of user behavior recognition based on optical sensors. At the same time, CiteSpace (Basic version 6.2.R6) software is used to visualize and analyze the related literature, elaborate the main research hotspots and evolutionary changes of optical sensor-based smart home user behavior recognition, and summarize the future research trends. Finally, fully utilizing the advantages of cloud computing technology, such as scalability and on-demand services, combining typical life situations and the requirements of smart home users, a smart home data collection and processing technology framework based on elderly fall monitoring scenarios is designed. Based on the comprehensive research results, the application and positive impact of optical sensors in smart home user behavior recognition were analyzed, and inspiration was provided for future smart home user experience research.

Ultra-conformal epidermal antenna for multifunctional motion artifact-free sensing and point-of-care monitoring.

Accurate acquisition of physiological and physical information from human tissue is essential for health monitoring, disease prevention and treatment. The existing antennas with traditional rigid or flexible substrates are susceptible to motion artifacts in wearable applications due to the miniaturization limitation and lack of proper adhesion and conformal interfaces with the skin. Recent advances in wearable radio frequency (RF) bioelectronics directly drawn on the skin are a promising solution for future skin-interfaced devices. Herein, we present a first-of-its kind epidermal antenna architecture with skin as the antenna substrate, which is ultra-low profile, ultra-conformal, ultra-compact, and simple fabrication without specialized equipment. The radiation unit and ground of antenna are drawn directly on the skin with the strong adhesion and ultra conformality. Therefore, this RF device is highly adaptable to motion. As a proof-of- feasibility, epidermal antenna can be freely drawn on demand at different locations on the skin for the development of temperature sensor, skin hydration sensor, strain sensor, glucose sensor and other devices. An epidermal antenna-based temperature sensor can offer accurate and real-time monitoring of human body temperature changes in the ultra-wideband (UWB) range. The results during the monitoring of hydration level with and without stretching show that the epidermal antenna drawn on the skin is motion artifact-free. We also designed an epidermal antenna array employing a horseshoe-shaped configuration for the precise identification of various gestures. In addition, the non-invasive blood glucose level (BGL) monitoring results during the in-vivo experiments report high correlation between the epidermal antenna responses and BGLs, without any time hysteresis. After the prediction of BGL by BP network, all the predicted BGL values are fallen 100% into the clinically acceptable zones. Together, these results show that epidermal antenna offers a promising new approach for biosensing platform.

Building Feedback-Regulation System Through Atomic Design for Highly Active SO2 Sensing.

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction. Herein, we present an ingenious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO2 sensing. We found that the single Pt sites on the MoS2 surface can induce easier volatilization of adjacent S species to activate the whole inert S plane. Reversely, the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms, thus creating a combined system involving S vacancy-assisted single Pt sites (Pt-Vs) to synergistically improve the adsorption ability of SO2 gas molecules. Furthermore, in situ Raman, ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS2 supports in SO2 gas atmosphere. Equipped with wireless-sensing modules, the final Pt1-MoS2-def sensors array can further realize real-time monitoring of SO2 levels and cloud-data storage for plant growth. Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

Intelligent monitoring of the available lead (Pb) and cadmium (Cd) in soil samples based on half adder and half subtractor molecular logic gates.

The available heavy metals in soil samples can cause the direct toxicity on ecosystems, plants, and human health. Traditional chemical extraction and recombinant bacterial methods for the available heavy metals assay often suffer from inaccuracy and poor specificity. In this work, we construct half adder and half subtractor molecular logic gates with molecular-level biocomputation capabilities for the intelligent sensing of the available lead (Pb) and cadmium (Cd). The available Pb and Cd can cleave DNAzyme sequences to release the trigger DNA, which can activate the hairpin probe assembly in the logic system. This multifunctional logic system can not only achieve the intelligent recognition of the available Pb and Cd according to the truth tables, but also can realize the simultaneous quantification with high sensitivity, with the detection limits of 2.8 pM and 25.6 pM, respectively. The logic biosensor is robust and has been applied to determination of the available Pb and Cd in soil samples with good accuracy and reliability. The relative error (Re) between the logic biosensor and the DTPA + ICP-MS method was from -8.1 % to 7.9 %. With the advantages of programmability, scalability, and multicomputing capacity, the molecular logic system can provide a simple, rapid, and smart method for intelligent monitoring of the available Pb and Cd in environmental samples.

Simultaneously Intelligent Sensing and Beamforming Based on an Adaptive Information Metasurface.

Due to its ability to adapt to a variety of electromagnetic (EM) environments, the sensing-enabled metasurface has garnered significant attention. However, large-scale EM-field sensing to obtain more information is still very challenging. Here, an adaptive information metasurface is proposed to enable intelligent sensing and wave manipulating simultaneously or more specifically, to realize intelligent target localization and beam tracking adaptively. The metasurface is composed of an array of meta-atoms, and each is loaded with two PIN diodes and a sensing-channel structure, for polarization-insensitive and programmable beamforming and sensing. By controlling the state of the PIN diode, the proposed meta-atom has 1-bit phase response in the designed frequency band, while the sensing loss keeps higher than -10 dB for both "ON" and "OFF" states. Hence there is nearly no interaction between the beamforming and sensing modes. Experiments are conducted to show multiple functions of the metasurface, including intelligent target sensing and self-adaptive beamforming, and the measured results are in good agreement with the numerical simulations and theoretical calculations.

The emerging progress on wound dressings and their application in clinic wound management.

Background: In addition to its barrier function, the skin plays a crucial role in maintaining the stability of the body's internal environment and normal physiological functions. When the skin is damaged, it is important to select proper dressings as temporary barriers to cover the wound, which can exert significant effects on defence against microbial infection, maintaining normal tissue/cell functions, and coordinating the process of wound repair and regeneration. It now forms an important approach in clinic practice to facilitate wound repair. Search strategies: We conducted a comprehensive literature search using online databases including PubMed, Web of Science, MEDLINE, ScienceDirect, Wiley Online Library, CNKI, and Wanfang Data. In addition, information was obtained from local and foreign books on biomaterials science and traumatology. Results: This review focuses on the efficacy and principles of functional dressings for anti-bacteria, anti-infection, anti-inflammation, anti-oxidation, hemostasis, and wound healing facilitation; and analyses the research progress of dressings carrying living cells such as fibroblasts, keratinocytes, skin appendage cells, and stem cells from different origins. We also summarize the recent advances in intelligent wound dressings with respect to real-time monitoring, automatic drug delivery, and precise adjustment according to the actual wound microenvironment. In addition, this review explores and compares the characteristics, advantages and disadvantages, mechanisms of actions, and application scopes of dressings made from different materials. Conclusion: The real-time and dynamic acquisition and analysis of wound conditions are crucial for wound management and prognostic evaluation. Therefore, the development of modern dressings that integrate multiple functions, have high similarity to the skin, and are highly intelligent will be the focus of future research, which could drive efficient wound management and personalized medicine, and ultimately facilitate the translation of health monitoring into clinical practice.

The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review.

Disease diagnosis and monitoring using conventional healthcare services is typically expensive and has limited accuracy. Wearable health technology based on flexible electronics has gained tremendous attention in recent years for monitoring patient health owing to attractive features, such as lower medical costs, quick access to patient health data, ability to operate and transmit data in harsh environments, storage at room temperature, non-invasive implementation, mass scaling, etc. This technology provides an opportunity for disease pre-diagnosis and immediate therapy. Wearable sensors have opened a new area of personalized health monitoring by accurately measuring physical states and biochemical signals. Despite the progress to date in the development of wearable sensors, there are still several limitations in the accuracy of the data collected, precise disease diagnosis, and early treatment. This necessitates advances in applied materials and structures and using artificial intelligence (AI)-enabled wearable sensors to extract target signals for accurate clinical decision-making and efficient medical care. In this paper, we review two significant aspects of smart wearable sensors. First, we offer an overview of the most recent progress in improving wearable sensor performance for physical, chemical, and biosensors, focusing on materials, structural configurations, and transduction mechanisms. Next, we review the use of AI technology in combination with wearable technology for big data processing, self-learning, power-efficiency, real-time data acquisition and processing, and personalized health for an intelligent sensing platform. Finally, we present the challenges and future opportunities associated with smart wearable sensors.

Utilizing the intelligent sensing function of conjugated materials to create intelligent flute training equipment.

The manufacturing of flutes has always relied on traditional ceramics and metals, which may be affected by various factors during the manufacturing process, as well as the lack of intelligent sensing functions, resulting in poor sound quality and performance of the instrument. The purpose of this article is to explore the use of the intelligent sensing function of conjugated materials to create intelligent flute training equipment, achieve automatic tuning, volume control, etc., and improve the playing experience and training effect of the instrument. This article first analyzes the smart sensing function of conjugate materials and applies it to smart flute training equipment; then, introduces photosensitive materials at appropriate locations to change the size and shape of the flute's sound hole, thereby adjusting the timbre; finally, uses smart flute training based on conjugate materials for real-time perception of performers' performance experiments. The test results show that the average delay time of the conjugate material trench is reduced by 73.1% compared with the average delay time of the ceramic trench, and is reduced by 63.5% compared with the average delay time of the metal trench. This shows that the conjugated material flute is more intelligent and can quickly respond to the player's performance and automatically control and respond.

[Patent application of intelligent quality control technology in traditional Chinese medicine production process: a review].

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.

Construction of molecular logic gates using heavy metal ions as inputs based on catalytic hairpin assembly and CRISPR-Cas12a.

We successfully constructed several molecular logic gates using heavy metal ions as inputs based on catalytic hairpin assembly (CHA) and CRISPR-Cas12a. The corresponding DNAzymes were used to recognize heavy metal ions (Hg2+, Cd2+, Pb2+, and Mn2+). The specific cleavage between heavy metal ions and DNAzymes leads to the release of the trigger DNA, which can be used to activate CHA through logic computation. The CHA-generated DNA duplexes contain the protospacer adjacent motifs (PAM) sequence, which can be distinguished by CRISPR-Cas12a. The hybridization interactions between the duplexes and gRNA will activate the trans-cleavage capability of Cas12a, which can cleave the single-stranded DNA (ssDNA) reporter. The separation of the fluorescence group and quench group in ssDNA will generate a high fluorescence signal for readout. Using Hg2+ and Cd2+ as the two inputs, several basic logic gates were constructed, including OR, AND, and INHIBT. Using Hg2+, Cd2+, Pb2+, and Mn2+ as the four inputs, cascaded logic gates were further fabricated. With the advantages of scalability, versatility, and logic computing capability, our proposed molecular logic gates can provide an intelligent sensing system for heavy metal ions monitoring.

Cascaded molecular logic gates using antibiotics as inputs based on exonuclease III and DNAzyme.

We successfully constructed several cascaded molecular logic gates (2INHIBIT-2AND, 2AND-2OR, and 2OR-2INHIBIT) using three different antibiotics as the inputs. In the presence of kanamycin (KAN), chloramphenicol (CHL), or oxytetracycline (OXY), the aptamer-antibiotic recognition will release the trigger DNA to active the hairpin DNA hybridization. Exonuclease III (Exo III)-mediated catalysis reaction was introduced in the logic system to generate Mg2+-dependent DNAzyme, which was used to cleave the fluorescence signal reporter probe. For input, the presence and absence of the antibiotic was defined as 1 and 0, respectively. For output, the fluorescence intensity higher or lower than the threshold value was defined as 1 and 0, respectively. In the 2INHIBIT-2AND logic circuit, the 101 input combination generates an output of 1 and other input combinations generate an output of 0. In the 2AND-2OR logic circuit, the input combinations of 001, 011, 110, 101, and 111 generate an output of 1 and other input combinations generate an output of 0. In the 2OR-2INHIBIT logic circuit, the input combinations of 010, 100, and 110 generate an output of 1 and other input combinations generate an output of 0. Our constructed logic system exhibits high selectivity and can work even in complex water samples. With the advantages of multiple biocomputation capabilities, high flexibility, and easy scalability, this logic gate system provides a new analytical method for the intelligent detection of different antibiotics.

Radiation environment monitoring system based on the Internet of Things technology / 中国辐射卫生

This paper presents a nuclear radiation environment monitoring scheme based on the Internet of Things technology. The scheme primarily utilizes ZigBee wireless communication protocol, dedicated line network topology, and cloud-based processing techniques to achieve the entire process of acquisition, localization, transmission, tracking, monitoring, and management of X, γ, α, β, and neutron radiation data at nuclear radiation monitoring sites. Through initial application, the system demonstrates favorable characteristics such as good portability, strong scalability, secure information transmission, and deep data mining.

Patent application of intelligent quality control technology in traditional Chinese medicine production process: a review / 中国中药杂志

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.

Serpentine-Inspired Strain Sensor with Predictable Cracks for Remote Bio-Mechanical Signal Monitoring.

Flexible strain sensors have attracted intense interest due to their application as intelligent wearable electronic devices. However, it is still a huge challenge to achieve a flexible sensor with simultaneous high sensitivity, excellent durability, and a wide sensing region. In this work, a crack-based strain sensor with a paired-serpentine conductive network is fabricated onto flexible film by screen printing. The innovative conductive network exhibits a controlled crack morphology during stretching, which endows the prepared sensor with outstanding sensing characteristics, including high sensitivity (gauge factor up to 2391.5), wide detection (rang up to 132%), low strain detection limit, a fast response time (about 40 ms), as well as excellent durability (more than 2000 stretching/releasing cycles). Benefiting from these excellent performances, full-range human body motions including subtle physiological signals and large motions are accurately detected by the prepared sensor. Furthermore, wearable electronic equipment integrated with a wireless transmitter and the prepared strain sensor shows great potential for remote motion monitoring and intelligent mobile diagnosis for humans. This work provides an effective strategy for the fabrication of novel strain sensors with highly comprehensive performance.

Emerging MXene-Polymer Hybrid Nanocomposites for High-Performance Ammonia Sensing and Monitoring.

Ammonia (NH3) is a vital compound in diversified fields, including agriculture, automotive, chemical, food processing, hydrogen production and storage, and biomedical applications. Its extensive industrial use and emission have emerged hazardous to the ecosystem and have raised global public health concerns for monitoring NH3 emissions and implementing proper safety strategies. These facts created emergent demand for translational and sustainable approaches to design efficient, affordable, and high-performance compact NH3 sensors. Commercially available NH3 sensors possess three major bottlenecks: poor selectivity, low concentration detection, and room-temperature operation. State-of-the-art NH3 sensors are scaling up using advanced nano-systems possessing rapid, selective, efficient, and enhanced detection to overcome these challenges. MXene-polymer nanocomposites (MXP-NCs) are emerging as advanced nanomaterials of choice for NH3 sensing owing to their affordability, excellent conductivity, mechanical flexibility, scalable production, rich surface functionalities, and tunable morphology. The MXP-NCs have demonstrated high performance to develop next-generation intelligent NH3 sensors in agricultural, industrial, and biomedical applications. However, their excellent NH3-sensing features are not articulated in the form of a review. This comprehensive review summarizes state-of-the-art MXP-NCs fabrication techniques, optimization of desired properties, enhanced sensing characteristics, and applications to detect airborne NH3. Furthermore, an overview of challenges, possible solutions, and prospects associated with MXP-NCs is discussed.