A new type of carbonized polymer dot was prepared by the one-step hydrothermal method of triethoxylsilane (TEOS) and citric acid (CA). The sensor made from carbonized polymer dots (CPDs) showed superior gas sensing performance toward ammonia at room temperature. The Si, O-codoped CPDs exhibited superior ammonia sensing performance at room temperature, including a low practical limit of detection (pLOD) of 1 ppm (Ra/Rg: 1.10, 1 ppm), short response/recovery time (30/36 s, 1 ppm), high humidity resistance (less than 5% undulation when changing relative humidity to 80 from 30%), high stability (less than 5% initial response undulation after 120 days), reliable repeatability, and high selectivity against other interferential gases. The gas sensing mechanism was investigated through control experiments and in situ FTIR, indicating that Si, O-codoping essentially improves the electron transfer capability of CPDs and synergistically dominates the superior ammonia sensing properties of the CPDs. This work presents a facile strategy for constructing novel high-performance, single-component carbonized polymer dots for gas sensing.@en

Inspired by the activation mechanism of slow anion channels 1 (SLAC1) in plants that proton pump reversibly induces plant stomata open for CO2 adsorption, a CO2-switching H+ conduction/HCO3− diffusion dual ion channel (CO2-switching-DIC) was constructed by assembling γ-cyclodextrin-MOF (γ-CD-MOF) and 3,4,9,10-perylenetetracarboxylic acid (PTCA) for CO2 chemiresistive sensing. The obtained CO2 sensor exhibited high response (Rg/R0 = 1.33, 50 ppm) and selectivity, low practical limit of detection (1 ppm) and excellent consistency (94.5%) with a commercial infrared CO2 meter at room temperature. It is indicated that hydrogen bond networks in CO2-switching-DIC will be enlarged with the increasing of carboxylic group’s content on perylene skeleton, thereby modulating proton conductivity at molecular level and furthermore CO2 sensing performance of the composite. The CO2-switching-DIC-based sensor has been utilized to distinguish the exhaled CO2 concentration between lung cancer patients and healthy individuals, illustrating its promising application prospect in non-invasive diagnose.@en

Inspired by the CO₂-induced reversible activation mechanism of the slow anion channel 1 (SLAC1) in plant stomatal guard cells during plant photosynthesis, we designed and prepared a CO₂- switchable H⁺/OH⁻ ion channel (CSPH ion channel). A high-performance chemiresistive room temperature CO₂ sensor has been prepared based on this CSPH ion channel. The obtained CO₂ room temperature sensor γ-CD-MOF@RhB exhibits high sensitivity (R_g/R₀ = 1.50, 100 ppm), excellent selectivity, good stability (less than 5% reduction in 30 days response value), and 99.96% consistency with commercial infrared CO₂ meter. The practical limit of detection (pLOD) of the γ-CD-MOF@RhB sensor reaches 10 ppm at room temperature toward CO₂, which is the lowest for reported MOF-derived chemiresistive room temperature CO₂ sensors so far. Ion conduction mechanism studies have shown that the CSPH ion channel behaves as a CO₂-switchable H⁺/OH⁻ ion channel with a switching point of approximately 60 000 ppm CO₂. As an application attempt, the fabricated low pLOD CO₂ sensor has been used for human exhaled CO₂ detection to compare CO₂ concentration in the breath of individuals before and after exercise and COVID-19. It was also logically indicated that the average concentration of human exhaled CO₂ after COVID-19 recovery is different for undiseased subjects.

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Transition metal dichalcogenides (TMDCs) garner significant attention for their potential to create high-performance gas sensors. Despite their favorable properties such as tunable bandgap, high carrier mobility, and large surface-to-volume ratio, the performance of TMDCs devices is compromised by sulfur vacancies, which reduce carrier mobility. To mitigate this issue, we propose a simple and universal approach for patching sulfur vacancies, wherein thiol groups are inserted to repair sulfur vacancies. The sulfur vacancy patching (SVP) approach is applied to fabricate a MoS₂-based gas sensor using mechanical exfoliation and all-dry transfer methods, and the resulting 4-nitrothiophenol (4NTP) repaired molybdenum disulfide (4NTP-MoS₂) is prepared via a sample solution process. Our results show that 4NTP-MoS₂ exhibits higher response (increased by 200 %) to ppb-level NO₂ with shorter response/recovery times (61/82 s) and better selectivity at 25 °C compared to pristine MoS₂. Notably, the limit of detection (LOD) toward NO₂ of 4NTP-MoS₂ is 10 ppb. Kelvin probe force microscopy (KPFM) and density functional theory (DFT) reveal that the improved gas sensing performance is mainly attributed to the 4NTP-induced n-doping effect on MoS₂ and the corresponding increment of surface absorption energy to NO₂. Additionally, our 4NTP-induced SVP approach is universal for enhancing gas sensing properties of other TMDCs, such as MoSe₂, WS₂, and WSe₂.

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To develop multifunctional small-molecule prodrugs is highly desirable for cancer treatment but remains challenging in intrinsic traceability. As an acid-cleavable linkage, a Schiff bases benefiting from its distinctive fluorescence quenching ability was selected to prepare a small-molecule prodrug with cancer-targeted and self-indicating. In this study, we designed and developed a multifunctional self-assembled nanobomb of amphiphilic TPE-Lenalidomide prodrug, which comprises a hydrophobic aggregation-induced emission (AIE) probe 4-(1,2,2-triphenylvinyl)benzaldehyde (TPE-CHO) and a hydrophilic anticancer drug Lenalidomide via a Schiff base linkage. We investigated the synergistic effect of d-PET and C═N isomerization which would keep the fluorescence of TPE-Lenalidomide in the “always off” state by density functional theory (DFT) calculation. Once reaching the pathological site, such a vesicular nanobomb of TPE-Lenalidomide will be acidolyzed to release the AIE probe and Lenalidomide molecules simultaneously, consequently realizing high-efficiency effects of tumor imaging and cancer therapy (cell viability: normal cell L929, ∼79.49%; cancer cell 4T1, ∼27.08%; p = 0.000118). This work may pave an avenue to prepare small-molecule prodrugs for tumor-targeted diagnosis and cancer therapy.

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Constructing near-infrared light (NIR) light-enhanced room temperature gas sensors is becoming more promising for practical application. In this study, learning from the structure and photosynthetic process of chlorophyll thylakoid membranes in plants, the first “Thylakoid membrane” structural formaldehyde (HCHO) sensor is constructed by matching the upconversion emission of the lanthanide-doped upconversion nanoparticles (UCNPs) and the UV–vis adsorption of the as-prepared nanocomposites. The NIR-mediated sensor exhibits excellent performances, including ultra-high response (R_a / R_g = 2.22, 1 ppm), low practical limit of detection (50 ppb), reliable repeatability, high selectivity, and broadband spectral response. The practicality of the NIR-mediated gas sensor is confirmed through the remote and external stimulation test. A study of sensing mechanism demonstrates that it is the UCNPs-based light transducer produces more light-induced oxygen species for gas response in the process of non-radiative/radiative energy transfer, playing a key role in significantly improving the sensing properties of the sensor. The universality of NIR-mediated gas sensors based on UCNPs is verified using ZnO, In₂O_3, and SnO₂ systems. This work paves a way for fabricating high-performance NIR-mediated gas sensors and will expand the application fields of NIR light.

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Achieving convenient and accurate detection of indoor ppb-level formaldehyde is an urgent requirement to ensure a healthy working and living environment for people. Herein, ultrasmall In₂O₃ nanorods and supramolecularly functionalized reduced graphene oxide are selected as hybrid components of visible-light-driven (VLD) heterojunctions to fabricate ppb-level formaldehyde (HCHO) gas sensors (named InAG sensors). Under 405 nm visible light illumination, the sensor exhibits an outstanding response toward ppb-level HCHO at room temperature, including the ultralow practical limit of detection (pLOD) of 5 ppb, high response (R_a/R_g = 2.4, 500 ppb), relatively short response/recovery time (119 s/179 s, 500 ppb), high selectivity, and long-term stability. The ultrasensitive room temperature HCHO-sensing property is derived from visible-light-driven and large-area heterojunctions between ultrasmall In₂O₃ nanorods and supramolecularly functionalized graphene nanosheets. The performance of the actual detection toward HCHO is evaluated in a 3 m³ test chamber, confirming the practicability and reliability of the InAG sensor. This work provides an effective strategy for the development of low-power-consumption ppb-level gas sensors.

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It is a great challenge to develop efficient room-temperature sensing materials and sensors for nitric oxide (NO) gas, which is a biomarker molecule used in the monitoring of inflammatory respiratory diseases. Herein, Hemin (Fe (III)-protoporphyrin IX) is introduced into the nitrogen-doped reduced graphene oxide (N-rGO) to obtain a novel sensing material HNG-ethanol. Detailed XPS spectra and DFT calculations confirm the formation of carbon–iron bonds in HNG-ethanol during synthesis process, which act as electron transport channels from graphene to Hemin. Owing to this unique chemical structure, HNG-ethanol exhibits superior gas sensing properties toward NO gas (R_a/R_g = 3.05, 20 ppm) with a practical limit of detection (LOD) of 500 ppb and reliable repeatability (over 5 cycles). The HNG-ethanol sensor also possesses high selectivity against other exhaled gases, high humidity resistance, and stability (less than 3% decrease over 30 days). In addition, a deep understanding of the gas sensing mechanisms is proposed for the first time in this work, which is instructive to the community for fabricating sensing materials based on graphene-iron derivatives in the future.

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Graphene foams are promising three-dimensional (3D) architectures with the combination of the intrinsic nature of graphene and unique cellular structures for various realms. Herein, a facile technique is developed by combining supramolecular assembly with lyophilization to functionalize graphene with donor−π-acceptor (D−π-A) molecules and then massively transform the two-dimensional (2D) plane nanosheets into 3D foams. The as-prepared gas sensors work at room temperature (RT) and reveal comprehensive gas sensing performance with an ultrahigh response (R _a/R _g = 3.2, 10 ppm), excellent selectivity, and reliable repeatability toward NO ₂. Notably, a gas sensing enhancement mechanism with density functional theory (DFT) calculations is proposed to unravel the synergetic effect of the “Greater Electron Transferring Area” and the specific 3D foam structure for the enhancement of charge transfer and NO ₂ adsorption. The combination of supramolecular assembly and the lyophilization technique provides a strategy to prepare 3D architectural graphene-based materials for high-performance gas sensors and chemical trace detectors.

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The magnitude of leakage in the dam body and its foundation can be used as an important indicator in dam risk management. This study presents a data mining and monitoring framework for safety control of the dam leakage flow. First, the influencing factors in dam leakage flow are investigated. Second, a kernel extreme learning machine (KELM) is trained to predict dam leakage, where the parameters are optimized adaptively by parallel multi-population Jaya algorithm. Finally, a novel global sensitivity analysis is proposed to evaluate the relative importance of each input variable based on the KELM. Monitoring data of leakage flow from the concrete face rockfill dam in a pumped-storage power station is used for modeling and verification. The simulated results of the case study reveal that KELM achieves a satisfactory prediction of the leakage flow. It is also found that the water level fluctuation and rainfall have a significant impact on leakage magnitude. The sensitivity analysis provides a useful qualitative metric of dam leakage, which is of great value for dam safety monitoring and operation.

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Recent progress of quantum simulators provides insight into the fundamental problems of strongly correlated systems. To adequately assess the accuracy of these simulators, the precise modeling of the many-body physics, with accurate model parameters, is crucially important. In this paper, we employed an ab initio exact diagonalization framework to compute the correlated physics of a few electrons in artificial potentials. We apply this approach to a quantum-dot system and study the magnetism of the correlated electrons, obtaining good agreement with recent experimental measurements in a plaquette. Through control of dot potentials and separation, including geometric manipulation of tunneling, we examine the Nagaoka transition and determine the robustness of the ferromagnetic state. While the Nagaoka theorem considers only a single-band Hubbard model, in this work we perform extensive ab initio calculations that include realistic multiorbital conditions in which the level splitting is smaller than the interactions. This simulation complements the experiments and provides insight into the formation of ferromagnetism in correlated systems. More generally, our calculation sets the stage for further theoretical analysis of analog quantum simulators at a quantitative level.

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The focus of this paper is on the estimation of optical turbulence (commonly characterized by C2n) near the land-surface using routinely measured meteorological variables (e.g., temperature, wind speed). We demonstrate that an artificial neural network-based approach has the potential to be effectively utilized for this purpose. We use an extensive scintillometer-based C2n dataset from a recent field experiment in Texas, USA to evaluate the accuracy of the proposed approach.@en