Hasil untuk "Chemical industries"

Hao Chen, M. Ling, Luke Hencz et al.

Tremendous efforts have been devoted to the development of electrode materials, electrolytes, and separators of energy-storage devices to address the fundamental needs of emerging technologies such as electric vehicles, artificial intelligence, and virtual reality. However, binders, as an important component of energy-storage devices, are yet to receive similar attention. Polyvinylidene fluoride (PVDF) has been the dominant binder in the battery industry for decades despite several well-recognized drawbacks, i.e., limited binding strength due to the lack of chemical bonds with electroactive materials, insufficient mechanical properties, and low electronic and lithium-ion conductivities. The limited binding function cannot meet inherent demands of emerging electrode materials with high capacities such as silicon anodes and sulfur cathodes. To address these concerns, in this review we divide the binding between active materials and binders into two major mechanisms: mechanical interlocking and interfacial binding forces. We review existing and emerging binders, binding technology used in energy-storage devices (including lithium-ion batteries, lithium-sulfur batteries, sodium-ion batteries, and supercapacitors), and state-of-the-art mechanical characterization and computational methods for binder research. Finally, we propose prospective next-generation binders for energy-storage devices from the molecular level to the macro level. Functional binders will play crucial roles in future high-performance energy-storage devices.

Maxence Fache, B. Boutevin, S. Caillol

Janusz J. Sikorski, Joy Haughton, M. Kraft

A. Hoffman

Karin Ackermann

Hao Wu, Jinsong Zhao

Abstract Numerous accidents in chemical processes have caused emergency shutdowns, property losses, casualties and/or environmental disruptions in the chemical process industry. Fault detection and diagnosis (FDD) can help operators timely detect and diagnose abnormal situations, and take right actions to avoid adverse consequences. However, FDD is still far from widely practical applications. Over the past few years, deep convolutional neural network (DCNN) has shown excellent performance on machine-learning tasks. In this paper, a fault diagnosis method based on a DCNN model consisting of convolutional layers, pooling layers, dropout, fully connected layers is proposed for chemical process fault diagnosis. The benchmark Tennessee Eastman (TE) process is utilized to verify the outstanding performance of the fault diagnosis method.

Zia-ud-din, Hanguo Xiong, Peng Fei

S. Pankaj, Hu Shi, K. Keener

Brendan Janissen, T. Huynh

U. Biermann, U. Bornscheuer, I. Feussner et al.

Abstract Oils and fats of vegetable and animal origin remain an important renewable feedstock for the chemical industry. Their industrial use has increased during the last 10 years from 31 to 51 million tonnes annually. Remarkable achievements made in the field of oleochemistry in this timeframe are summarized herein, including the reduction of fatty esters to ethers, the selective oxidation and oxidative cleavage of C–C double bonds, the synthesis of alkyl‐branched fatty compounds, the isomerizing hydroformylation and alkoxycarbonylation, and olefin metathesis. The use of oleochemicals for the synthesis of a great variety of polymeric materials has increased tremendously, too. In addition to lipases and phospholipases, other enzymes have found their way into biocatalytic oleochemistry. Important achievements have also generated new oil qualities in existing crop plants or by using microorganisms optimized by metabolic engineering.

Jingxin Shi, Wenping Huang, Hong-jun Han et al.

Abstract The current situation of China's coal chemical industry faces many problems: 1) This industry causes environmental pollution; 2) employs inadequate environmental management system, wastewater pollution control standards, and energy consumption standards; 3) lacks environmental standards applicable to the coal chemical industry; 4) suffers from poor implementation of technical standards for coal use; 5) and lacks top-level design of a high salinity wastewater standard. A modern coal chemical industry demonstration area should be established to promote industrial agglomeration and development. Therefore, several suggestions are put forward to promote the modernization of the coal chemical industry: 1) The responsibilities, supervision tasks, scope, and implementation rules of local environmental law enforcement and supervision agencies should be improved and clarified at all levels; consequently, law enforcement and supervision work would be backed up by relevant laws. 2) To decrease the treatment cost of highly saline wastewater, a corresponding subsidy scheme should be formulated. 3) Research on the top-level design of the standard system for saline wastewater should be accelerated to standardize the treatment of saline wastewater. 4) Coal chemical enterprises should integrate environmental management into their daily production management system, constantly improve their management level, and reduce pollution generation and emission. 5) Furthermore, it is necessary to consider the recycling of wastes and both the separation and recovery of valuable resources as part of the treatment of wastewater from the coal chemical industry. 6) Moreover, economic policies can be used because economic leverage may be more effective than administrative orders or even regulations. 7) Finally, cooperation should be increased to promote the “green development, circular development, and low-carbon development” of the modern coal chemical industry.

Jingxin Shi, Wenping Huang, Hong-jun Han et al.

Abstract Reducing salt wastewater emissions to the outside world is significant for the “zero discharge” requirement of coal chemical industry. This review is mainly about the treatment technologies of salt-containing wastewater and high-salt wastewater in coal chemical industry of China. In the treatment of high-salt wastewater, coal chemical industry projects in China mostly use the “double membrane” reuse technology of “ultrafiltration + reverse osmosis”. Reverse osmosis is the core and main technology of reuse treatment, while ultrafiltration is the pretreatment and protection process. High-salt wastewater refers to the concentrated reverse osmosis wastewater of the reuse system. Evaporation crystallization technology can achieve “zero discharge” of wastewater by transforming high-salt wastewater into solid crystal mixed salt. It is a mature and recognized process at present stage, but the disposal of mixed salt is an urgent problem to be solved. Cooling crystallization and nanofiltration membrane can realize separation of mixed salt, but these technologies have not been applied to actual coal chemical project, and further research is needed.

R. Sheldon, D. Brady

In the movement to decarbonize our economy and move away from fossil fuels we will need to harness the waste products of our activities, such as waste lignocellulose, methane and carbon dioxide. Our wastes need to be integrated into a circular economy where used products are recycled into a manufacturing carbon cycle. Key to this will be the recycling of plastics at the resin and monomer levels. Biotechnology is well suited to a future chemical industry that must adapt to widely distributed and diverse biological chemical feedstocks. Our increasing mastery of biotechnology is allowing us to develop enzymes and organisms that can synthesize a widening selection of desirable bulk chemicals, including plastics, at commercially viable productivities. Integration of bioreactors with electrochemical systems will permit new production opportunities with enhanced productivities and the advantage of using a low-carbon electricity from renewable and sustainable sources.

A. A. Kiss, Robin Smith

Abstract The need for greater sustainability for the production of fuels and chemicals has spurred significant research to rethink energy use in the chemical industry, and eventually substitute fossil fuel sources by renewable sources. Nowadays, the chemical industry is responsible for about one third of the total energy used - and the associated CO2 emissions - in the industrial sector. Among the energy intensive operations, distillation alone is responsible for about 40% of the energy used in the chemical industry, but there is clearly much room for improvement. This paper aims to provide an informative perspective on the current energy use in the chemical industry, with a focus on distillation – the undisputed king of industrial separation processes – and potential improvements for a more sustainable future. There is clearly an increasing need and scope for advanced distillation technologies (e.g. reactive distillation, dividing-wall columns, thermal coupling, cyclic distillation, heat pump assisted distillation, and heat integrated distillation columns) that can significantly reduce the energy usage and the carbon footprint of modern chemical plants. However, these advanced distillation technologies must be considered, along with conventional distillation operations, in the context of the process as a whole. Based on the overview provided, several challenges and opportunities for research directions are highlighted towards rethinking the energy use in distillation processes, for a more sustainable chemical industry.

Rong Xia, Sean Overa, F. Jiao

Electrification is a potential approach to decarbonizing the chemical industry. Electrochemical processes, when they are powered by renewable electricity, have lower carbon footprints in comparison to conventional thermochemical routes. In this Perspective, we discuss the potential electrochemical routes for chemical production and provide our views on how electrochemical processes can be matured in academic research laboratories for future industrial applications. We first analyze the CO2 emission in the manufacturing industry and conduct a survey of state of the art electrosynthesis methods in the three most emission-intensive areas: petrochemical production, nitrogen compound production, and metal smelting. Then, we identify the technical bottlenecks in electrifying chemical productions from both chemistry and engineering perspectives and propose potential strategies to tackle these issues. Finally, we provide our views on how electrochemical manufacturing can reduce carbon emissions in the chemical industry with the hope to inspire more research efforts in electrifying chemical manufacturing.

Mohammad Safdari, Mostafa Narimani, Majid Dastanian et al.

In this study, the novel poly (ether-ester) urethane membranes, synthesized from poly(dioxanone) (PDO) and poly (ethylene glycol) (PEG) triblock copolymers, were introduced for the humic acid removal as a model of natural organic matter from aqueous solution. These membranes were modified with Sulfonated Graphene Oxide (SGO). Bulk ring-opening polymerization and one-step bulk polycondensation were used to prepare triblock poly(p-dioxanone)-poly (ethylene oxide)-poly(p-dioxanone) (PEDO) and Poly (ether-ester) urethanes, respectively. The phase inversion method was used for preparation of impregnated poly(ether-ester) urethanes (PEEUs) membranes with 0,0.03,0.06,0.09, and 0.125 SGO/PEEU mass ratios. Membrane characterization involved Nuclear Magnetic Resonance (H1-NMR), Scanning Electron Microscopy (SEM), Differential Scanning Calorimetry (DSC), Fourier Transform InfraRed (FT-IR) spectrometer, tensile strength testing, and contact angle measurement. Results showed that modified membranes with PEG content of 11.23% and SGO/PEEU mass ratio of 0.09 exhibit significant differences in properties (morphology, thermal, hydrophilicity, and mechanical) and performance due to the presence of PEG and sulfonated graphene oxide. The total fouling ratio (Rt) value of the modified membrane (SGO/ PEEU mass ratio:0.09, PEG molecular weight: 600 g/mol) was obtained at 25.3%, which is due to the additive effect on fouling reduction. Also, the result of filtration rejection showed that the humic acid rejection increased up to 99% by SGO incorporation. According to the results, these membranes can be introduced as a comprehensive potential for the proper rejection of humic acid from water.

Ruohan Yu, Yuan Chi, Richard Fuchs et al.

Abstract Conventional display technologies rely on rigid architectures, limiting their adaptability for reconfigurable systems. Plasma discharge, as a field‐driven excitation method, offers great opportunities for visual interfaces, yet integrating it into controllable and adaptable color display platforms remains challenging. Here, configurable and adaptable electroluminescent platforms based on the plasma discharge of phosphor‐coated liquid metal marbles based on eutectic gallium indium liquid metal droplets are presented. Electroluminescent phosphors emitting the red, green, and blue primary colors are used as a functionalizing coating for the droplets. Mixing different types of phosphor particles at controllable ratios fine tunes the electroluminescent color emitted from individual air gaps between adjacent liquid metal marbles. Such a particle‐mixing‐enabled additive color mixing strategy enables bright color emission across the whole visible spectrum and plasma‐discharge‐based pixelated multicolor display of diverse reconfigurable patterns. This low‐cost and easily reconfigurable liquid metal marble platform offers a multicolor display technique for future displays.

Tomoya Shiota, Klaas Gunst, Toshio Mori et al.

We demonstrate the feasibility of quantum computing for large-scale, realistic chemical systems through the development of a new interface using a quantum circuit simulator and CP2K, a highly efficient first-principles calculation software. Quantum chemistry calculations using quantum computers require Hamiltonians prepared on classical computers. Moreover, to compute forces beyond just single-point energy calculations, one- and two-electron integral derivatives and response equations are also to be computed on classical computers. Our developed interface allows for efficient evaluation of forces with the quantum-classical hybrid framework for large chemical systems. We performed geometry optimizations and first-principles molecular dynamics calculations on typical condensed-phase systems. These included liquid water, molecular adsorption on solid surfaces, and biological enzymes. In water benchmarks with periodic boundary conditions, we confirmed that the cost of preparing second-quantized Hamiltonians and evaluating forces scales almost linearly with the simulation box size. This research marks a step towards the practical application of quantum-classical hybrid calculations, expanding the scope of quantum computing to realistic and complex chemical phenomena.

Lu Xia, Kaiqi Zhao, Sunil Kadam et al.

Paired electrolysis at industrial current densities offers an energy-efficient and sustainable alternative to thermocatalytic chemical synthesis by leveraging anodic and cathodic valorization. However, its industrial feasibility remains constrained by system integration, including reactor assembly, asymmetric electron transfer kinetics, membrane selection, mass transport limitations, and techno-economic bottlenecks. Addressing these challenges requires an engineering-driven approach that integrates reactor architecture, electrode-electrolyte interactions, reaction pairing, and process optimization. Here, we discuss scale-specific electrochemical reactor assembly strategies, transitioning from half-cell research to full-scale stack validation. We develop reaction pairing frameworks that align electrocatalyst design with electrochemical kinetics, enhancing efficiency and selectivity under industrial operating conditions. We also establish application-dependent key performance indicators (KPIs) and benchmark propylene oxidation coupled with hydrogen evolution reaction (HER) or oxygen reduction reaction (ORR) against existing industrial routes to evaluate process viability. Finally, we propose hybrid integration models that embed paired electrolysis into existing industrial workflows, overcoming adoption barriers.

Habibollah Safari, Mona Bavarian

Predicting monomer reactivity ratios is crucial for controlling monomer sequence distribution in copolymers and their properties. Traditional experimental methods of determining reactivity ratios are time-consuming and resource-intensive, while existing computational methods often struggle with accuracy or scalability. Here, we present a method that combines unsupervised learning with artificial neural networks to predict reactivity ratios in radical copolymerization. By applying spectral clustering to physicochemical features of monomers, we identified three distinct monomer groups with characteristic reactivity patterns. This computationally efficient clustering approach revealed specific monomer group interactions leading to different sequence arrangements, including alternating, random, block, and gradient copolymers, providing chemical insights for initial exploration. Building upon these insights, we trained artificial neural networks to achieve quantitative reactivity ratio predictions. We explored two integration strategies including direct feature concatenation, and cluster-specific training, which demonstrated performance enhancements for targeted chemical domains compared to general training with equivalent sample sizes. However, models utilizing complete datasets outperformed specialized models trained on focused subsets, revealing a fundamental trade-off between chemical specificity and data availability. This work demonstrates that unsupervised learning offers rapid chemical insight for exploratory analysis, while supervised learning provides the accuracy necessary for final design predictions, with optimal strategies depending on data availability and application requirements.