Development Of Industrial Processes Research Articles

Experimental study on alkylation of PCl3 for methyl-dichloride phosphine synthesis using mass spectrometry detection

An online sampling and mass spectrometry (MS) detection method was developed to study the alkylation of PCl3 with methane at high temperature for synthesis of methyl-dichloride phosphine (CH3PCl2, MDP), which was a free radical reaction on a millisecond time scale. Through qualitative analysis, the byproducts P4 and chloro-dimethyl-phosphine ((CH3)2PCl, CDMP) were identified, with their formation mechanisms elucidated for the first time. The effects of operation conditions, including temperature, residence time, and types and concentrations of chloromethanes (CH4-xClx, x = 2, 3, 4), on both MDP yield and selectivity, were systematically investigated. The optimal operation conditions were determined based on MDP yield and selectivity. The addition of chloromethanes significantly enhanced PCl3 conversion. Chloromethanes underwent conversion in the reaction, promoting PCl3 conversion while also continuously converting into lower chlorinated methane derivatives. These results are of great significance for guiding rational industrial process development.

Nitrogen and me — How little did we, and do we know about “stikstof – azote – nitrogen”?

This retrospective article reflects on the complex and evolving relationship between humans and nitrogen over several decades. Raised on a Flemish farm, the author's early experiences with nitrogen in agriculture – both its benefits and dangers – laid the foundation for a lifelong interest in this element. The article traverses a broad range of topics related to nitrogen, highlighting its critical role in various historical, agricultural, environmental, and industrial contexts. The narrative begins with a historical overview of nitrogen's role in agriculture and warfare. The development of industrial processes like the Haber and Ostwald methods transformed nitrogen into a key ingredient for both fertilizers and explosives. The dual nature of nitrogen – as a life-giver in agriculture and a destructive component in warfare and also in biodiversity – is an important theme. The article delves into the environmental impacts of nitrogen, particularly in the context of modern agriculture and industrialization. Issues like fertilization, water contamination, and the challenges of managing nitrogenous waste highlight the complex interplay between human activities and environmental health. Technological advancements are explored, including the development of bioaugmentation methods and the potential of genetic engineering in optimizing nitrogen fixation. Throughout the narrative, personal anecdotes are weaved with scientific information, offering a unique perspective on the historical and contemporary challenges of managing nitrogen. The discussion extends to the broader implications of nitrogen management in the context of sustainability, climate change, and global food security and its overall regulatory space. All these considerations call for a re-evaluation of our relationship with nitrogen, advocating for innovative solutions and systemic thinking to address the multifaceted challenges posed by this essential, yet often problematic element.

Online monitoring of protein refolding in inclusion body processing using intrinsic fluorescence

Inclusion bodies (IBs) are protein aggregates formed as a result of overexpression of recombinant protein in E. coli. The formation of IBs is a valuable strategy of recombinant protein production despite the need for additional processing steps, i.e., isolation, solubilization and refolding. Industrial process development of protein refolding is a labor-intensive task based largely on empirical approaches rather than knowledge-driven strategies. A prerequisite for knowledge-driven process development is a reliable monitoring strategy. This work explores the potential of intrinsic tryptophan and tyrosine fluorescence for real-time and in situ monitoring of protein refolding. In contrast to commonly established process analytical technology (PAT), this technique showed high sensitivity with reproducible measurements for protein concentrations down to 0.01 g L-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document}. The change of protein conformation during refolding is reflected as a shift in the position of the maxima of the tryptophan and tyrosine fluorescence spectra as well as change in the signal intensity. The shift in the peak position, expressed as average emission wavelength of a spectrum, was correlated to the amount of folding intermediates whereas the intensity integral correlates to the extent of aggregation. These correlations were implemented as an observation function into a mechanistic model. The versatility and transferability of the technique were demonstrated on the refolding of three different proteins with varying structural complexity. The technique was also successfully applied to detect the effect of additives and process mode on the refolding process efficiency. Thus, the methodology presented poses a generic and reliable PAT tool enabling real-time process monitoring of protein refolding.Graphical abstractReal-time intrinsic fluorescence monitoring in protein refolding

Green solvent selection and extractin protocol for selective recovery of anti-diabetic components from T. crispa

This study systematically explores a green extraction process of T. crispa stems to selectively isolate therapeutic compounds, borapetoside C (BPC) and magnoflorine (MGF), recognized for their anti-diabetic properties. In agreement with Hansen solubility parameters prediction, H2O and EtOH were found to be suitable solvents for extraction of BPC and MGF, respectively, resulting in 33 % and 45 % extractabilities after 60 min. Further investigations demonstrated considerable increase in BPC extractability using 20 % EtOH:H2O mixture at 40 °C, with complete extraction achieved after 60 min. While for MGF, pure-EtOH at 40 °C, was the most suitable solvent, showing the highest selectivity and complete extraction after 100 min. The BPC-rich extract from 20 % EtOH:H2O exhibited higher anti-diabatic activity (IC50 = 0.63 ± 0.03 and 0.72 ± 0.04 mg/mL, respectively, for α-glucosidase and α-amylase enzymes inhibition activity), and considerably lower cytotoxicity to L6 and HepG2 cells, with IC50 = 0.26 ± 0.16 and 0.24 ± 0.02 mg/mL, respectively, compared with the MGF-rich extract obtained with pure-EtOH. Based on these results, a sequential extraction scheme was proposed involving initial pure-EtOH extraction to selectively and completely remove MGF, followed by extraction with a 20 % EtOH:H2O mixture to recover the remaining BPC, which was approximately 80 % of the BPC originally present. The obtained MGF-free BPC-rich extract showed significantly lower cytotoxicity (IC50 = 0.31 ± 0.06 mg/mL against L6 cell) and higher enzyme inhibition activities (IC50 = 0.53 ± 0.32 and 0.52 ± 0.02 mg/mL for α-glucosidase and α-glucosidase enzymes inhibition activity), comparable to acarbose (IC50 = 0.43 ± 0.02 and 0.83 ± 0.03 mg/mL for α-glucosidase and α-glucosidase enzymes inhibition activity), the result that potentially leads to the development of a promising industrial process to harness T. crispa for diabetes prevention and treatment.

Networking Platform: For transfer and collaboration

AbstractA forum for chemists, chemical and process engineers promotes the sustainable growth of the Swiss chemical industry. It aims to emphasize the importance of chemical production and process development in research, education, industry and politics. This portrait reveals how it does this.

Industrial Development and Social Values: an Econometric Approach

The article delves into how original institutional economics elucidates processes of industrial development through the lenses of technological, institutional, and social factors. By employing econometric methods, we can further enhance theoretical research within the realm of original institutionalism by quantitatively analyzing social values. Fundamentally, social values form the basis for selecting behavioral patterns, institutions, and institutional frameworks to shape both individual and collective development trajectories. Research on social values yields crucial insights into how the public perceives specific contemporary challenges and issues. The Veblenian dichotomy aptly conceptualizes industrial and technological transformations alongside social values and institutions. Leveraging this dichotomy draws attention to the limitations of market mechanisms driven by contracts and profit motives, underscoring the need for a comprehensive analysis of modern industrial production in light of evolving social values. Through econometric modeling, specifically the use of the ordered logit model, we investigate the impact of industrial development levels and metrics assessing institutional progress in countries, as well as the significance of technology advancement in the future. While Russia exhibits relatively lower indices reflecting both personalized and institutional trust, the model validates a correlation between respondents' subjective evaluations of institutional quality in the country and their perceptions of future technology significance. Moreover, the model confirms a positive association between a country's industrial development level and respondents' views on the importance of technology progression in the future.

Niclosamide: A career builder

My contribution to honoring Professor Kinam Park celebrates and resonates with his scholarly career in drug delivery, his commitment to encouraging the next generation(s), and his efforts to keep us focused on clinically effective formulations. To do this I take as my example, niclosamide, a small molecule protonophore that, uniquely, can “target” all cell membranes, both plasma and organelle. As such, it acts upstream of many cell pathways and so has the potential to affect many of the essential events that a cell, and particularly a diseased cell or other entities like a virus, use to stay alive and prosper. Literature shows that it has so far been discovered to positively influence (at least): cancer, bacterial and viral infection, metabolic diseases such as Type II diabetes, NASH and NAFLD, artery constriction, endometriosis, neuropathic pain, rheumatoid arthritis, sclerodermatous graft-versus-host disease, systemic sclerosis, Parkinson's, and COPD. With such a fundamental action and broad-spectrum activity, I believe that studying niclosamide in all its manifestations, discovering if and to what extent it can contribute positively to disease control (and also where it can't), formulating it as effective therapeutics, and testing them in preclinical and clinical trials is a career builder for our next generation(s).The article is divided into two parts: Part I introduces niclosamide and other proton shunts mainly in cancer and viral infections and reviews an exponentially growing literature with some concepts and physicochemical properties that lead to its proton shunt mechanism. Part II focuses on repurposing by reformulation of niclosamide. I give two examples of “carrier-free formulations”, — one for cancer (as a prodrug therapeutic of niclosamide stearate for i.v. and other administration routes, exemplified by our recent work on Osteosarcoma in mice and canine patients), and the other as a niclosamide solution formulation (that could provide the basis for a preventative nasal spray and early treatment option for COVID19 and other respiratory virus infections).My goal is to excite and enthuse, encourage, and motivate all involved in the drug development and testing process in academia, institutes, and industry, to learn more about this interesting molecule and others like it. To enable such endeavors, I give many proposed ideas throughout the document, that have been stimulated and inspired by gaps in the literature, urgent needs in disease, and new studies arising from our own work. The hope is that, by reading through this document and studying the suggested topics and references, the drug delivery and development community will continue our lineage and benefit from our legacy to achieve niclosamide's potential as an effective contributor to the treatment and control of many diseases and conditions.

An empirical study on the factors influencing the new product development process in Indian automobile industries

Automobile manufacturing industries are looking at innovative ways to improve their company processes globally to maintain profitability in an increasingly complicated and competitive global market. There is fierce competition in the automotive business, which is evolving quickly. A crucial constituent of an organization’s success, survival, and vitality in such industries is the process of new product development. Several studies have been conducted to investigate the success factors of the new product development process in the Automobile industry. This research work tested the hypothesis that factors influence the process of new product development in the Automobile manufacturing industries of Maharashtra. The evidence was collected from higher officials of respective industries. The findings show that market orientation, market competition, and organizational culture have a significant impact on the New Product Development Process in the Automobile Manufacturing industry. The result of this study also shows that the role of governance and organization competence and resources do not impact the New Product Development Process. This suggests that management in the Automobile manufacturing industry strategy should focus on all the possible influential factors during the process of product development.

Transformer enhanced by local perception self-attention for dynamic soft sensor modeling of industrial processes

The use of dynamic soft sensor modeling methods to mine the time-varying and dynamic characteristics of industrial process data is of great significance for improving production efficiency and quality, given the rapid development of industrial processes and the increasing prominence of dynamic changes in the production process. However, existing dynamic soft sensor methods have limited long-term memory capacity, making it difficult to capture the long dynamic dependence, which can severely affect the results of the soft sensor model. To address this issue, we propose a dynamic soft sensor model based on local perception transformer, where the transformer is applied to achieve global perception of the variables. Through the application of the self-attention mechanism in the transformer encoder, the dynamic tracking and prediction of parameters can be realized by assigning different weights to the process variables and quality variables at different time steps, thereby adapting to the time-varying nature of the process. Additionally, convolution is used to generate a Query and Key in the self-attention mechanism, thereby enhancing local information learning. The proposed dot product self-attention calculation method effectively utilizes local information, thereby reducing the potential impact of abnormal data at a certain moment. Furthermore, by utilizing LSTM to extract time series information, the final prediction result was obtained. In soft sensor modeling experiments of the sulfur recovery unit and debutanizer tower, our proposed model demonstrated higher prediction accuracy compared to other methods, such as SVR, MLP, LSTM, CNN + LSTM, and vanilla transformer.

Continuous Synthesis of Nanoscale Emulsions by Vapor Condensation (EVC).

Emulsions are widely used in many industrial applications, and the development of efficient techniques for synthesizing them is a subject of ongoing research. Vapor condensation is a promising method for energy-efficient, high-throughput production of monodisperse nanoscale emulsions. However, previous studies using this technique are limited to producing small volumes of water-in-oil dispersions. In this work, a new method for the continuous synthesis of nanoscale emulsions (water-in-oil and oil-in-water) is presented by condensing vapor on free-flowing surfactant solutions. The viability of oil vaporization and condensation is demonstrated under mild heating/cooling using diverse esters, terpenes, aromatic hydrocarbons, and alkanes. By systematically investigating water vapor and oil vapor condensation dynamics on bulk liquid-surfactant solutions, a rich diversity of outcomes, including floating films, nanoscale drops, and hexagonally packed microdrops is uncovered. It is demonstrated that surfactant concentration impacts oil spreading, self-emulsification, and such behavior can aid in the emulsification of condensed oil drops. This work represents a critical step toward advancing the vapor condensation method's applications for emulsions and colloidal systems, with broad implications for various fields and the development of new emulsion-based products and industrial processes.

Deep hybrid modeling of a HEK293 process: Combining long short-term memory networks with first principles equations.

The combination of physical equations with deep learning is becoming a promising methodology for bioprocess digitalization. In this paper, we investigate for the first time the combination of long short-term memory (LSTM) networks with first principles equations in a hybrid workflow to describe human embryonic kidney 293 (HEK293) culture dynamics. Experimental data of 27 extracellular state variables in 20 fed-batch HEK293 cultures were collected in a parallel high throughput 250 mL cultivation system in an industrial process development setting. The adaptive moment estimation method with stochastic regularization and cross-validation were employed for deep learning. A total of 784 hybrid models with varying deep neural network architectures, depths, layers sizes and node activation functions were compared. In most scenarios, hybrid LSTM models outperformed classical hybrid Feedforward Neural Network (FFNN) models in terms of training and testing error. Hybrid LSTM models revealed to be less sensitive to data resampling than FFNN hybrid models. As disadvantages, Hybrid LSTM models are in general more complex (higher number of parameters) and have a higher computation cost than FFNN hybrid models. The hybrid model with the highest prediction accuracy consisted in a LSTM network with seven internal states connected in series with dynamic material balance equations. This hybrid model correctly predicted the dynamics of the 27 state variables (R2 = 0.93 in the test data set), including biomass, key substrates, amino acids and metabolic by-products for around 10 cultivation days.

Research on the development strategy selection of the new energy vehicle industry from the perspective of green credit-Based on the foursquare evolutionary game analysis.

Developing new energy vehicles is vital to promote green development and the harmonious coexistence of humans and nature. It is also the only way to help China move from a significant automobile country to a powerful automobile country. Based on the background of the "recession" of government subsidies and considering the importance of green credit in promoting green and low-carbon transformation, this paper constructs a four-party evolutionary game model that includes government, automotive companies, banks, and consumers to analyze the stability of the strategic choices of various parties in the development process of the new energy vehicle industry. It uses MATLAB simulation tools to analyze the impact of relevant factors on system stability. The research shows that: (1) The government's subsidy mechanism significantly promotes the development of the new energy vehicle industry. Still, there is a subsidy threshold, beyond which the effect will weaken and quickly bring financial pressure. (2) With the gradual decline of government subsidies, the bank's green credit policy has a specific policy complementary effect on the decline of government subsidies. (3) Considering that costs and benefits are the main influencing factors for automotive companies and consumers' strategic choices, the impact of factors such as the punishment of violations, adjustment of subsidy policies, and consumers' environmental awareness must also be paid attention to.

Research on industrial structure adjustment and spillover effect in resource-based regions in the post-pandemic era.

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development.

Monitoring Aging Effects in Graphite Bisulfates by Means of Raman Spectroscopy

Graphite bisulfate (GBS) compounds consist of graphite layers intercalated by HSO4− ions and H2SO4 molecules. Owing to electrostatic interactions with the graphene plane, HSO4− ions cause point defects in the graphite’s crystalline structure, while H2SO4 molecules are free to move via diffusion in the spaces between the adjacent graphite sheets and segregate to form linear defects. In the present work, we report the results of our investigation using Raman spectroscopy on the temporal evolution of such defects on selected GBS samples over 84 months. Two characteristic lengths correlated with the average distance between defects have been estimated and their evolution with aging was investigated. The results show a decrease in the density of point-like defects after aging, regardless of the pristine structural configuration of the GBS samples, revealing a structural instability. This study can provide significant information for the technological development of industrial processes aimed to produce expanded graphite based on GBS precursors, where the aging of GBS is known to influence the efficiency and quality.

IMPROVEMENT OF THE MANAGEMENT SYSTEM OF FACTORS THAT HINDER THE DEVELOPMENT OF THE NON-OIL INDUSTRY BASED ON INTERNATIONAL EXPERIENCE

The study of the problems of improving the mechanism of the management of the factors that slow down the development of the non-oil industry confirms the instability of the development rates of the Azerbaijani industry in 2005-2021, the disparities in the development of the industry in the production and processing areas, as well as in the regions. As a result of the study, the classification of internal and external factors that hinder the development of the non-oil industry is justified. Application of ISO standards in enterprises operating for the creation of a non-oil industry based on innovative economy, a new concept of regulation of production activities based on the data of technical projects, technical and economic justifications and project estimates were presented as the main direction of improving the management system of factors that hinder the development process of the non-oil industry. The relevance of the subject. In recent years, factors such as creating an inter-sector balance and effective use of natural and material resources have played an important role in ensuring economic stability in our country, but it is necessary to solve the economic and institutional regulation issues related to the development of the non-oil sector of the industry. Because ensuring the development of the non-oil sector has been set as a priority direction and main task of the state’s economic policy. The main goal in the implementation of the specified task is to increase the level of welfare of the population, transition to an export-oriented economy and improve the competitiveness of the economy. From this point of view, the relevance of the research of the subject is not in doubt. The purpose of the article. The main goal of the research is to create an effective management structure, which ensures the elimination of obstacles that slow down the development of this section of the industry, taking into account the role of the non-oil industrial sector in ensuring the sustainable development of the country’s economy and raising the standard of living of the population, through the formation and evaluation of a qualitatively new model of sustainable economic development of added value growth and structural changes in production areas and enterprises. Elucidation of practical aspects of using the concepts «technical structure of production», «organic structure of capital and turnover rate» to improve the management system of non-oil industries and enterprises, which are considered as objects of study of economic theory, is a priority direction of research. Research methods. The article was written on the basis of scientific research methods which includes theoretical analysis, systematic analysis, statistical analysis, generalization, comparative structural analysis, etc. Scientific innovation. In the article, based on the analysis of the production structure and current situation of the non-oil industry in 2005-2021, the classification of the obstacles that slow down the development of the industry was justified for the first time, and specific proposals for their elimination were put forward. Acknowledging the dependence of solving issues such as the application of ISO standards in the non-oil industry sector and the admission of the Republic of Azerbaijan to the World Trade Organization on the condition of ensuring the quality and safety of goods and services, determination of the technical structure of production on the basis of project-estimate documents and proposals for regulating the distribution of income (profit) according to the capital structure and turnover rate should be evaluated as innovative development directions of management in the industry.

Research on Fine Cost Control of Civil Engineering Works Supported by Building Information Modeling

Abstract The problems of cost control in the development process of the construction industry are endless, and cost control, as a core task in the process of project management, has a decisive role in the realization of project economic benefits. This paper combines the DEMATEL method and WBS work breakdown structure to screen and decompose the factors affecting cost under the cost control theory. Then, BIM5D technology is introduced to construct a refined cost control model based on the combination of the earned value method and BIM technology, in which the BIM-5D model can become its grassroots database and combined with the earned value method to provide the basic data for cost monitoring, cost early warning, cost correction and cost prediction, to realize an effective and refined control of costs. The case study shows that enterprise infrastructure, human resource management, internal logistics, procurement and bidding, cooperative and competitive relationships, technology development, project construction, completion and acceptance, and subsequent maintenance services all affect civil engineering costs. The control method can effectively control the construction progress and cost status, can play a good effect on the schedule-cost synergistic control, and provide support for the project management decisions of the constructor in the construction stage.

Exploration of Talent Cultivation Mode of Engineering Green Building Professionals under the Guidance of “Dual Carbon” Objective

Abstract Under the dual-carbon background, green building is a revolution in the development process of the construction industry, which has a far-reaching impact on the transformation of people’s concept of life and employment. This paper is oriented to the characteristics of the traditional construction industry and constructs the training mode for innovative green building professionals based on professional setting and practical ability. To verify its effectiveness, the fuzzy comprehensive evaluation method is utilized to determine the affiliation function and construct the evaluation system for talent cultivation mode. The evaluation index weights are determined using the improved entropy weight method at the same time. In the job demand analysis, the demand for sustainability design positions has grown the most, rising from 1,003 in 2005 to 5,172 in 2020, which is 5.16 times the original number. It shows that the number of positions related to low-carbon energy in the construction industry is increasing. In addition, from the perspective of talent cultivation mode, the average difference between the two different construction talent cultivation modes in the talent cultivation concept is the largest, .911. The average difference between the two modes in terms of students’ sense of identity is 1.345, and the significance of the difference is 0.000<0.005. Therefore, the green construction talent cultivation mode constructed in this paper can effectively strengthen the students’ practical ability of green construction and adapt to the current status quo of construction industry positions. Adjust to the current status of construction industry positions.

Bio-bleaching of ankara pulp with xylanase-producing bacterial consortium for sustainable handmade paper production

The paper industry faces two critical challenges: the scarcity of raw materials and the environmental impact of chemical waste pollution. Addressing the first challenge involves harnessing alternative, sustainable raw materials, while the second challenge can be mitigated through the adoption of bio-bleaching processes, which significantly reduce chemical consumption while enhancing paper brightness and quality. This study proposes a solution to both challenges by using non-woody Calotropis procera (Ankara) and a xylanase-producing microbial consortium for sustainable handmade paper production, a combination not extensively explored in prior research. To evaluate this approach, the process was divided into three stages. In stage I, Ankara fibre was pulped through open hot digestion. In stage II, the pulp was subjected to bio-bleaching in two experimental setups: Set I (without sucrose) and Set II (with sucrose) for 5 days. In stage III, chemical bleaching was used to improve the final brightness of the treated pulps. A novel comparison was made between the bio-bleaching efficiency of an individual isolate g5 (BI) and a bacterial consortium (BC). This research highlighted that bio-bleaching with the consortium effectively removed lignin (140±60 mg/l) and colour (1830±50 PCU), especially in the presence of sucrose, compared to using a single xylanase isolate. Pulp residue/filtrate collected at each stage was estimated based on parameters such as colour and lignin content. After stage III (chemical bleaching), the release of colour and lignin in pulp filtrate was higher in BI compared to BC, indicating the consortium's effectiveness during bio-bleaching, which leaves fewer degradable lignin structures for the chemical bleaching stage. Papers crafted from consortium-treated pulp also exhibited higher brightness than those treated with the isolate. This study reveals the synergistic effect of microbial consortia, leading to more efficient lignin degradation and enhanced bio-bleaching capabilities, supporting the development of greener industrial processes. Ultimately, this study demonstrates a unique and eco-friendly approach to papermaking, combining C. procera and enzymatic bio-bleaching to reduce dependency on hazardous chemicals and support sustainable industry practices.

Molecular structure and composition elucidation of an industrial humin and its fractions.

Humins, (side-)products of the acid-catalysed dehydration of carbohydrates, will be produced in substantial quantities with the development of industrial biorefining processes. Most structural knowledge about such humins is based on synthetic model humins prepared at lab-scale from typical carbohydrate(-derived) compounds. Here, we report the first extensive characterisation study of an industrial humin. The soluble humin was generated from pilot plant-scale methanolic cyclodehydration of D-fructose to 5-methoxymethyl-2-furfural (MMF), as part of the Avantium YXY® process to produce FDCA. Purification of the industrial humin followed by fractionation allowed isolation of a water-insoluble, high molecular weight fraction (WIPIH) and a water-soluble, low-to-middle molecular weight soluble fraction (WES). Characterisation by elemental analysis, thermogravimetry, IR and NMR spectroscopy and size exclusion chromatography provided a detailed picture of the humin structure in both fractions. Aided by a comprehensive NMR spectral library of furanic model compounds, we identified the main furanic building blocks and inter-unit linkages and propose a structure for this industrial humin sample. The WIPIH and WES fractions were found to be composed of furanic rings interconnected by short aliphatic chains containing a wide range of functionalities including alcohols, ethers, carboxylic acids, esters, aldehydes and ketones. The low level of crosslinking and high functional group content of the industrial humin differ from the more extensively studied, (highly over-)condensed synthetic model humins, towards which they can be considered intermediates. The structural and compositional insights into the nature of an actual industrial humin open up a broad spectrum of valorisation opportunities.

Designing the Operator of the Future: The Architecture of Human Digital Twin Systems

The central role that the human operator assumed in industrial design and development processes, driven by Industry 5.0 principles, has paved the way for the creation of new human-centric system architectures. This paper discusses the practical implications regarding the deployment of a Human Digital Twin-based system in the manufacturing environment. It provides a proof-of-concept of the architecture for the implementation of the twinning process, starting from the investigation of the most suitable hardware selection based on the desired outcomes to build up the human monitoring phase. We analyze three management decision-making levels to determine the scalability of the proposed architecture for strategical, technical, and operational managerial strategies. This research aims to propose some technological selection criteria, based on the main characteristics of the available technological acquisition devices, to determine the most suitable sensors for the creation of the physical twinning monitoring process.