•This article reports for the first time the percolation effect of rGO on the ammonia sensing properties of rGO-SnO2 composite.•The sensor using rGO-SnO2 composites exhibited a switch from an n-type ...semiconductor response behavior to a p-type semiconductor behavior as the rGO content increased from 0.1wt% to 1wt%.•A physical model for prediction of the critical weight ratio of rGO in the composite was developed. The calculated result was reasonably consistent with the experimental one.
Reduced graphene oxide (rGO) was added to SnO2 to implement a room temperature chemoresistive ammonia sensor. The percolation effect of rGO on the ammonia sensing properties of SnO2 based sensor was observed. rGO was added physically to SnO2 followed with a magnetic stirring. The sensor using rGO-SnO2 composites exhibited a switch from an n-type semiconductor response behavior to a p-type semiconductor behavior as the rGO content increased from 0.1wt% to 1wt%. The p-type response to ammonia indicated an enhanced sensitivity, better signal stability and faster response/recovery speeds compared to the n-type response. The p-type response can be due to the p-type rGO in the composite and the enhanced room temperature n-type response of SnO2 could be assisted by the added rGO which facilitated the redox reactions of ammonia with oxygen in air. A physical model for prediction of the critical weight ratio of rGO in the composite was developed. The calculated results were reasonably consistent with the experimental ones.
Purpose
To build and validate a radiomics nomogram integrated with the radiomics signature and subjective CT characteristics to predict the Ki-67 expression level of gastrointestinal stromal tumors ...(GISTs). Moreover, the purpose was to compare the performance of pathological Ki-67 expression level with predicted Ki-67 expression level in estimating the prognosis of GISTs patients.
Methods
According to pathological results, patients were classified into high-Ki-67 labeling index group (Ki-67 LI ≥ 5%) and low-Ki-67 LI group (Ki-67 LI < 5%). Radiomics features extracted from contrast-enhanced CT(CECT) images were selected and classified to build a radiomics signature. A combined model was built by incorporating radiomics signature and determinant subjective CT characteristics using multivariate logistic regression analysis. The diagnostic performance of the radiomics signature, subjective CT model and combined model were explored by receiver operating characteristic (ROC) curve analysis and Delong test. The model with best diagnostic performance was then set up for the prediction nomogram. Recurrence-free survival (RFS) rates were compared utilizing Kaplan–Meier curve.
Results
The generated combined model yielded the best diagnostic performance with area under the curve (AUC) values of 0.738 95% confidence interval (CI): 0.669–0.807 and 0.772 (95% CI 0.683–0.860) in the training set and testing set respectively. The nomogram based on the combined model demonstrated good calibration in the training set and testing set (both
P
> 0.05). Patients of high-Ki-67 LI group predicted by our nomogram had a poorer RFS than patients of low–Ki-67 LI group (
P
< 0.0001).
Conclusion
This radiomics nomogram based on CECT had a satisfactory performance in predicting both the Ki-67 expression level and prognosis noninvasively in patients with GISTs, which may serve as an effective imaging tool that can assist in guiding personalized clinical treatment.
Au modified TiO2/In2O3 hollow nanospheres were synthesized by the hydrolysis method using the carbon nanospheres as a sacrificial template. Compared to pure In2O3, pure TiO2, and TiO2/In2O3 based ...sensors, the Au/TiO2/In2O3 nanosphere-based chemiresistive-type sensor exhibited excellent sensing performances to formaldehyde at room temperature under ultraviolet light (UV-LED) activation. The response of the Au/TiO2/In2O3 nanocomposite-based sensor to 1 ppm formaldehyde was about 5.6, which is higher than that of In2O3 (1.6), TiO2 (2.1), and TiO2/In2O3 (3.8). The response time and recovery time of the Au/TiO2/In2O3 nanocomposite sensor were 18 s and 42 s, respectively. The detectable formaldehyde concentration could go down as low as 60 ppb. In situ diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) was used to analyze the chemical reactions on the surface of the sensor activated by UV light. The improvement in the sensing properties of the Au/TiO2/In2O3 nanocomposites could be attributed to the nanoheterojunctions and electronic/chemical sensitization of the Au nanoparticles.
Research has been conducted on solid oxide fuel cells (SOFCs) for their fuel flexibility, modularity, high efficiency, and power density. However, the high working temperature leads to the ...deterioration of materials and increased operating costs. Considering the high protonic conductivity and low activation energy, the proton conducting SOFC, i.e., the protonic ceramic fuel cell (PCFC), working at a low temperature, has been wildly investigated. The PCFC is a promising state-of-the-art electrochemical energy conversion system for ecological energy; it is characterized by near zero carbon emissions and high efficiency, and it is environment-friendly. The PCFC can be applied for the direct conversion of various renewable fuels into electricity at intermediate temperatures (400–650 °C). The construction of the PCFC directly affect its properties; therefore, manufacturing technology is the crucial factor that determines the performance. As a thinner electrolyte layer will lead to a lower polarization resistance, a uniformly constructed and crack-free layer which can perfectly bond to electrodes with a large effective area is challenging to achieve. In this work, different fabrication methods are investigated, and their effect on the overall performance of PCFCs is evaluated. This article reviews the recent preparation methods of PCFCs, including common methods, 3D printing methods, and other advanced methods, with summarized respective features, and their testing and characterization results.
Accurate modeling of threshold voltage is necessary in the integrated circuit design of strained silicon devices. Thoroughly researching the factors that affect threshold voltage and establishing a ...more precise threshold voltage model, can provide essential theoretical support for integrated circuit design. By solving a Poisson equation, in this paper, we demonstrate a comprehensive physical model for the threshold voltage of strained Si NMOSFETs using the gradual channel approximation theory and a quasi-two-dimensional analysis. The model investigates the physical effects such as short-channel, narrow-channel, non-uniform doping, and drain-induced barrier lowering effects on the threshold voltage. After substituting the extracted parameters into the model, a comparison was made with experimental results to validate the accuracy and correctness of the established model. Additionally, variations in the tunneling current of small-sized devices were studied. The two models provide essential references for the analysis and design of strained Si large-scale integrated circuits.
In practical applications, the hydrophone array has element position errors, which seriously degrade the performance of the direction of arrival estimation. We propose a direction of arrival (DOA) ...estimation method based on sparse Bayesian learning using existing array position errors to solve this problem. The array position error and angle grid error parameters are introduced, and the prior distribution of these two errors is determined. The joint probability density distribution function is established by means of a sparse Bayesian learning model. At the same time, the unknown parameters are optimized and iterated using the expectation maximum algorithm and the corresponding parameters are solved to obtain the spatial spectrum. The results of the simulation and the lake experiments show that the proposed method effectively overcomes the problem of array element position errors and has strong robustness. It shows a good performance in terms of its estimation accuracy, meaning that the resolution ability can be greatly improved in the case of a low signal-to-noise ratio or small number of snapshots.
In this work, MXene/NiO-composite-based formaldehyde (HCHO) sensing materials were successfully synthesized by an in situ precipitation method. The heterostructures between the MXene and NiO ...nanoparticles were verified by transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The HCHO sensing performance of the MXene/NiO-based chemiresistive-type sensors was investigated. Compared to pure MXene and NiO materials, the sensing performance of the MXene/NiO-P2-based sensor to HCHO gas at room temperature was significantly enhanced by the formation of MXene/NiO heterojunctions. The response of the MXene/NiO-P2 sensor to 50 ppm HCHO gas was 8.8, which was much higher than that of the pure MXene and NiO. At room temperature, the detectable HCHO concentration of the MXene/NiO-P2-based sensor was 1 ppm, and the response and recovery time to 2 ppm HCHO was 279 s and 346 s, respectively. The MXene/NiO-P2 sensor also exhibited a good selectivity and a long-term stability to HCHO gas for 56 days. The in situ Fourier transform infrared (FTIR) spectra of the MXene/NiO-P2 sensor, when exposed to HCHO gas at different times, were investigated to verify the adsorption reaction products of HCHO molecules.
Graphene‐based heterostructure composite is a new type of advanced sensing material that includes composites of graphene with noble metals/metal oxides/metal sulfides/polymers and organic ligands. ...Exerting the synergistic effect of graphene and noble metals/metal oxides/metal sulfides/polymers and organic ligands is a new way to design advanced gas sensors for nitrogen‐containing gas species including NH3 and NO2 to solve the problems such as poor stability, high working temperature, poor recovery, and poor selectivity. Different fabrication methods of graphene‐based heterostructure composite are extensively studied, enabling massive progress in developing chemiresistive‐type sensors for detecting the nitrogen‐containing gas species. With the components of noble metals/metal oxides/metal sulfides/polymers and organic ligands which are composited with graphene, each material has its attractive and unique electrical properties. Consequently, the corresponding composite formed with graphene has different sensing characteristics. Furthermore, working ambient gas and response type can affect gas‐sensitive characteristic parameters of graphene‐based heterostructure composite sensing materials. Moreover, it requires particular attention in studying gas sensing mechanism of graphene‐based heterostructure composite sensing materials for nitrogen‐containing gas species. This review focuses on related scientific issues such as material synthesis methods, sensing performance, and gas sensing mechanism to discuss the technical challenges and several perspectives.
This review focuses on related scientific issues such as the material synthesis methods, sensing performance, and gas sensing mechanism of graphene based heterostructure composite sensing materials for application of nitrogen‐containing gas (NH3/NO2) sensors to discuss the technical challenges and several perspectives.
The reduced graphene oxide (rGO) encapsulated Co3O4 nanocrystals were fabricated by using the electrospinning technology. The sample shows nanofiber morphology and the Co3O4 nanocrystals were wrapped ...by rGO thin layers. The as-electrospun rGO–Co3O4 nanofibers based chemoresistive sensor exhibited a p-type semiconductor behavior in ambient conditions and showed an excellent sensitivity with a fast response and recovery to different concentrations of ammonia from 5 to 100ppm at room temperature. The sensor displays selectivity to several potential interferrents such as methanol, ethanol, formaldehyde, acetone, benzene, and methylbenzene. It may be attributed to the unique hierarchical wrapping microstructure and the selective NH3 adsorption at both the wrapping layer of rGO and the polarized CCo3+ covalent centers within the nanofibers.
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•The generation of C-Co coupling with Co3O4 (110B) at a specific Cooct site which enhances NH3 adsorption is related to graphene defects, which provides a way and theoretical basis ...for introduction of C-Co coupling by controlling graphene defects.•C-Co coupling promotes the dissociative adsorption of pre-adsorbed O2 or H2O and thus the formation of oxygen-containing functional groups which produces an enhancement in stability of NH3 adsorption.•Charge transfer amount in the NH3 adsorption process is enhanced by C-Co coupling effect, C atoms from graphene, lattice oxygen from Co3O4 and pre-adsorbed O2 or H2O which is instructive for the catalytic site in detection or treatment of NH3.
The model of Co3O4 (110B)/defective graphene surface to adsorb NH3 is established. DFT calculation is conducted to study the effects of the defective graphene, Co3O4 (110B) and their coupling effect on adsorption for NH3 and the joint effects of pre-adsorbed O2/H2O on the model. The calculation results reveal the generation of C-Co coupling with Co3O4 (110B) at a specific Cooct site which enhances NH3 adsorption is related to graphene defects. Besides, C-Co coupling promotes the dissociative adsorption of pre-adsorbed O2 or H2O at Cooct site with C-Co and thus the formation of oxygen-containing functional groups such as C = O and C-OH group which produces an enhancement in stability of NH3 adsorption. Charge transfer amount in the NH3 adsorption process is enhanced by C-Co coupling effect, C atoms from graphene, lattice oxygen from Co3O4 and pre-adsorbed O2 or H2O. This work gives a better understand of influence factors of NH3 adsorption on Co3O4/graphene composite which is important for its catalytic reaction. It provides a theoretical basis for controlling catalytic reaction in NH3 treatment or sensing process.
