Hasil untuk "Chemical technology"

R. Sheldon

Deep Jariwala, V. Sangwan, L. Lauhon et al.

In the last three decades, zero-dimensional, one-dimensional, and two-dimensional carbon nanomaterials (i.e., fullerenes, carbon nanotubes, and graphene, respectively) have attracted significant attention from the scientific community due to their unique electronic, optical, thermal, mechanical, and chemical properties. While early work showed that these properties could enable high performance in selected applications, issues surrounding structural inhomogeneity and imprecise assembly have impeded robust and reliable implementation of carbon nanomaterials in widespread technologies. However, with recent advances in synthesis, sorting, and assembly techniques, carbon nanomaterials are experiencing renewed interest as the basis of numerous scalable technologies. Here, we present an extensive review of carbon nanomaterials in electronic, optoelectronic, photovoltaic, and sensing devices with a particular focus on the latest examples based on the highest purity samples. Specific attention is devoted to each class of carbon nanomaterial, thereby allowing comparative analysis of the suitability of fullerenes, carbon nanotubes, and graphene for each application area. In this manner, this article will provide guidance to future application developers and also articulate the remaining research challenges confronting this field.

D. Huh, G. Hamilton, D. Ingber

D. Rajak, Durgesh Devchand Pagar, Ravinder Kumar et al.

Abstract Emerged in the middle of 20th century, composite materials are now one of the hotspot research topics in the modern technology. Their promising characteristics make them suitable for enormous applications in industrial field such as aerospace, automotive, construction, sports, bio-medical and many others. These materials reveal remarkable structural and mechanical properties such as high strength to weight ratio, resistance to chemicals, fire, corrosion and wear; being economical to manufacture. Herein, an overview of composite materials, their characterization, classification and main advantages linked to physical and mechanical properties based on the recent studies are presented. There, were presented the conventional manufacturing techniques of composite and their applications. It was highlighted the tremendous need to discovery new generation of composites that should incorporate the synthetic or natural materials by implementing new efficient manufacturing processes. In the combination of matrix and reinforcement materials, the use of natural materials as constituent are compulsory in order to obtain a complete material degradable as environmentally friendly.

J. Barber

Hongqun Yang, Zhenghe Xu, M. Fan et al.

Gonzalo Prieto, H. Tüysüz, Nicolas Duyckaerts et al.

R. Porta, M. Benaglia, A. Puglisi

Shao-En Ong, M. Mann

F. Hasan, A. Shah, A. Hameed

L. Vaisman, H. Wagner, G. Marom

C. Dimitrakopoulos, P. Malenfant

I. Tetko, J. Gasteiger, R. Todeschini et al.

Shikha Dahiya, A. N. Kumar, J. Shanthi Sravan et al.

E. Alper, O. Y. Orhan

Abstract Carbon dioxide capture, utilization and storage (CCUS) –including conversion to valuable chemicals-is a challenging contemporary issue having multi-facets. The prospect to utilize carbon dioxide (CO2) as a feedstock for synthetic applications in chemical and fuel industries -through carboxylation and reduction reactions-is the subject of this review. Current statute of the heterogeneously catalyzed hydrogenation, as well as the photocatalytic and electrocatalytic activations of conversion of CO2 to value-added chemicals is overviewed. Envisaging CO2 as a viable alternative to natural gas and oil as carbon resource for the chemical supply chain, three stages of development; namely, (i) existing mature technologies (such as urea production), (ii) emerging technologies (such as formic acid or other single carbon (C1) chemicals manufacture) and (iii) innovative explorations (such as electrocatalytic ethylene production) have been identified and highlighted. A unique aspect of this review is the exploitations of reactions of CO2 –which stems from existing petrochemical plants-with the commodity petrochemicals (such as, methanol, ethylene and ethylene oxide) produced at the same or nearby complex in order to obtain value-added products while contributing also to CO2 fixation simultaneously. Exemplifying worldwide ethylene oxide facilities, it is recognized that they produce about 3 million tons of CO2 annually. Such a CO2 resource, which is already separated in pure form as a requirement of the process, should best be converted to a value-added chemical there avoiding current practice of discharging to the atmosphere. The potential utilization of CO2, captured at power plants, should also been taken into consideration for sustainability. This CO2 source, which is potentially a raw material for the chemical industry, will be available at sufficient quality and at gigantic quantity upon realization of on-going tangible capture projects. Products resulting from carboxylation reactions are obvious conversions. In addition, provided that enough supply of energy from non-fossil resources, such as solar [1], is ensured, CO2 reduction reactions can produce several valuable commodity chemicals including multi-carbon compounds, such as ethylene and acrylic acid, in addition to C1 chemicals and polymers. Presently, there are only few developing technologies which can find industrial applications. Therefore, there is a need for concerted research in order to assess the viability of these promising exploratory technologies rationally.

Ritchie Chen, Andrés Canales, P. Anikeeva

Manish Kumar, S. Sridharan, Ankush D. Sawarkar et al.

Pharmaceutical and personnel care products (PPCPs) from wastewater are a potential hazard to the human health and wildlife, and their occurrence in wastewater has caught the concern of researchers recently. To deal with PPCPs, various treatment technologies have been evolved such as physical, biological, and chemical methods. Nevertheless, modern and efficient techniques such as advance oxidation processes (AOPs) demand expensive chemicals and energy, which ultimately leads to a high treatment cost. Therefore, integration of chemical techniques with biological processes has been recently suggested to decrease the expenses. Furthermore, combining ozonation with activated carbon (AC) can significantly enhance the removal efficiency. There are some other emerging technologies of lower operational cost like photo-Fenton method and solar radiation-based methods as well as constructed wetland, which are promising. However, feasibility and practicality in pilot-scale have not been estimated for most of these advanced treatment technologies. In this context, the present review work explores the treatment of emerging PPCPs in wastewater, via available conventional, non-conventional, and integrated technologies. Furthermore, this work focused on the state-of-art technologies via an extensive literature search, highlights the limitations and challenges of the prevailing commercial technologies. Finally, this work provides a brief discussion and offers future research directions on technologies needed for treatment of wastewater containing PPCPs, accompanied by techno-economic feasibility assessment.

Malik Muhammad Waqar, Hassan Ali, Heng Zhou et al.

In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. However, the accurate measurement of shrimp size is challenged by factors such as their naturally curved body posture, frequent overlapping among individuals, and their tendency to blend with the background, all of which hinder precise size estimation. Traditional methods for measuring the size of shrimp involve manual sampling, which is labor-intensive and time consuming. In contrast, image processing and classical computer vision techniques provide some reasonable results but often suffer from inaccuracies, making them unsuitable for large-scale monitoring. To address this problem, this paper proposes a dual-segmentation deep learning-based framework for accurately estimating shrimp size. It integrates instance segmentation using the RTMDet-m model with an enhanced semantic segmentation model to effectively predict the centerline of the shrimp’s body, enabling precise size measurements. The first stage employs the RTMDet-m model for the instance segmentation of shrimp, achieving an average precision (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>AP</mi><mn>50</mn></msub></semantics></math></inline-formula>) of 96% with fewer parameters and the highest frames per second (FPS) count among state-of-the-art models. The second stage utilizes our custom segmentation model for centerline predictive module, attaining the highest FPS and F1-score of 88.3%. The proposed framework achieves the lowest mean absolute error of 1.02 cm and a root mean square error of 1.27 cm in shrimp size estimation compared to the baseline methods discussed in comparative study sections. Our proposed dual-segmentation framework outperforms both traditional and deep learning based methods used for measuring shrimp size.

Yunfeng Xu, Ling Shen, Mingjiong Chen et al.

Cadmium (Cd) contamination in soil poses a threat to crop production and food safety. Rhizosphere microorganisms are crucial for crop growth and production. However, sufficient evidence regarding Cd-responsive bacteria and fungi within crop rhizosphere remains largely unknown. Here, we investigated the impacts of Cd on soil microbial communities in wheat rhizosphere by performing 16S and ITS sequencing under normal (CK) and Cd (10 μM) conditions. We found that the lower concentration of Cd significantly increased Cd concentration in wheat grains (nearly 0.2 mg ​kg−1), but it had no obvious growth inhibition. Interestingly, bacterial abundance and diversity were significantly decreased in soil rhizosphere when exposed to Cd, whereas little changes were observed in fungi. A total of 259 CK-specific and 45 Cd-specific operational taxonomic units (OTUs) in bacteria, as well as 3 CK-specific and 2 Cd-specific OTUs in fungi were identified. The function of identified bacteria were enriched in human diseases, organismal systems, metabolism, genetic information processing and environmental information processing. We also revealed a complicated bacterial co-occurrence network responding to Cd, including the core bacteria of Acidobacteria, Nitrospirae and Chloroflexi phylums. This study revealed Cd-responding bacteria and fungi communities in wheat rhizosphere, which may provide new insights into beneficial microorganisms for food safety.

Armin Mohebbi, Maryam Ahmadi-Pour, Milad Mohebbi

This report introduces the application of two advanced intelligent models, an adaptively trained neuro-fuzzy inference logic in a hybrid configuration (Hybrid-ANFIS) and multilayer perceptron neural network (MLP-NN) to accurately determine the equilibrium sulfur adsorption in the liquid phase of hydrocarbon/ sulfur compound solution. Models were meticulously developed using a dataset of 107 empirical observations of seven types of sulfur compounds. These models incorporate the influence of input parameters, including initial sulfur level, adsorbent weight, molecular weights of the solvent and solute, densities of the solvent and solute, adsorbent particle diameter, temperature, and the Si/Al ratio of the adsorbent. Notably, the equilibrium sulfur adsorption amount was considered as the sole output variable. To evaluate the performance and precision of the implemented models, graphical representations and quantitative analyses were employed. Moreover, an assessment between the results of implemented models of the existing study and outcomes of previous reports were conducted. The results indicate that both developed models provide precise predictions. However, the Hybrid-ANFIS model demonstrates a strong correlation in predicting the adsorption empirical data, with an average absolute relative deviation of 0.36 % and an overall R2 value and 0.9997. In addition, superiority of the Hybrid-ANFIS model in providing the most reliable and accurate predictions of adsorption experimental data among all types of implemented models was concluded. This study sets a new benchmark in adsorption modeling by providing the most accurate and generalizable predictive framework to date.