Perspectives on life cycle analysis of solar technologies with emphasis on production in India.

The COVID-19 pandemic impacted the solar power industry, business, and supply chain for 2019-2021, and installations are falling behind the mission plan. However, Indian PV manufacturers see it as a chance to engage in solar manufacturing to establish a competitive, sustainable, and robust domestic solar industry instead of import-based installations. Given the country's current environmental concerns, green and sustainable local manufacturing is the only viable alternative. By conducting a life cycle assessment (LCA), this study compared the environmental impacts generated by the five most promising photovoltaic technologies-mono-silicon, polysilicon, copper indium gallium selenide (CIGS), cadmium telluride (CdTe), and passivated emitter and rear contact (PERC) solar modules considering manufacturing in India. The study utilizes the ReCiPe method supported by Ecoinvent 3 databases and Simapro V9.0 software, and the functional unit for the data collection is in 'per square meter', which is later converted to 'per kWh' standard for comparison with the existing studies. The system boundary selected is from cradle to gate. The results demonstrate that cadmium telluride (CdTe) is the best technology for Indian climatic conditions in terms of environmental impact, with a global warming potential of 0.015 kg CO2 eq/kWh, stratospheric ozone depletion of 5.41E-09 kg CFC11 eq/kWh, human carcinogenic and non-carcinogenic toxicity of 6.67E-04 kg 1,4-DCB/kWh and 1.48E-02 kg 1,4-DCB/kWh, respectively and fine particulate matter formation of 3.96E-05 kg PM 2.5 eq/kWh assuming a lifetime of 25 years for these modules. CIGS follows CdTe in almost every environmental impact category.

Green manufacturing for achieving carbon neutrality goal requires innovative technologies: A bibliometric analysis from 1991 to 2022.

Recent years have seen a significant increase in interest in green manufacturing as a key driver of global carbon-neutral efforts and sustainable development. To find the research hotspots of green manufacturing and reveal future research trends, this study reviewed and analyzed research articles from the Web of Science database on green manufacturing from 1991 to 2022 using a bibliometric method. The findings indicate a significant rise in the number of articles related to green manufacturing since the 2010s. Moreover, there has been an increase in the involvement of scholars from developing countries such as China and India in this field. Based on the literature review and bibliometric cluster analysis on green manufacturing, we believed that future research may continue following the lines of intelligent technology integration, adoption of frontier engineering techniques, and industry development in line with carbon reduction targets. A framework for future green manufacturing development is proposed, with a focus on Chinese policies. The framework could provide policy implications for developing countries looking to pursue opportunities for development in green manufacturing.

Application of Semiconductor Metal Oxide in Chemiresistive Methane Gas Sensor: Recent Developments and Future Perspectives.

The application of semiconductor metal oxides in chemiresistive methane gas sensors has seen significant progress in recent years, driven by their promising sensitivity, miniaturization potential, and cost-effectiveness. This paper presents a comprehensive review of recent developments and future perspectives in this field. The main findings highlight the advancements in material science, sensor fabrication techniques, and integration methods that have led to enhanced methane-sensing capabilities. Notably, the incorporation of noble metal dopants, nanostructuring, and hybrid materials has significantly improved sensitivity and selectivity. Furthermore, innovative sensor fabrication techniques, such as thin-film deposition and screen printing, have enabled cost-effective and scalable production. The challenges and limitations facing metal oxide-based methane sensors were identified, including issues with sensitivity, selectivity, operating temperature, long-term stability, and response times. To address these challenges, advanced material science techniques were explored, leading to novel metal oxide materials with unique properties. Design improvements, such as integrated heating elements for precise temperature control, were investigated to enhance sensor stability. Additionally, data processing algorithms and machine learning methods were employed to improve selectivity and mitigate baseline drift. The recent developments in semiconductor metal oxide-based chemiresistive methane gas sensors show promising potential for practical applications. The improvements in sensitivity, selectivity, and stability achieved through material innovations and design modifications pave the way for real-world deployment. The integration of machine learning and data processing techniques further enhances the reliability and accuracy of methane detection. However, challenges remain, and future research should focus on overcoming the limitations to fully unlock the capabilities of these sensors. Green manufacturing practices should also be explored to align with increasing environmental consciousness. Overall, the advances in this field open up new opportunities for efficient methane monitoring, leak prevention, and environmental protection.

The potential of 3D printing in facilitating carbon neutrality.

At present, dramatically reduction of fossil fuel usage is regarded as a major initiative to achieve the carbon neutrality goal. Nevertheless, current energy policies are unlikely to achieve the climate goal without sacrificing economic development and people's livelihood because fossil fuels are currently the dominant energy source. As an environment-friendly manufacturing technology, three-dimensional printing (3DP) is flourishing and is considered beneficial to energy structure adjustment and industrial upgrading. Despite this, its potential to contribute to global carbon neutrality has not attracted enough attention. Herein, we explore the application of 3DP and its potential facilitating carbon neutrality from crucial sectors and applications including manufacturing, construction energy, livestock, and carbon capture and storage (CCS) technologies. The additive manufacturing and decentralized manufacturing characteristics of 3DP allow reducing greenhouse gas (GHG) emissions in manufacturing and construction sectors by optimized and lightweight designs, reduced material and energy consumption, and shortened transport processes. In addition, 3DP enables the precise manufacturing of customized complex structures and the expansion of functional materials, which makes 3DP an innovative alternative to the development of novel energy-related devices, cultured meat production technology, and CCS technologies. Despite this, the majority of applications of 3DP are still in an early stage and need further exploration. We call for further research to precisely evaluate the GHG emission reduction potential of 3DP and to make it better involved and deployed to better achieve carbon neutrality.

Solvent-Free Synthesis and Processing of Conductive Elastomer Composites for Green Dielectric Elastomer Transducers.

Stretchable electrodes are more suitable for dielectric elastomer transducers (DET) the closer the mechanical characteristics of the electrodes and elastomer are. Here, a solvent-free synthesis and processing of conductive composites with excellent electrical and mechanical properties for transducers are presented. The composites are prepared by in situ polymerization of cyclosiloxane monomers in the presence of graphene nanoplatelets. The low viscosity of the monomer allows for easy dispersion of the filler, eliminating the need for a solvent. After the polymerization, a cross-linking agent is added at room temperature, the composite is solvent-free screen-printed, and the cross-linking reaction is initiated by heating. The best material shows conductivity σ = 8.2 S cm-1 , Young's modulus Y10%  = 167 kPa, and strain at break s = 305%. The electrode withstands large strains without delamination, shows no conductivity losses during repeated operation for 500 000 cycles, and has an excellent recovery of electrical properties upon being stretched at strains of up to 180%. Reliable prototype capacitive sensors and stack actuators are manufactured by screen-printing the conductive composite on the dielectric film. Stack actuators manufactured from dielectric and conductive materials that are synthesized solvent-free are demonstrated. The stack actuators even self-repair after a breakdown event.

Current efforts on sustainable green growth in the manufacturing sector to complement "make in India" for making "self-reliant India".

In an effort to become a global manufacturing giant, India has launched an ambitious "Make in India" campaign. In this article, we discussed the initiatives launched by Indian Government to create a sustainable economy, as well as opportunities for national and international start-up organisations to reinforce "Make in India" campaign. For the first time, we present an in-depth discussion of Green India policies and manufacturing sector challenges. The aim is to improve the manufacturing output of India and reduce dependence on foreign imports for which campaigns like "Atmanirbhar Bharat" which translates into "Self-Reliant-Green" India has also been started. Department of Science & Technology play a key role in establishing various programs such as infrastructure development, technological support, and green manufacturing programs all of which help to translate "discovery research" into "commercially viable technologies". It focuses specifically on "Startups", MSME's, young scientists, R&D labs and traditional manufacturing units that have little access to financial support but are an integral part of the Indian manufacturing ambit. The programs are interconnected and designed to function in a way that every support could be provided to the indigenous manufacturing, innovation and implementation of climate-resilient green growth strategies.

[Application prospect of new technology and new equipment in production of Chinese patent medicine].

At present,the production equipment and process of Chinese patent medicines still have many problems including high energy consumption,low efficiency,high pollution,and low intelligence,which seriously hinder the transformation,upgrading and modernized development of traditional Chinese medicine industry. With the emergence of various new pharmaceutical technologies and the application of technologies of other fields in traditional Chinese medicine industry,the development of Chinese patent medicine has ushered in new opportunities. The processes such as pulverization,mixing,extraction,separation,concentration,drying and sterilization are unique for the production of Chinese patent medicine. These main features can be distinguished from the manufacturing process of chemical drugs,determining the characteristics of the production process and equipment of Chinese patent medicine. In this paper,each operation unit was mentioned to summarize and analyze the new equipment and new technologies with advantages and characteristics in recent years from the perspectives of definition,principle,classification and application. Among them,the automatic spray device of the mixer,the extraction and separation equipment of volatile oil,and the crane basket-type circulation extraction technology,composite multi-layer spiral vibration countercurrent drying,and vibration sterilization equipment all have rapid development in recent years,with great prospects in the production of Chinese patent medicines. In this paper,we also analyzed some problems existing in the production equipment and technology of Chinese patent medicine and the key factors restricting the development of Chinese patent medicine,discussed the transformation of Chinese patent medicine production from traditional to modern and from semi-automatic to intelligent,and put forward three suggestions to help Chinese patent medicine achieve the goal of improving quality,efficiency and green manufacturing in production.

Biomachining: metal etching via microorganisms.

The use of microorganisms to remove metal from a workpiece is known as biological machining or biomachining, and it has gained in both importance and scientific relevance over the past decade. Conversely to mechanical methods, the use of readily available microorganisms is low-energy consuming, and no thermal damage is caused during biomachining. The performance of this sustainable process is assessed by the material removal rate, and certain parameters have to be controlled for manufacturing the machined part with the desired surface finish. Although the variety of microorganisms is scarce, cell concentration or density plays an important role in the process. There is a need to control the temperature to maintain microorganism activity at its optimum, and a suitable shaking rate provides an efficient contact between the workpiece and the biological medium. The system's tolerance to the sharp changes in pH is quite limited, and in many cases, an acid medium has to be maintained for effective performance. This process is highly dependent on the type of metal being removed. Consequently, the operating parameters need to be determined on a case-by-case basis. The biomachining time is another variable with a direct impact on the removal rate. This biological technique can be used for machining simple and complex shapes, such as series of linear, circular, and square micropatterns on different metal surfaces. The optimal biomachining process should be fast enough to ensure high production, a smooth and homogenous surface finish and, in sum, a high-quality piece. As a result of the high global demand for micro-components, biomachining provides an effective and sustainable alternative. However, its industrial-scale implementation is still pending.

Green manufacturing of a hypoxanthine enzyme sensor for fish freshness based on modified nitrocellulose surface with chito-oligosaccharide.

Hypoxanthine (Hx), produced by adenosine triphosphate (ATP) metabolism, is a valuable indicator that determines the quality and degradation status of meat products and is also an important biochemical marker to certain diseases such as gout. The rapid emergence of paper-based enzyme biosensors has already revolutionized its on-site determination. But it is still limited by the complex patterning and fabrication, unstable enzyme and uneven coloration. This work aims to develop an eco-friendly method to construct engineered paper microfluidic, which seeks to produce reaction and non-reaction zones without any patterning procedure. Chito-oligosaccharide (COS), derived from shrimp shells, was used to modify nitrocellulose membranes and immobilize xanthine oxidase (XOD) and chromogenic agent of nitro blue tetrazolium chloride (NBT). After modification, micro fluids could converge into the modification area and Hx could be detected by XOD-catalyzed conversion. Due to the positively charged cationic basic properties of COS, the enzyme storage stability and the color homogeneity could be greatly strengthened through the electrostatic attraction between COS and XOD and formazan product. The detection limit (LOD) is 2.30 µM; the linear range is 0.05-0.35 mM; the complete test time can be as short as 5 min. The COS-based biosensor shows high specificity and can be used directly for Hx in complex samples such as fish and shrimp samples, and different broths. This biosensor is eco-friendly, nontechnical, economical and therefore a compelling platform for on-site or home-based detection of food freshness.

The nexus between green intellectual capital, blockchain technology, green manufacturing, and sustainable performance.

Enterprises across the globe are facing increasing pressure to effectively utilize resources and reduce costs through green supply chain practices. Emerging technology, such as blockchain technology which enables green practices, has become a contemporary industrial paradigm. However, enterprises need to build green intellectual capital to implement blockchain technology, which can be key to realizing green supply chain practices. This research examines the impact of green intellectual capital (GIC) on blockchain technology and its role in implementing green manufacturing to achieve sustainability. Partial least squares structural equation modeling was utilized for assessing the proposed hypotheses, and cross-sectional data was accumulated from manufacturing firms. As per the results, GIC, which includes green human capital, green structural capital, and green relational capital has a crucial role in the implementation of blockchain technology. The outcomes also indicated that the adoption of blockchain technology significantly influences green manufacturing. Moreover, green manufacturing (GM) has a substantial role in improving business sustainability. This empirical research provides a deeper understanding of how GIC and blockchain technology contribute to the implementation of GM. This research also provides guidelines that managers, policymakers, and producers can use to facilitate the incorporation of GM practice into business activities.

A Critical Review on Immobilized Sucrose Isomerase and Cells for Producing Isomaltulose.

Isomaltulose is a novel sweetener and is considered healthier than the common sugars, such as sucrose or glucose. It has been internationally recognized as a safe food product and holds vast potential in pharmaceutical and food industries. Sucrose isomerase is commonly used to produce isomaltulose from the substrate sucrose in vitro and in vivo. However, free cells/enzymes were often mixed with the product, making recycling difficult and leading to a significant increase in production costs. Immobilized cells/enzymes have the following advantages including easy separation from products, high stability, and reusability, which can significantly reduce production costs. They are more suitable than free ones for industrial production. Recently, immobilized cells/enzymes have been encapsulated using composite materials to enhance their mechanical strength and reusability and reduce leakage. This review summarizes the advancements made in immobilized cells/enzymes for isomaltulose production in terms of refining traditional approaches and innovating in materials and methods. Moreover, innovations in immobilized enzyme methods include cross-linked enzyme aggregates, nanoflowers, inclusion bodies, and directed affinity immobilization. Material innovations involve nanomaterials, graphene oxide, and so on. These innovations circumvent challenges like the utilization of toxic cross-linking agents and enzyme leakage encountered in traditional methods, thus contributing to enhanced enzyme stability.

Impact of warranty and green level of the product with nonlinear demand via optimal control theory and Artificial Hummingbird Algorithm.

Due to the current environmental situation and human health, a green manufacturing system is very essential in the manufacturing world. Several researchers have developed various types of green manufacturing models by considering green products, green investments, carbon emission taxes, etc. Motivated by this topic, a green production model is formulated by considering selling price, time, warranty period and green level dependent demand with a carbon emission tax policy. Also, the production rate of the system is an unknown function of time. Per unit production cost of the products is taken as increasing function of production rate and green level of the products. In our proposed model, carbon emission rate is taken as linear function of time. Then, an optimization problem of the production model is constructed. To validate of our proposed model, a numerical example is considered and solved it by AHA. Further, other five metaheuristics algorithms (AEFA, FA, GWOA, WOA and EOA) are taken to compare the results obtained from AHA. Also, concavity of the average profit function and convergence graph of different metaheuristics algorithms are presented. Finally, a sensitivity analysis is carried out to investigate the impact of different system parameters on our optimal policy and reach a fruitful conclusion from this study.

Available Strategies for Improving the Biosynthesis of Methionine: A Review.

Methionine is the only nonpolar α-amino acid containing sulfur among the eight essential amino acids and is closely related to the metabolism of sulfur-containing compounds in the human body. Widely used in feed, medicine, food, and other fields, the market demand is increasing annually. However, low productivity and high cost largely limit the industrial production of methionine, and many novel production methods still have their own disadvantages. In this paper, the available methods for synthesizing methionine are reviewed and discussed. The latest strategies for improving methionine production are further introduced, including culture medium optimization, mutation technology, expression of key genes in the metabolic pathway, knockout and recombination, as well as the engineering of membrane transporters, the fermentation-enzymatic coupling route, and innovation of CO2 biotransformation.

Linking green supply chain management practices and environmental performance in the manufacturing industry: a hybrid SEM-ANN approach.

This research determines the influence of green supply chain management practices (GSCM) on environmental performance. It also investigates the moderating role of supply chain environmental cooperation on GSCM practices and environmental performance relationships. A total of 370 employees of several Bangladeshi manufacturing companies were conveniently chosen as respondents. To verify the data validity and reliability and to test the hypotheses, we used SmartPLS. Finally, we employed an artificial neural network (ANN) to examine the relationship. Green design and green manufacturing have significant positive impacts on environmental performance, while green procurement and green distribution do not. Moreover, environmental cooperation moderates the relationships of green design and green distribution with environmental performance. The moderating effect of supply chain environmental cooperation in the relationship between GSCM practices and environmental performance in the manufacturing industry adds knowledge to the existing literature by incorporating a hybrid model combining PLS-SEM and ANN. Our study adds to the current body of knowledge by delving into the literature on GSCM from the perspective of Bangladesh's industrial sector. This study fills a knowledge gap by shedding light on the interactions of GSCM and environmental performance. Indeed, this study represents a step forward from classic linear regression-based models to an ANN-based nonlinear model. It also demonstrates new contributions to the literature on green supply chain management and environmental performance.

Direct Recycling of WC-Co Grinding Chip.

Grinding is a finishing process for high precision, high surface quality parts, and hard materials, including tool fabrication and sharpening. The recycling of grinding scraps, which often contain rare and costly materials such as tungsten carbide (WC-Co), has been established for decades. However, there is a growing need for more energy-efficient and environmentally friendly recycling processes. Currently, grinding sludges, which are a mixture of abrasives, lubricants, and hard metal chips, are only treated through chemical recycling. Direct recycling ("reuse" of chips as raw material) is the most effective but not yet viable process due to the presence of contaminants. This paper presents an oil-free dry grinding process that produces high-quality chips (i.e., oil-free and with few contaminants, smaller than 60 mesh particle size) that can be directly recycled, as opposed to the oil-based wet grinding that generates sludges, which require indirect recycling. The proposed alternative recycling method is validated experimentally using WC-Co chips from a leading hard metals' processing specialized company. The contaminant level (oxygen 0.8 wt.%, others < 0.4 wt.%), granulometry (chip D50 = 10.4 µm with grain size < 3 µm) and morphology of the recycled chips' powder is comparable to commercial powders proving the research and industrial potential of direct recycling. The comparison of sintered products using recycled and commercial powder provided equivalent characteristics for hardness (HRA of 90.7, HV30 of 1430), porosity grade (A02-04) and grain size (<3 µm).

Hybrid evolutionary algorithm for stochastic multiobjective disassembly line balancing problem in remanufacturing.

With the development of the industrial economy and the accelerated renewal of products, many end-of-life products (EOL) have been generated to pollute our environment. This fact highlights the importance of recycling and remanufacturing EOL products as an active research topic. An efficient disassembly line is one solution for improving the remanufacturing and recycling processes of EOL products while reducing the environmental pollution. Although many optimization models and intelligent algorithms were developed to address the disassembly line balancing problem (DLBP), uncertainty was ignored by them. To alleviate the drawbacks of uncertainty for the disassembly operation, this study proposes a stochastic multi-objective optimization model for the DLBP minimizing the disassembly idle rate, smoothness, and energy consumption generated during the operation under uncertain operation time. Another novelty of this paper is to present an improved version of the northern goshawk optimization algorithm using a stochastic simulation method to solve the proposed model. The feasibility of the proposed model and the applicability of the developed algorithm are shown by two extensive examples. Finally, the performance of the proposed algorithm is revealed by a comparison with recent and state-of-the-art algorithms from the literature.

Contribution of Bayesian networks as a robust tool in risk assessment under sustainability considerations, a case study of Bandarabbas refinery.

Background and purpose: Refineries are among the industrial centers that supply the energy and raw materials to downstream industries. To achieve sustainable development goals, creating appropriate balance between economical and environmental goals has always been the focus of managers and policy makers in the societies. Bayesian Network model has become a robust tool in the field of risk assessment and uncertainty management in refineries. The focus of this research is to prioritizing different units from the point of view of social and ecological aspects for facilitating the decision making process in the context of waste material treatment in Bandarabbas refinery in line with the sustainable development goals. Materials and methods: The methodology of this research is based on risk assessment with the aid of Bayesian Networks. To this end, first material flow analysis of the processes procured risk identification, subsequently influence diagram and Bayesian Network structure were designed. After completing conditional probability tables, finally risk factors were prioritized. What is more, sensitivity analysis of the model performed by applying three approaches namely predictive, diagnostic, and considering only one risk. Conclusion: According to the risk assessment results, Amine treatment and Fuel units were classified as the most significant risk factors, whereas Pipelines and Plant air & instrument air system were identified as the most environmental friendly units. In addition, sensitivity analysis of the model provided appropriate framework to shed some light on the circumstances of determining dominant risk factors whether only one or concurrently all of the endpoints are evaluated.

Environment-oriented disassembly planning for end-of-life vehicle batteries based on an improved northern goshawk optimisation algorithm.

Due to environmental pollution and resource shortages, the electric vehicle industry has been developing swiftly, and the market demand for batteries, as an essential part of electric vehicles, has also surged. Proper disassembly of end-of-life vehicle batteries (ELV batteries) is necessary to achieve the integrity and closure of their life cycle, promote the development of green remanufacturing, effectively reduce the pollution of the environment caused by metal ion leakage, and reduce people's dependence on natural resources to a certain extent. To schedule the disassembly operations of ELV batteries more rationally and further promote their disassembly quality and efficiency, this paper proposes a dual-objective disassembly sequence planning (DSP) optimisation model, which aims to minimise the hazard index and energy cost during ELV battery disassembly operations. Since the proposed model is a complex NP-hard optimisation problem, this study develops an efficient metaheuristic algorithm for solving this model based on the northern goshawk optimisation algorithm. The main algorithm adds two types of discrete recombination operators and a local search operator. At the same time, the predatory behaviour of the goshawk is optimised by combining the characteristics of the disassembly sequence planning problem to improve its performance. Finally, the disassembly of the battery of a Tesla Model 1 is used as a case study to demonstrate the effectiveness and feasibility of the proposed method.

Digital finance innovation in green manufacturing: a bibliometric approach.

In the era of Industry 4.0, the innovative applications of the industrial internet of things continue to deepen, and the trend of digital transformation of the green manufacturing industry continues to expand. In this context, the study of digital finance innovation in green manufacturing enterprises is conducive to transforming and upgrading enterprises and national economic development. In order to review the theoretical foundations and the current state of research under this topic, this paper provides an overview of digital finance innovation in green manufacturing companies based on 296 papers published between 1900 and 2021 through bibliometric and scientific visualization methods. This paper uses HistCite to identify the most influential authors, institutions, and countries and uncover the lineage of research on digital finance innovation in green manufacturing companies. At the same time, VOSviewer is used to identify research hotspots and research clusters under the topic. Finally, on this basis, this paper classifies the types of digital innovation from the perspective of value creation. It proposes a theoretical framework for the realization path of digital finance innovation in green manufacturing enterprises based on intelligent servitization and orchestration capabilities. The findings of this paper enrich the existing innovation theory and facilitate scholars to conduct future research more effectively.

A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems.

With the increasing severity of environmental problems, low-carbon development has become an inevitable choice. Nowadays, low-carbon green sustainable development is influenced by a variety of factors such as social, environmental, technological, and economic development levels, making its development complex, which in turn imposes challenges on decision-makers. In this context, the application of multi-criteria decision-making (MCDM) in different areas of sustainable development engineering has become a hot topic. Although many reviews of MCDM techniques already exist, there is a lack of holistic review efforts on MCDM in the field of low-carbon transport and green logistics. Considering these shortcomings in the state of the art, this paper systematically reviews more than 190 papers from 2010 to 2022, constructs a general structure of MCDM techniques for this research topic, provides a comprehensive review and analysis of it, and clarifies the current practices. Furthermore, future directions for the development of MCDM techniques for green logistics and low-carbon transportation systems are presented as well.