scholarly journals Recent Advances and Applications of Semiconductor Photocatalytic Technology

2019 ◽  
Vol 9 (12) ◽  
pp. 2489 ◽  
Author(s):  
Fubao Zhang ◽  
Xianming Wang ◽  
Haonan Liu ◽  
Chunli Liu ◽  
Yong Wan ◽  
...  

Along with the development of industry and the improvement of people’s living standards, peoples’ demand on resources has greatly increased, causing energy crises and environmental pollution. In recent years, photocatalytic technology has shown great potential as a low-cost, environmentally-friendly, and sustainable technology, and it has become a hot research topic. However, current photocatalytic technology cannot meet industrial requirements. The biggest challenge in the industrialization of photocatalyst technology is the development of an ideal photocatalyst, which should possess four features, including a high photocatalytic efficiency, a large specific surface area, a full utilization of sunlight, and recyclability. In this review, starting from the photocatalytic reaction mechanism and the preparation of the photocatalyst, we review the classification of current photocatalysts and the methods for improving photocatalytic performance; we also further discuss the potential industrial usage of photocatalytic technology. This review also aims to provide basic and comprehensive information on the industrialization of photocatalysis technology.

2020 ◽  
pp. 1557-1579
Author(s):  
Nassima Bouadem ◽  
Rahim Kacimi ◽  
Abdelkamel Tari

Wireless Sensor Networks (WSNs) became omnipresent in our daily life. As a result, they have emerged as a fruitful research topic, because of their advantages, especially their low cost and easy deployment. However, these attractive merits imply that available resources, especially energy, in each sensor node have to be wisely used through different network dynamics. Beside other techniques, duty-cycling (DC) is the first widely used one to save energy in WSNs. However, due to the continuous changes, mainly in the energy availability, the nodes have to operate in a very low DC which is a required strategy in many applications in order to keep the network operational. This article presents a detailed survey that provides an interesting view of different DC schemes which are proposed to tackle the specific WSN challenges, and it also gives a novel classification of DC schemes that includes the most recent techniques. The last part aims to investigate the impact of the low DC on both the network and the application layer.


Author(s):  
Nassima Bouadem ◽  
Rahim Kacimi ◽  
Abdelkamel Tari

Wireless Sensor Networks (WSNs) became omnipresent in our daily life. As a result, they have emerged as a fruitful research topic, because of their advantages, especially their low cost and easy deployment. However, these attractive merits imply that available resources, especially energy, in each sensor node have to be wisely used through different network dynamics. Beside other techniques, duty-cycling (DC) is the first widely used one to save energy in WSNs. However, due to the continuous changes, mainly in the energy availability, the nodes have to operate in a very low DC which is a required strategy in many applications in order to keep the network operational. This article presents a detailed survey that provides an interesting view of different DC schemes which are proposed to tackle the specific WSN challenges, and it also gives a novel classification of DC schemes that includes the most recent techniques. The last part aims to investigate the impact of the low DC on both the network and the application layer.


Author(s):  
Yanwen Wang ◽  
Rong Liang ◽  
Chao Qin ◽  
Lei Ren ◽  
Zhizhen Ye ◽  
...  

Antimony sulfide (Sb2S3) is a light absorbing material with strong visible light response, which is suitable for efficient and low-cost photoelectrodes. Nano-structured films have unique advantages in constructing photoelectrodes due...


2021 ◽  
Vol 14 (5) ◽  
pp. 440
Author(s):  
Eirini Siozou ◽  
Vasilios Sakkas ◽  
Nikolaos Kourkoumelis

A new methodology, based on Fourier transform infrared spectroscopy equipped with an attenuated total reflectance accessory (ATR FT-IR), was developed for the determination of diclofenac sodium (DS) in dispersed commercially available tablets using chemometric tools such as partial least squares (PLS) coupled with discriminant analysis (PLS-DA). The results of PLS-DA depicted a perfect classification of the tablets into three different groups based on their DS concentrations, while the developed model with PLS had a sufficiently low root mean square error (RMSE) for the prediction of the samples’ concentration (~5%) and therefore can be practically used for any tablet with an unknown concentration of DS. Comparison with ultraviolet/visible (UV/Vis) spectrophotometry as the reference method revealed no significant difference between the two methods. The proposed methodology exhibited satisfactory results in terms of both accuracy and precision while being rapid, simple and of low cost.


Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 56
Author(s):  
Martina Miloloža ◽  
Dajana Kučić Grgić ◽  
Tomislav Bolanča ◽  
Šime Ukić ◽  
Matija Cvetnić ◽  
...  

High living standards and a comfortable modern way of life are related to an increased usage of various plastic products, yielding eventually the generation of an increased amount of plastic debris in the environment. A special concern is on microplastics (MPs), recently classified as contaminants of emerging concern (CECs). This review focuses on MPs’ adverse effects on the environment based on their bioactivity. Hence, the main topic covered is MPs’ ecotoxicity on various aquatic (micro)organisms such as bacteria, algae, daphnids, and fish. The cumulative toxic effects caused by MPs and adsorbed organic/inorganic pollutants are presented and critically discussed. Since MPs’ bioactivity, including ecotoxicity, is strongly influenced by their properties (e.g., types, size, shapes), the most common classification of MPs types present in freshwater are provided, along with their main characteristics. The review includes also the sources of MPs discharge in the environment and the currently available characterization methods for monitoring MPs, including identification and quantification, to obtain a broader insight into the complex problem caused by the presence of MPs in the environment.


Chemosensors ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 149
Author(s):  
André Olean-Oliveira ◽  
Gilberto A. Oliveira Brito ◽  
Celso Xavier Cardoso ◽  
Marcos F. S. Teixeira

The use of graphene and its derivatives in the development of electrochemical sensors has been growing in recent decades. Part of this success is due to the excellent characteristics of such materials, such as good electrical and mechanical properties and a large specific surface area. The formation of composites and nanocomposites with these two materials leads to better sensing performance compared to pure graphene and conductive polymers. The increased large specific surface area of the nanocomposites and the synergistic effect between graphene and conducting polymers is responsible for this interesting result. The most widely used methodologies for the synthesis of these materials are still based on chemical routes. However, electrochemical routes have emerged and are gaining space, affording advantages such as low cost and the promising possibility of modulation of the structural characteristics of composites. As a result, application in sensor devices can lead to increased sensitivity and decreased analysis cost. Thus, this review presents the main aspects for the construction of nanomaterials based on graphene oxide and conducting polymers, as well as the recent efforts made to apply this methodology in the development of sensors and biosensors.


Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.


2021 ◽  
pp. 108199
Author(s):  
Pau Arce ◽  
David Salvo ◽  
Gema Piñero ◽  
Alberto Gonzalez

Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.


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