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At least 253 records · Page 14

Enabling Industrial Re-Use of Large-Format Additive Manufacturing Molding and Tooling

Large-format additive manufacturing (LFAM) is an enabling manufacturing technology capable of producing large parts with highly complex geometries for a wide variety of applications, including automotive, infrastructure/construction, and aerospace mold and tooling. In the past decade, the LFAM industry has seen widespread use of bio-based, glass, and/or carbon fiber reinforced thermoplastic composites which, when printed, serve as a lower-cost alternative to metallic parts. One of the highest-volume materials utilized by the industry is carbon fiber (CF)-filled polycarbonate (PC), which in out-of-autoclave applications can achieve comparable mechanical performance to metal at a significantly lower cost. Previous work has shown that if this material is recovered at various points throughout the manufacturing process for both the lab and pilot scale, it can be mechanically recycled with minimal impacts on the functional performance and printability of the material while significantly reducing the feedstock costs. End-of-life (EOL) CF-PC components were processed through industrial shredding, melt compounding, and LFAM equipment, followed by evaluation of the second-life material properties. Experimental assessments included quantitative analysis of fiber length attrition, polymer molecular weight degradation using gel permeation chromatography (GPC), density changes via pycnometry, thermal performance using dynamic mechanical analysis (DMA), and mechanical performance (tensile properties) in both the X- and Z-directions. Results demonstrated a 24.6% reduction in average fiber length compared to virgin prints, accompanied by a 21% decrease in X-direction tensile strength and a 39% reduction in tensile modulus. Despite these reductions, Z-direction tensile modulus improved by 4%, density increased by 6.8%, and heat deflection temperature (HDT) under high stress retained over 97% of its original value. These findings underscore the potential for integrating mechanically recycled CF-PC into industrial LFAM applications while highlighting the need for technological innovations to mitigate fiber degradation and enhance material performance for broader adoption. This critical step toward circular material practices in LFAM offers a pathway to reducing feedstock costs and environmental impact while maintaining functional performance in industrial applications.

additive manufacturing↗

Staying Competitive in Clean Manufacturing: Insights on Barriers from Industry Interviews

While industrial emissions research has historically focused on energy-intensive sectors like steel, cement, and chemicals, this study addresses a critical gap by examining barriers across all the manufacturing industry in the U.S. Sectors like food processing, retail, plastics, and transportation face unique challenges distinct from heavy industry, operating on thin margins with limited bargaining power while experiencing heightened consumer and stakeholder pressure for improved environmental responsibility. Through structured interview data collection process and using quantitative ratings and qualitative analysis, this research identifies and categorizes emission reduction barriers across four key themes: financial, technical, organizational, and regulatory. Unlike energy-intensive industries that may pursue hydrogen or carbon capture technologies, discrete manufacturing industry like automotive, electrical and electronics, and machine manufacturers typically focus on energy efficiency, electrification of thermal processes, and alternate fuel switching, solutions better aligned with their lower-temperature processes and distributed facility profiles. The study’s primary contribution lies in documenting specific barrier manifestations within organizations and identifying proven mitigation strategies that companies have successfully implemented or observed among peers.

business competitiveness↗

The Industrial Efficiency and Decarbonization Office

The Industrial Efficiency and Decarbonization Office (IEDO) supports innovation technologies and the adoption of practices to enable the industrial sector to cost-effectively reduce greenhouse gas (GHG) emissions. IEDO and its programs are critical to putting the Nation on a pathway to reduce CO2 emissions by 50% by 2030 when compared to 2005 levels, and to achieve net-zero carbon emissions by 2050. With 30% of primary energy-related emissions attributable to the industrial sector, IEDO builds upon a foundation of energy efficiency as a decarbonization pathway to include process electrification, use of low carbon fuels and feedstocks, and carbon capture to meet industrial emissions reductions targets. IEDO provides planning, management, and direction necessary for a balanced national program of research, development, demonstration, technical assistance, and workforce development to drive energy, materials and production efficiency, and decarbonization across the industrial sector.

Energy-Intensive Industries, Cross-Sector Technolo↗

An Industrial Perspective of Research Within the DISTINCTIVE Program - 18045

UK Engineering and Physical Sciences Research Council (EPSRC) and three industrial partners, the Nuclear Decommissioning Authority (NDA), the National Nuclear Laboratory (NNL) and Sellafield Ltd (SL) are supporting the DISTINCTIVE (Decommissioning, Immobilisation and Storage Solutions for Nuclear Waste Inventories) consortium of eleven universities to carry out research in four theme areas of importance to the UK nuclear industry: Advanced Gas-cooled Reactor (AGR), Magnox and exotic spent fuels; PuO{sub 2} and fuel residues; legacy ponds and silo wastes; and structural integrity. This paper describes the main industry challenges in each of these theme areas and some of industry led activities to address these challenges, and provides examples of where the DISTINCTIVE research output is assisting the nuclear industry in meeting these challenges. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Retooling a Trade Association in a Challenged Industry: The Nuclear Energy Institute Story - 18503

The U.S. Nuclear industry is facing significant challenges to maintain economic competitiveness in an electricity supply sector where advances in natural gas, wind, and solar technologies are reshaping the marketplace. As clean and reliable baseload generation, nuclear still has a valuable role to play. But in order for the power of the atom to remain available for meeting the nation's energy, environmental, and national security needs, it will be imperative that industry leadership innovate and become more efficient at a pace that matches the competition. Industry leaders rely, to a large extent, on their trade association - the Nuclear Energy Institute (NEI) - to be the prime mover in championing initiatives that will enable a successful future. NEI realized that, in the face of an increasingly difficult economic situation, it must become both leaner and more forward looking - it would have to extend its reach and influence while at the same time reigning in costs to its membership. Therefore, on January 17, 2017 NEI completed a restructuring to improve member value and organizational effectiveness. This restructuring was designed in recognition that the nuclear industry is at a pivotal time, and NEI had a unique opportunity to change its trajectory and underline the importance of nuclear energy's role in the nation's critical infrastructure. NEI is now better positioned to support the existing reactor fleet, promote commercialization of advanced reactors, and drive American leadership in commercial nuclear exports and technology around the world. NEI began this restructuring in the fall of 2016 when it consolidated Government Affairs, Communications, Policy and Public Affairs under a new External Affairs function. The January 2017 action extended that effort across the remainder of the organization, ensuring that the organization is highly aligned, member-focused and results driven. The new NEI takes pride in the fact that it is comprised of talented employees who are passionate about nuclear energy and can make a difference for our membership. With this team in place, NEI looks forward to advancing the interests of the nuclear industry while contributing to a safer, cleaner and more productive world. This paper will examine the details of how this new organization was constructed, provide an overview of the National Nuclear Energy Strategy it developed to guide its efforts, examine the trials and tribulations that come along with disruptive change, and reflect on what has been accomplished in the retooled organizations first year. (authors)

99 GENERAL AND MISCELLANEOUS↗

Engineering Out Industry 4.0 Cyber Risk Presentation for EnCyCriS

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

99 GENERAL AND MISCELLANEOUS↗

Engineering Out Industry 4.0 Cyber Risk

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

42 - ENGINEERING↗

Chapter 2: Genetics of Unstudied Thermophiles for Industry

Thermophilic organisms hold great potential for industry due to their numerous advantages in biotechnological applications such as higher reaction rate, higher substrate loading, decreased susceptibility to reaction contamination, energy savings in industrial fermentations, and ability to express thermostable proteins that can be utilized in many important industrial processes. Bioprospecting for thermophiles will continue to reveal new enzymatic and metabolic paradigms with industrial applicability. In order to translate these paradigms to production scale, routine methods for microbial genetic engineering are needed, yet remain to be developed in many newly isolated thermophiles. Major challenges and recent developments in the establishment of reliable genetic systems in thermophiles are discussed. Here, we use a hyperthermophilic, cellulolytic bacterium, Caldicellulosiruptor bescii, as a case study to demonstrate the development of a genetic system for an industrially useful thermophile, describing in detail methods for transformation, genetic tool utilization, and chromosomal modification using targeted gene deletion and insertion techniques.

93 SC - Biological and Environmental Research (BER↗

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs

The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work.

Calix, Ricardo↗

Risk Assessment of Industrial Microbes Using a Terrestrial Mesocosm Platform

Abstract Industrial microbes and bio-derived products have emerged as an integral component of the bioeconomy, with an array of agricultural, bioenergy, and biomedical applications. However, the rapid development of microbial biotechnology raises concerns related to environmental escape of laboratory microbes, detection and tracking thereof, and resultant impact upon native ecosystems. Indeed, though wild-type and genetically modified microbes are actively deployed in industrial bioprocesses, an understanding of microbial interactivity and impact upon the environment is severely lacking. In particular, the persistence and sustained ecosystem impact of industrial microbes following laboratory release or unintentional laboratory escape remains largely unexplored. Herein, we investigate the applicability of soil-sorghum mesocosms for the ecological risk assessment of the industrial microbe, Saccharomyces cerevisiae . We developed and applied a suite of diagnostic and bioinformatic analyses, including digital droplet PCR, microscopy, and phylogenomic analyses to assess the impacts of a terrestrial ecosystem perturbation event over a 30-day time course. The platform enables reproducible, high-sensitivity tracking of S. cerevisiae in a complex soil microbiome and analysis of the impact upon abiotic soil characteristics and soil microbiome population dynamics and diversity. The resultant data indicate that even though S. cerevisiae is relatively short-lived in the soil, a single perturbation event can have sustained impact upon mesocosm soil composition and underlying microbial populations in our system, underscoring the necessity for more comprehensive risk assessment and development of mitigation and biocontainment strategies in industrial bioprocesses.

09 BIOMASS FUELS↗

Pathway to Decarbonization Through Industrial Energy Efficiency: Micro and Macro Perspectives from Compressed Air Usage

Abstract Energy audits directly provided the industrial sector with reduced energy costs and avoided emissions. Still, they also lead to far-reaching indirect and induced local, regional, and national benefits. This paper aims to present the techno-economic-environmental analysis to achieve decarbonization through implementing industrial energy efficiency at micro and macro levels. An integrated techno-economic-environmental methodology is developed. Case studies of micro-level carbon reduction efforts through industrial energy efficiency technologies are presented. The broader macroeconomic and environmental effects of technology on society are analyzed using data from 206 energy audits of industrial compressed air systems conducted over 13 years. The impacts show that energy-efficient improvements lead to direct cost savings for manufacturers, boost economic activity across sectors, and affect carbon dioxide emissions both short-term and long-term in the region. Given their extensive benefits, energy audits significantly influence policymaking. We devised a methodology to link micro-level energy audit data with macroeconomic and environmental analyses to quantify these cascading benefits. The economic scenario analysis shows that $228 M has been saved from direct industrial energy savings from implementing all compressed air recommendations in the studied periods and the region. In addition, the investment made through manufacturers would create 2,025 jobs and $383 M annually, cascading regional economic impacts. The environmental analysis shows that the regional manufacturers have directly avoided about 2.8 M metric tons of carbon dioxide emissions.

Engineering↗

Wastewater hydrogen nexus (WwHeN): Greening the wastewater industry via integration with the hydrogen economy

As industries rally toward achieving net zero emissions, hydrogen and hydrogen-based fuels are emerging as key players in decarbonization efforts. Although the primary technology for producing renewable natural gas has been well implemented in the wastewater industry, the “decarbonization based goal setting” is trailing. This perspective assimilates existing literature presented in other contexts to highlight the need for framing the decarbonization dialog by using green hydrogen as a potential pathway for the wastewater industry. Specifically, we note the importance of (a) developing the decarbonization or net zero focus in the wastewater industry, and (b) colocating the wastewater industry with hydrogen production facilities. Finally, we also delve into technological, cost, and operational considerations to understand the readiness level of key stakeholders to identify future research and development opportunities for the wastewater hydrogen nexus.

08 HYDROGEN↗

Annual and seasonal variability of metals and metalloids in urban and industrial soils in Alcalá de Henares (Spain)

Contamination of urban and industrial soils with trace metals has been recognized as a major concern at local, regional and global levels due to their implication on human health. In this study, concentrations of aluminum (Al), arsenic (As), beryllium (Be), cadmium (Cd), chromium (Cr), manganese (Mn), nickel (Ni), lead (Pb), tin (Sn), thallium (Tl), vanadium (V) and zinc (Zn) were determined in soil samples collected in Alcalá de Henares (Madrid, Spain) in order to evaluate the annual and seasonal variation in their levels. The results show that the soils of the industrial area have higher metals concentrations than the urban area. Principal component analysis (PCA) revealed that the two principal sources of trace metal contamination, especially Cd, Cu, Pb, and Zn in the urban soils of Alcalá can be attributed to traffic emissions, while As, Ni and Be primarily originated from industrial discharges. The seasonal variation analysis has revealed that the emission sources in the industrial area remain constant with time. However, in urban areas, both emissions and emission pathways significantly increase over time due to ongoing development. Currently, there is no hypothesis that explains the small seasonal fluctuations of trace metals in soils, since there are many factors affecting this. Owing to the fact that urban environments are becoming the human habitat, it would therefore be advisable to monitor metals and metalloids in urban soils because of the potential risks to human health. - Highlights: • Anthropogenic activities may affect the seasonal metal variation in Alcalá's soils. • Weather characteristics may also influence the seasonal metal variation in soils. • Alcalá's continual urban growth may have increased the levels of metals in its soils. • Metal variability in Alcalá's industrial soils might be dependent on their sources. • High soil metal content might make it difficult to identify temporal variation.

54 ENVIRONMENTAL SCIENCES↗

Recycling process for recovery of gallium from GaN an e-waste of LED industry through ball milling, annealing and leaching

Waste dust generated during manufacturing of LED contains significant amounts of gallium and indium, needs suitable treatment and can be an important resource for recovery. The LED industry waste dust contains primarily gallium as GaN. Leaching followed by purification technology is the green and clean technology. To develop treatment and recycling technology of these GaN bearing e-waste, leaching is the primary stage. In our current investigation possible process for treatment and quantitative leaching of gallium and indium from the GaN bearing e-waste or waste of LED industry dust has been developed. To recycle the waste and quantitative leaching of gallium, two different process flow sheets have been proposed. In one, process first the GaN of the waste the LED industry dust was leached at the optimum condition. Subsequently, the leach residue was mixed with Na{sub 2}CO{sub 3}, ball milled followed by annealing, again leached to recover gallium. In the second process, the waste LED industry dust was mixed with Na{sub 2}CO{sub 3}, after ball milling and annealing, followed acidic leaching. Without pretreatment, the gallium leaching was only 4.91 w/w % using 4 M HCl, 100 °C and pulp density of 20 g/L. After mechano-chemical processing, both these processes achieved 73.68 w/w % of gallium leaching at their optimum condition. The developed process can treat and recycle any e-waste containing GaN through ball milling, annealing and leaching. - Highlights: • Simplest process for treatment of GaN an LED industry waste developed. • The process developed recovers gallium from waste LED waste dust. • Thermal analysis and phase properties of GaN to Ga{sub 2}O{sub 3} and GaN to NaGaO{sub 2} revealed. • Solid-state chemistry involved in this process reported. • Quantitative leaching of the GaN was achieved.

54 ENVIRONMENTAL SCIENCES↗

Decarbonization of the Chemical Industry Through Electrification: Barriers and Opportunities

The chemical industry is a major source of economic productivity and employment globally and among the top 3 industrial sources of greenhouse gas (GHG) emissions, along with steel and cement. As global demand for chemical products continues to grow, there is an urgency to develop and deploy sustainable chemical production pathways and to reconsider continued investment in current emission-intensive production technologies. This perspective describes the challenges and opportunities to decarbonize the chemical industry via electrification powered by low-carbon electricity supply, both in the near term and long term, and it discusses four technological pathways ranging from the more mature direct substitution of heat with electricity and use of hydrogen to technologically less mature, yet potentially more selective, approaches based on electrochemistry and plasma. Finally, we highlight the key elements of integrating an electrified industrial process with the power sector to leverage process flexibility to reduce energy costs of chemical production and provide valuable power grid support services. Unlocking such plant-to-grid coordination and the four electrification pathways has significant potential to facilitate rapid and deep decarbonization of the chemical industry sector.

chemical synthesis↗

Emission factors of industrial boilers burning biomass-derived fuels

Boilers are combustion devices that provide process heat and are integral to many industrial facilities. Historically, outside of the pulp and paper industry, most boilers burned fossil fuels, although interest in decarbonization has been leading to an increased use of renewable fuels in boilers. These boilers, including those in the biorefineries, are often large sources of air pollutant emissions, and the characterization of these emissions is critical to obtaining air permits and ensuring protection of the surrounding air quality. Several industrial boilers and new biorefineries allow utilization of biomass-derived fuels (e.g. wastewater sludge, lignin, etc.) produced during their operation as a fuel for the boiler to meet process energy needs. However, there is limited empirical data on emission factors for the burning of unconventional fuels, such as solid-gas mixtures containing biomass residues. To fill this gap, we carry out a comprehensive data survey, collecting information on emission factors for boilers burning either a single or a mixture of solid and gaseous biomass-derived fuels. We review multiple hard-to-obtain and unconventional data sources, such as air permit applications, stack test data, and industry-sponsored data collection efforts, to compile emission factors for biomass-derived fuels. We then compare this data with wood residue emission factors from the U.S. Environmental Protection Agency’s AP-42 emission factor database. Our results indicate that the emission factors for boilers burning unconventional fuels vary widely depending on the fuel composition, boiler type, and fuel characteristics. Overall, we find that median emission factors of selected biomass-derived fuels are typically lower than those of wood residue boilers in AP-42. The information collected herein could be useful to permitting agencies and industries utilizing boilers who may want to reduce the carbon impact of their facilities by combusting biomass-derived wastes for process energy needs, for more accurate emission estimation for permitting.

09 BIOMASS FUELS↗

Machine learning for reducing noise in RF control signals at industrial accelerators

Industrial particle accelerators typically operate in dirtier environments than research accelerators, leading to increased noise in RF and electronic systems. Furthermore, given that industrial accelerators are mass produced, less attention is given to optimizing the performance of individual systems. As a result, industrial accelerators tend to underperform their own hardware capabilities. Improving signal processing for these machines will improve cost and time margins for deployment, helping to meet the growing demand for accelerators for medical sterilization, food irradiation, cancer treatment, and imaging. Our work focuses on using machine learning techniques to reduce noise in RF signals used for pulse-to-pulse feedback in industrial accelerators. Here we review our algorithms and observed results for simulated RF systems, and discuss next steps with the ultimate goal of deployment on industrial systems.

43 PARTICLE ACCELERATORS↗

Evaluating the carbon capture potential of industrial waste as a feedstock for enhanced weathering

Abstract Limiting anthropogenic global climate warming since the start of the industrial period to less than 2 °C will very likely require both deep and rapid reductions in anthropogenic greenhouse gas emissions and a range of approaches toward carbon dioxide removal (CDR). One prominent CDR approach is enhanced weathering (EW), in which crushed silicate rock is applied on land or in the open ocean to accelerate natural weathering processes that absorb carbon dioxide from Earth’s ocean–atmosphere system. However, in addition to a range of potential environmental, socioeconomic, and ethical issues associated with this pathway, bottlenecks in feedstock sourcing represent a key barrier for deployment of EW at scale. Here, we evaluate the potential of silicate wastes produced from industrial processes—such as steel slag and cement waste—as feedstocks for the EW process. An empirical model that links industrial alkaline waste production to gross domestic product at purchase power parity is developed to forecast waste production in the alternative futures described by the shared socioeconomic pathway (SSP) framework. By incorporating these results into an intermediate-complexity Earth system model, we also explore the impacts of EW using industrial waste on changes to global temperature, ocean pH, and ocean aragonite saturation state, while also quantifying overall CDR efficiency through the end of the century. We estimate a maximum cumulative end-of-century capture potential of ∼400 GtCO 2 for industrial waste, which could represent a significant fraction of the projected CDR requirement of many mitigation scenarios in the SSP framework. However, feedstock-dependent environmental impacts and the technoeconomics of feedstock redistribution may ultimately limit deployment scope.

Xu, Pengxiao (ORCID:0009000633724293)↗