Process Design Research Articles

Prediction of CFD Simulation Results Using Machine-Learning Models and Process Designs Based on Direct Inverse Analysis of the Models

Prediction of CFD Simulation Results Using Machine-Learning Models and Process Designs Based on Direct Inverse Analysis of the Models

Multi-project wafer runs for electronic graphene devices in the European 2D-Experimental Pilot Line project

The commercialization of electronic devices based on graphene has not yet been successful, even 20 years after its first isolation. To this end, the European Commission is supporting research toward establishing a European experimental pilot line for electronic and optoelectronic devices based on graphene and related two-dimensional (2D) materials, namely the Experimental Pilot Line (2D-EPL) project. Here, we report the results obtained during the first and third multi-project wafer (MPW) runs completed at the end of 2022 (MPW run 1) and 2023 (MPW run 3) as an outcome of the 2D-EPL. Test devices were measured across the wafers to assess the device quality and variability before delivering the fabricated dies to the customers. Raman spectroscopy confirmed minimal structural changes in the graphene caused by the fabrication process, while electrical measurements of two different device types verified the device specifications defined in the process design kit.

Automated Transformer Selection for RFIC Design: Accelerating Development with a Comprehensive Database

The design of transformers, a key component of radio frequency integrated circuits (RFICs), is traditionally carried out through an iterative process involving extensive electromagnetic simulations. While process design kits (PDKs) offer tools based on interpolation or fitting equations to simplify parameter estimation, these tools are restricted to standard geometries, leaving designers to manually simulate and optimize custom designs. This approach is inefficient and resource intensive. This paper proposes an automated process to generate a database containing the physical and electrical parameters of a wide range of transformers. This database is part of a tool designed to efficiently identify the desired transformer. To evaluate the tool’s effectiveness in reducing the time required for design, a millimeter-wave (mm-Wave) 69.4–74.2 GHz differential low-noise amplifier (LNA) is designed using GlobalFoundries 45 nm silicon-on-insulator (SOI) technology. This circuit demonstrates a noise figure (NF) of 4.1 dB, a gain of 10.1 dB, an input third-order intercept point (IIP3) of −10.78 dBm, and a power consumption of 4.7 mW from a 0.406 V DC supply. Moreover, the simulated performance achieves these specifications within a highly compact area of 0.12 mm2. The transformer selection process for the circuit takes only a few seconds, whereas the conventional method of manual transformer design and electromagnetic simulation would require a significantly greater amount of time.

Transitional Care Interventions in Improving Patient and Caregiver Outcomes After Discharge: A Scoping Review

Background. Caregivers play a fundamental role in the complexity of the transitional process between different healthcare settings. Current research shows that caregiver preparedness can affect the quality and efficacy of post-hospital care, therefore highlighting the need to integrate caregiver roles into the design of transitional care processes. This study aims to map existing evidence on effectiveness of transitional care interventions in improving post-discharge outcomes, as well as the influence of caregiver involvement on both patients and caregivers’ outcomes. Methods. Referring to PRISMA-ScR guidelines, a systematic search was conducted between January and February 2024 on Scopus, WoS and PubMed. In order to be included in the systematic search, a study was required to use a RCT design, as well as to describe a transitional care intervention targeting caregivers or patient–caregiver dyads applied in the inpatient setting, lastly the study had to include follow-ups after discharge. There were no limitations on the country or publication year. Results. The review has included 51 RCTs of transitional care interventions, discussing caregivers’ roles in improving dyad outcomes after discharge. Although the review highlighted a heterogeneity in the transitional care interventions, it was observed that the interventions shared some common components categorized in the following clusters: need assessments, providing information, psychological support, self-management training, and monitoring or follow-up. Conclusions. This review emphasizes the important role of caregivers in the transition from hospital to home, addressing a significant gap in the literature. It highlights the effectiveness of transitional care interventions in improving patients’ quality of life and functional abilities while reducing caregivers’ burden and depression. Further research should focus on assessing the efficacy of these interventions in relation to healthcare utilization, hospital readmission rates, and emergency department visits.

A dosimetric evaluation using the Monte Carlo method considering geometric variations of the Iodine-125 seed for brachytherapy

The Institute for Energy and Nuclear Research – IPEN-CNEN/SP is uniquely positioned to develop a new source of Iodine-125 for brachytherapy treatment. Therefore, research into the dosimetric process and source design is widely studied. Task Group 43 – TG 43 cites methodologies for dosimetry of sources for brachytherapy, the most used method is Monte Carlo. However, the dosimetric protocol does not mention possible variations in the source geometry after its conception. The investigative focus of the work was to obtain measurements of the Iodine-125 seed during the production stages until completion, quantify them and simulate them using the Monte Carlo method with the MCNP – 4C code, the formalism was in water and a 101x101 matrix was used to calculate the dose point by point. Two variations were chosen: a) seed length; b) nucleus length, using a batch of 100 seeds for each case. 100 simulations were carried out for each variation and one simulation using the reference seed geometry. The following calculations were applied: relative difference to compare variations to the reference; average among the 100 seeds of each batch to calculate the standard deviation. In both cases there was no point that exceeded 4.48% relative difference, and for standard deviation the largest point was 1.6%, while the Type A uncertainty was 0.018% at the largest point.

Precision Processing for Value-Added Fats and Oils

Lipids are key compounds in foods and provide energy and nutrients to the body. They are carriers of aroma and flavor compounds and contribute to structure and texture. Nutritional research has shown that positive effects on human health are derived from the intake of specific lipids. Similarly, food science research has shown that food matrix design benefits from having tailored lipid fractions with specific functions such as melting profiles, crystal structures, and oil-binding capacities. Minor constituents such as polar lipids or waxes also have valuable functional properties such as the ability to stabilize interfaces, facilitate spreadability, provide barriers, or act as organogelators. Coupled with the emergence of new feedstocks such as new plants, microbes, or insects, this has fueled a renewed interest in designing efficient, effective, and environmentally friendly processes to extract and fractionate lipids from feedstocks. Such precision-processing approaches are intended to yield not just bulk oils and fats but also specialty lipids with tailored properties. In this review article, we discuss the extraction and fractionation approaches used to obtain lipid fractions from plants, animals, or microbial fermentation, discuss their properties and functionalities, and highlight process design approaches, with a focus on sustainable extraction technologies. Recent advances in the three main steps in obtaining food lipids are highlighted: (a) crude oil manufacture; (b) refinement; and (c) fractionization. Finally, three case studies of specialty ingredients derived from such precision-processing approaches are presented.

Valorization of fisheries by-products via enzymatic protein hydrolysis: A review of operating conditions, process design, and future trends

Valorization of fisheries by-products via enzymatic protein hydrolysis: A review of operating conditions, process design, and future trends

Energy-efficient process design and optimization of the absorption-based CO2 capture process with a low-pressure flash column for the SMR-based hydrogen production plant

Energy-efficient process design and optimization of the absorption-based CO2 capture process with a low-pressure flash column for the SMR-based hydrogen production plant

Design and global sensitivity analysis of a flexible hydrogen regasification process integrated with liquid air energy storage system

Design and global sensitivity analysis of a flexible hydrogen regasification process integrated with liquid air energy storage system

What is transformative in participatory approaches to territorial agroecological transitions? A systematization of five case studies in Spain

ABSTRACT Participatory processes of agroecological transitions at territorial scales are becoming a widespread practice. However, systematic research based on empirical processes remains scarce. In this paper, we systematize the experiences of five cases of co-design for agroecological transitions in Spain, in different territorial contexts and scales, applying the framework of Local Agroecological Dynamization. The systematization has involved professional facilitators of each project and is based on the primary and secondary data they provided. The systematization describes a sequence of milestones to walk through to implement transformative, participatory processes of transitions and suggests some principles for the design of such processes. The paper highlights two elements that define the transformative character of the cases: the activation of social creativity based on the material and relational features of the territory, and the strengthening of local socio-economic actors in the framework of a plural social subject to promote the transition. More empirical, action-oriented research is needed, in different territorial contexts and long-term processes, to deepen the understanding of such issues.

An effective procedure for optimized design of heat pump distillation process

Research on heat pump-assisted (HP) distillation columns, especially those applied to divided-wall column (DWC), is increasing due to their potential for energy savings in distillation processes. HP systems offer various configurations and multiple decision variables, which increase computational demands across different distillation systems. In this contribution, a heat pump superstructure (HPS) method is developed and proposed that includes five common HP configurations. Combined with an improved differential evolution algorithm, the optimal HP structure in multiple configurations for different optimization tasks is automatically computed. The advantage of HPS method is that it could be incorporated in distillation columns to systematically and simply find an optimum configuration for various separator systems and separation tasks. The HPS effectively achieves optimal design configurations for binary columns, three-component DWCs, and four-component KDWC separation systems under varying pricing standards.

Towards sustainable chemical process design: Revisiting the integration of life cycle assessment

Towards sustainable chemical process design: Revisiting the integration of life cycle assessment

Large language models: Tools for new environmental decision-making.

This study represents the first exploration of Large Language Models (LLMs) in environmental decision-making, examining their potential benefits and limitations. To address environmental issues, we propose and compare two generalizable frameworks: an LLMs-assisted framework that leverages LLMs to augment human expertise and coding in traditional decision workflows, and an LLMs-driven framework that aims to automate optimization. Through a water engineering case study focusing on PFAS control, where Environmental Fluid Dynamics Code (EFDC) was used for water environment simulation, we illustrate how to instantiate these frameworks and assess their performance. The case study reveals generalizable insights about these frameworks. Results indicate that both frameworks can contribute to environmental decision-making optimization to varying degrees, though their applicability differs significantly when facing complex decision scenarios. The LLMs-assisted framework, which effectively regulates flow rates and achieves higher PFAS interception, demonstrates how AI can enhance human decision-making while preserving the essential role of domain expertise and professional judgment. In contrast, the LLMs-driven framework faces challenges in handling complex parameter optimization tasks due to constraints such as context window and maximum output length. The findings emphasize the advantages of integrating Artificial Intelligence (AI) with conventional environmental modeling and management practices. This work confirms a crucial principle: LLMs should enhance rather than replace human expertise, with the ultimate responsibility for environmental decisions remaining with humans. The originality of this research lies in its innovative methodological approach, which leverages process design and prompt engineering to integrate cutting-edge AI with conventional environmental models, establishing a foundation for responsible human-AI collaboration in environmental decision-making. While examining current strengths and limitations, this framework robustly generates optimized environmental decision strategies, marking a new exploration in the field.

Towards a digital twin of primary drying in lyophilization using coupled 3-D equipment CFD and 1-D vial-scale simulations.

A digital twin of lyophilization units was developed to facilitate the scale-up of the lyophilization process from the laboratory to the commercial scale. Our focus was on ensuring successful technology transfer for manufacture of high-quality drug products. Traditionally, lyophilization models have been specific either to the equipment or to the vial. In this study, we integrated the equipment and the vial models in a way that they mutually influenced each other via boundary conditions (two-way coupling). We conducted two sets of calculations. Firstly, we performed steady-state simulations using Computational Fluid Dynamics (CFD) to simulate an ice slab test, which helped determine the equipment capability curve. Secondly, we carried out transient, coupled simulations using a coupled 3-D CFD and 1-D vial scale simulation model to mimic the primary drying phase in a lyophilizer. Using the coupled 3-D CFD and 1-D vial scale model, we were able to determine the product temperature, the sublimation rate and the cycle time based on the temporal and spatial conditions in the lyophilizer. The coupled approach was then applied to capture the effects of process disturbances and failure conditions in the lyophilizer, which enables a more robust process design.

Performance comparison and mechanism analysis of pre-separation-column multi-stage heat exchange and heat pump distillation based on methyl methacrylate purification process design

Performance comparison and mechanism analysis of pre-separation-column multi-stage heat exchange and heat pump distillation based on methyl methacrylate purification process design

Modeling the Performance of an Anaerobic Moving Bed Biofilm Reactor.

Sub-models representing transformation processes by microorganisms and hydrolases, a one-dimensional (1-D) biofilm, and a bioreactor were integrated to simulate organic-matter fermentation and methane (CH4) production in an anaerobic moving bed biofilm reactor (AnMBBR). The integrated models correctly represented all experimental observations and identified mechanisms underlying how and why AnMBBR performance changed when the volumetric loading rate (VLR) of total chemical oxygen demand (TCOD) increased from 3.9 to 19.5 kg CODT/m3-d. The fractional removal of TCOD and CH4 production decreased as the VLR of TCOD increased, in part, due to an increasing biofilm thickness that filled the protected channels in the interior of the plastic carriers and led to a decrease in biofilm surface area and an increase in the mass-transfer boundary layer. Also, the ~25-day duration for each VLR of TCOD was too brief to allow the biofilm to establish a new quasi-steady state with respect to biofilm thickness. The mechanistic understanding of how biofilm characteristics and process performance respond to increased VLR of TCOD can be applied in engineering practice to improve AnMBBR process design and operation.

Identification of Phenolics and Structural Compounds of Different Agro-Industrial By-Products

This study provides a comprehensive analysis of the composition of onion peels, tomato peels, and pistachio green hulls, with a focus on their structural and bioactive compounds. Onion peels, regardless of cultivar, were found to be rich in quercetin and its derivatives, along with other flavonoids and pectin. Tomato peels emerged as a notable source of naringenin (0.52 mg/g in ethanol extract) and rutin (0.24 mg/g in water extract) and showed an unexpectedly high lignin content, comprising nearly 50% of their structural components. Pistachio green hulls demonstrated a high extractive content (63.4 g/100 g), 73% of which were water-soluble. Protocatechuic acid, rutin, and quercetin derivatives were the dominant phenolic compounds in the water extract, while luteolin was most abundant in the ethanol extract. Regarding structural composition, tomato peels and pistachio green hulls shared similarities, exhibiting a high lignin content (53.4% and 33.8%, respectively) and uronic acids (10–15%). In contrast, onion peels were characterized by high levels of glucans (around 38%) and galacturonic acid (33%). The insights from this study pave the way for the design of sustainable and efficient extraction processes, enabling the sequential recovery of valuable bioactive compounds and promoting the valorization of these agro-industrial by-products. Additionally, onion and tomato peels were evaluated as sources of pectin using two extraction methods: conventional acid water extraction and subcritical water extraction. The results revealed significant differences in the pectin composition (53–68% galacturonic acid) and degree of esterification (79–92%) compared to commercial pectin (72.8% galacturonic acid and 68% esterification), highlighting the influence of the raw material and extraction method on the final properties of pectin.

Unraveling the metabolic landscape of Exophiala spinifera strain FM: Model reconstruction, insights into biodesulfurization and beyond.

Exophiala spinifera strain FM, a black yeast and melanized ascomycete, shows potential for oil biodesulfurization by utilizing dibenzothiophene (DBT) as its sole sulfur source. However, the specific pathway and enzymes involved in this process remain unclear due to limited genome sequencing and metabolic understanding of E. spinifera. In this study, we sequenced the complete genome of E. spinifera FM to construct the first genome-scale metabolic model (GSMM) for this organism. Through bioinformatics analysis, we identified genes potentially involved in DBT desulfurization and degradation pathways for hazardous pollutants. We focused on understanding the cost associated with metabolites in sulfur assimilation pathway to assess economic feasibility, optimize resource allocation, and guide metabolic engineering and process design. To overcome knowledge gaps, we developed a genome-scale model for E. spinifera, iEsp1694, enabling a comprehensive investigation into its metabolism. The model was rigorously validated against growth phenotypes and gene essentiality data. Through shadow price analysis, we identified costly metabolites such as 3'-phospho-5'-adenylyl sulfate, 5'-adenylyl sulfate, and choline sulfate when DBT was used as the sulfur source. iEsp1694 encompasses the degradation of aromatic compounds, which serves as a crucial first step in comprehending the pan metabolic capabilities of this strain.

Energy-Related Assessment of a Hemicellulose-First Concept—Debottlenecking of a Hydrothermal Wheat Straw Biorefinery

A hemicellulose-first approach can offer advantages for biorefineries utilizing wheat straw as it combines lignocellulose fractionation and potentially higher added value from pentose-based hemicellulose. Therefore, a tailored hydrothermal concept for the production of xylooligosaccharides and xylan was investigated. The focus was on assessing the energy requirements and potential improvements based on experimental results. The wheat straw pretreatment and the downstream processing of hemicellulose hydrolysate were modeled at a scale of 30,000 tons of wheat straw dry mass per year. The results confirmed that the hydrothermal concept can be implemented in an energy-efficient manner without the need for additional auxiliaries, due to targeted process design, heat integration and a high solids loading during hydrolysis. The resulting specific energy requirements for pretreatment and hydrolysate processing are 0.28 kWh/kg and 0.13 kWh/kg of wheat straw dry mass, respectively. Compared to thermal hydrolysate processing alone, the combination of a multi-effect evaporator and pressure-driven ultrafiltration can reduce the heating and cooling energy by 29% and 44%, respectively. However, the ultrafiltration requirements (e.g., electrical energy, membrane area and costs) depend heavily on the properties of the hydrolysate and its interactions with the membrane. This work can contribute to the commercially viable ramp-up of wheat straw multi-product biorefineries.

Facile Access to Highly Efficient 3D Printing Using Robust Self-Healing CDs/Polymer Hybrids.

3D printing efficiency, as a key indicator of additive manufacturing technology, directly affects its competitiveness in rapid prototyping, small batch production, and even large-scale industrial applications. Compared with traditional manufacturing methods, the high efficiency of 3D printing is often considered a bottleneck, hindering its application across various fields. Herein, a versatile and efficient strategy is proposed, namely, the dimensional reduction printing (DRP) process, to break the obstacle of high efficiency of 3D printing. Specifically, the self-healing CDs/PMMA nanocomposites were constructed via introducing carbon dots (CDs) synthesized by microfluidics into poly(methyl methacrylate) (PMMA) materials. Under the assistance of abundant hydrogen bonding and the entanglement of polymer chains, the fabricated CDs/PMMA nanocomposites exhibited outstanding self-healing properties, which can be utilized as ideal printing inks to achieve a highly efficient 3D printing process through assembling the printed simple 1D and 2D components into complex 3D models. We firmly believe that the DRP strategy opens up an idea for the design of a 3D printing process and points out the direction for the meaningful application of 3D printing technologies.