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Functionalized and oxidized silicon nanosheets: Customized design for enhanced sensitivity towards relative humidity
摘要： The use of completely oxidized two-dimensional (2D) silicon nanosheets (SiNSs) represents a novel approach for the application of 2D silicon-based materials in the nanoelectronics field. Densely stacked and highly porous oxidized SiNSs (OSiNSs) act as a sensitive layer for humidity detection. Due to the oxidation-caused porosity of the SiNSs and the possibility functionalize the 2D surface with hydrophilic groups, this hybrid material exhibits an extremely good sensitivity towards relative humidity (RH). In this work, precise tuning of the SiNSs’ sensing properties by their functionalization is demonstrated. In particular, the modification with methacrylic acid (MAA) groups, leading to SiNS-MAA, and the subsequent deposition on interdigitated electrodes double the capacitance value in the range of 20-85%RH. These values were achieved after the full oxidation of SiNS-MAA in ambient conditions. The mentioned changes in capacitance are extremely high compared to the response of the so far known common polymer humidity sensors. Contrary to that, this response is neutralized when the SiNSs are functionalized with tert-butyl acrylic acid (tBMA), a rather hydrophobic functional group. The fabricated devices show, how the specific functionalization of SiNSs serves as a reliable tool to provide sensitivity towards RH. Similar approach, based on tuning the functionality, can be applied to achieve e.g., sensor array selectivity. For this purpose, the functional groups on the surface of the nanomaterial can be further modified. Additional molecules with sensitivities towards various surrounding conditions could be attached. Furthermore, these functional molecules can be used for subsequent (bio)molecule immobilization, which can serve as sensitive molecular groups towards surrounding substrates and gases. However, one of the main challenges in sensor technology is to find a highly selective solution: a sensor system capable to differentiate among different vapor species. The described strategy can serve as an access towards new and promising solutions, which can help to face this issue in modern nanomaterials-based technology.
关键词： two-dimensional materials,porous silicon,functionalization,silicon nanosheets,hybrid systems,moisture content
更新于2025-11-21 11:20:48
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Diode Array Near Infrared Spectrometer Calibrations for Composition Analysis of Single Plant Canola (Brassica napus) Seed
摘要： A canola breeder needs an accurate, rapid, non-destructive method for analyzing seeds from a single plant to select the most promising samples for further breeding trials. Near Infrared Spectroscopy (NIRS) is widely used for quantitative analysis of oilseeds in a non-destructive manner. This research was aimed at developing NIRS calibration models for single plant canola seed using a diode array NIRS (950-1650 nm wavelength range), multivariate prediction models, and a mirrored sample cup. Eighteen different NIRS calibration models were developed using 100 samples for each constituent with different pre-processing techniques (mean center, derivatives, variates) and models (PLS, PCR). The relative performance of different calibration models for each constituent was compared using R2, SEP, and ratio performance deviation (RPD) values obtained from the validation set of 30 samples. NIRS models developed using the PLS regression algorithm for moisture content (R2 = 0.97, SEP = 0.32, RPD = 6.13) and oil content (R2 = 0.84, SEP = 0.61, RPD = 4.16) were successful. However, acceptable NIRS models were not obtained for fatty acid and glucosinolates content likely due to limited variability and low levels of the constituent and a narrow wavelength range of the DA-NIR instrument.
关键词： Moisture content,Diode array,Fatty acid composition,Mirrored cup,DA-NIRS,Oil content,Oleic acid,Stearic acid,NIRS calibration model,Palmitic acid
更新于2025-09-23 15:23:52
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Visual detection of the moisture content of tea leaves with hyperspectral imaging technology
摘要： Hitherto, the rapid and nondestructive determination of the moisture content of tea leaves is still an unresolved issue because the upward facing surfaces of tea leaves lying on a conveyor belt are randomly chosen by the collapse of the leaves onto their front side or back side. To study the above issue, hyperspectral images of both the front side and back side of tea leaves on a conveyor belt were captured in the lab to simulate a practical production environment, and LS-SVR models with Rv2 values of 0.951 and 0.918 for the front side and back side, respectively, were established based on their characteristic spectral bands. To ensure that the spectrum of each pixel can be correctly imported into its corresponding model, a logistic regression classifier with a correct classification rate of 100 % was designed to identify the front side and back side of the leaves. Finally, a distribution map of the moisture content of the tea leaves was generated successfully according to the following steps: (1) Extracting the average spectrum of each leaf; (2) Identifying which side of the leaf the spectrum belongs to; (3) Importing the adjusted spectrum of each pixel into its corresponding regression model; and (4) Generating a distribution map of the moisture content. This research creatively provides a scheme for detecting the moisture content of tea leaves.
关键词： moisture content,front side,hyperspectral imaging,tea leaf,back side
更新于2025-09-23 15:23:52
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Rapid, non-destructive determination of ginseng seed moisture content by near infrared spectroscopy technology
摘要： Ginseng seed moisture content (SMC) determination and monitoring are of great importance during seed storage and in trading. The traditional oven-drying method for SMC measurement is accurate but takes both time and labour. The objective of this study was to develop a rapid and non-destructive method for ginseng SMC determination using near infrared (NIR) spectroscopy. Eighteen freshly harvested seed lots stored for different periods (days) were used for NIR model development and 12 commercial seed lots were used for validation of the model. The model developed in the present work had an R2 of 0.9913, residual prediction deviation (RPD) of 11.3 and low root mean square errors assessed by cross-validation (RMSECV; 0.387%). For commercial seed lot measurement, the predicted values of SMC were nearly the same as measured ones, with the relative differences less than 2.96%. In conclusion, NIR spectroscopy suitable for rapid and nondestructive determination of ginseng SMC.
关键词： near infrared spectroscopy,seed moisture content,ginseng
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Evaluation of the Vegetation Optical Depth Index on Monitoring Fire Risk in the Mediterranean Region
摘要： Monitoring live fuel moisture content (LFMC) in Mediterranean area is of great importance for fire risk assessment. LFMC has extensively been estimated based on optical remote sensing data. But the latter can be affected by atmospheric effects. As a complementary data source, microwave data can be used as they are relatively insensitive to atmospheric effects. Yet further evaluations are needed to investigate the potential of microwave observations to monitor LFMC. In this study, we assess the capability of long-term microwave vegetation optical depth (VOD) to capture the temporal variability of in situ measured LFMC in 14 Mediterranean shrub species in southern France during 1996-2014. Microwave-derived VOD at X band (VODX-15) displayed a high sensitivity to LFMC with correlation coefficients of 0.56. Similar evaluations were made using four optical indices computed from the Moderate Resolution Imaging Spectrometer (MODIS) data including normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), visible atmospheric resistant index (VARI), normalized difference water index (NDWI). The comparisons showed that VARI performs better than VODX-15 and other optical indices with highest median of correlation coefficients of 0.65. Overall, this study shows that passive microwave-derived VOD, are efficient proxies for LFMC of Mediterranean shrub species and could be used along with optical indices to evaluate fire risks in the Mediterranean region.
关键词： vegetation optical depth,fire risk,microwave remote sensing,live fuel moisture content
更新于2025-09-23 15:21:21
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Influence of soil texture on the estimation of bare soil moisture content using MODIS images
摘要： Spectral behaviour of soil is strongly influenced by the soil texture as well as its nutrient content. Many attempts have so far been made to assess the soil moisture using soil reflectance in different bands of satellite images. In this paper, the investigations showed that the coarse texture soils did not show a profound relationship with the reflectance values that was in part due to its weak water storage capacity. Fine texture soils, on the contrary, showed better results which could be attributed to their higher water storage capacity and the capillary phenomenon. Finally, a linear regression model made of a combination of Land Surface Temperature (LST), Normalized Difference Water Index (NDWI) and Visible and Short-wave infrared Drought Index (VSDI) indices was proposed. The suggested method has improved the accuracy of the soil moisture content estimation up to 1% in general and the medium texture soil in particular. The results were compared with the performance of seven conventional soil moisture estimators method all using the Moderate Resolution Imaging Spectroradiometer (MODIS) data.
关键词： Soil moisture content,MODIS,soil texture,US-SCAN
更新于2025-09-23 15:21:01
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Determination of Drying Patterns of Radish Slabs under Different Drying Methods Using Hyperspectral Imaging Coupled with Multivariate Analysis
摘要： Drying kinetics and the moisture distribution map of radish slabs under different drying methods (hot-air drying (HAD), microwave drying (MD), and hot-air and microwave combination drying (HMCD)) were determined and visualized by hyperspectral image (HSI) processing coupled with a partial least square regression (PLSR)-variable importance in projection (VIP) model, respectively. Page model was the most suitable in describing the experimental moisture loss data of radish slabs regardless of the drying method. Dielectric properties (DP, ε) of radish slices decreased with the decrease in moisture content (MC) during MD, and the penetration depth of microwaves in radish was between 0.81 and 1.15 cm. The PLSR-VIP model developed with 38 optimal variables could result in the high prediction accuracies for both the calibration (R2 = 0.967 and RMSEC = 4.32%) and validation (R2 = 0.962 and RMSEC = 4.45%). In visualized drying patterns, the radish slabs dried by HAD had a higher moisture content at the center than at the edges; however, the samples dried by MD contained higher moisture content at the edges. The nearly uniform drying pattern of radish slabs under HMCD was observed in hyperspectral images. Drying uniformity of radish slabs could be improved by the combination drying method, which significantly reduces drying time.
关键词： multivariate analysis,moisture content,drying pattern,hyperspectral imaging,radish
更新于2025-09-23 15:19:57
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In-line near infrared spectroscopy for the prediction of moisture content in the tapioca starch drying process
摘要： Moisture content is an important parameter measured in tapioca starch production as this parameter has been shown to correlate strongly with the quality of the ?nished product. However, there is currently no in-line sensor which can be used to directly measure the moisture content of the product in real time. The objective of the present work was to study the use of an in-line measurement which can be introduced at the end of the drying process for tapioca starch moisture content evaluation. Either in-line NIR data or at-line NIR data was used to develop the necessary calibration models for evaluating the moisture content. Furthermore, calibration models were also developed by pooling the in-line and at-line data. Its performance was then veri?ed using additional in-line data. The NIR model developed using 100% of the at-line data and 50% of the in-line data was validated using the unused 50% of the inline data. This model was shown to provide better performance in moisture content prediction with an SEP of 0.61% and a bias of 0.001%. In addition, the results showed that the at-line spectrum can also be used for the calibration model development to predict the moisture content of the samples scanned by an in-line spectrometer. However, the in-line spectrometer installation on a pneumatic conveying circular tube where tapioca starch and air mixed was found to be complicated due to signi?cant vibration. This caused additional variation in the data with time. Therefore, it is concluded that the most suitable place for installing a spectrometer would be at a position involving a low pressure, or where the stream ?ow of a product is steadier in order to avoid the dynamic mixing of the product within the drying tube affecting the uncertainty of NIR scattering during the measurement.
关键词： Moisture content,Tapioca starch,Drying process,In-line near infrared spectroscopy
更新于2025-09-19 17:15:36
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Contribution of cellulosic fibre filter on atmosphere moisture content in laser powder bed fusion additive manufacturing
摘要： Cellulosic materials are commonly used to manufacture the particulate filters used in laser powder bed fusion (LpBf) additive manufacturing (AM) equipment. An experimental approach has been used to calculate the moisture quantity and kinetics of sorption in a cellulosic filter at varying relative humidity (RH) levels. A prediction of the amount of moisture which can be theoretically held within a filter during storage before its use has been obtained. Subsequently, the quantity and the rate of moisture desorption which can be transferred into the build chamber during LpBf is presented. this work highlights the importance of filter storage and conditioning prior to use in additive manufacturing processing.
关键词： laser powder bed fusion,cellulosic fibre filter,atmosphere moisture content,additive manufacturing
更新于2025-09-19 17:13:59
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Detection of moisture content in peanut kernels using hyperspectral imaging technology coupled with chemometrics
摘要： Hyperspectral imaging technology at 416–1000 nm was investigated to detect moisture content in peanut kernels. Four varieties of peanuts were scanned using a “push-broom” system to acquire hyperspectral images. In this study, three models including partial least squares regression (PLSR), principal component regression (PCR), and support vector machine regression (SVR) were established to detect moisture content in peanut kernels based on full wavelengths. The performance of SVR was the best with determination coefficient (R2) of .9432, root mean square errors (RMSE) of 0.7054%, and residual prediction deviation (RPD) of 3.9694 for prediction set. In order to simplify modeling process and improve calculation speed of the models, successive projections algorithm (SPA) and regression coefficient were applied for optimal wavelengths selection. Then, PCR, PLSR, and SVR models were established based on these selected wavelengths, respectively. As a result, SPA–SVR generated a satisfied effect with R2 of .9363, RMSE of 0.7021%, and RPD of 3.988 for prediction set. All results in this study indicated that the combination of chemometrics and hyperspectral imaging technology could achieve rapid and nondestructive detection of moisture content in peanut kernels.
关键词： moisture content,nondestructive detection,peanut kernels,chemometrics,hyperspectral imaging technology
更新于2025-09-19 17:13:59