Complex Design Research Articles

Recent Advances in Additive Manufacturing of Refractory High Entropy Alloys: A Critical Review

Refractory High Entropy alloys (RHEAs) have evolved as a superior multicomponent material having a unique combination of microstructures and mechanical properties. RHEAs are a particular grade of high entropy alloys (HEAs) known for their outstanding high-temperature properties achieved thorough their constituent refractory elements. To date, majority of the RHEAs have been manufactured through several conventional methods, but are limited by certain limitations. Additive manufacturing (AM) has the potential to revolutionize the manufacturing industry by providing excellent opportunities to fabricate RHEAs while providing opportunities for enhancing the design freedom and complex geometrical shapes. As the field is rapidly evolving, a systematic examination of our comprehension is beneficial, and this article attempts to address this issue. To find the right place in industrial markets, additively manufactured RHEAs require further advancements. The present review provides a comprehensive overview of the additively manufactured RHEAs in terms of microstructural characterization, mechanical behaviour and other environmental properties published so far. This review article is presented lucidly with an aim of better understanding for the readers in this domain. To this end, future works and current challenges are also included and discussed briefly.

RUTHENIUM ORGANOMETALLIC COMPOUNDS IN CANCER TREATMENT

Organometallic complexes with ruthenium have shown promise as potential anticancer agents. These complexes represent a class of compounds that can exhibit unique mechanisms of action, and they may offer advantages or overcome some limitations associated with platinum-based drugs, such as cisplatin. Ruthenium-based complexes can have diverse mechanisms of action. They may interact with DNA, proteins, or other cellular components, leading to cytotoxic effects on cancer cells. The versatility of ruthenium coordination chemistry allows for the design of complexes with specific properties. Some cancers that become resistant to platinum-based drugs may still respond to ruthenium-based compounds. This reduced cross-resistance is attributed to differences in the mechanisms of action between platinum and ruthenium complexes. Researchers can design ruthenium complexes to target specific cellular pathways or processes associated with cancer. This targeted approach aims to enhance the selectivity of the treatment for cancer cells while minimizing the impact on normal cells. Ruthenium complexes often have unique structural features that contribute to their stability and reactivity. These features can be tailored to optimize the pharmacological properties of the compounds. Ruthenium-based complexes may be explored in combination with other anticancer agents to achieve synergistic effects and enhance overall treatment efficacy. Ongoing research continues to explore the potential of ruthenium-based organometallic complexes, and preclinical studies have demonstrated promising results. As with any emerging field, further investigations and clinical trials are needed to fully understand the therapeutic potential and safety profiles of these compounds for various types of cancers.

Towards gradient design of TPMS lattices and laser powder bed fusion processing– Role of laser strategies and lattice thickness

The ability to manufacture complex design geometries via Additive Manufacturing (AM) has led to a rapid growth in advancing the design methods, fabrication, and application of Triply Periodic Minimal Surface (TPMS) lattices with minimal surface topologies. Due to its zero-mean curvature, TPMS lattices can be additively manufactured without any sacrificial support structures and offer both design and manufacturing engineers, unprecedented control over the local physical properties (surface area, relative density, etc.) and local mechanical properties (flexural strength, Young’s modulus, etc.). TPMS lattices are of high interest for a wide range of applications such as biomedical implants, energy absorption, and surface fluidic applications such as heat exchangers, and energy storage. Recent advancements in functionally graded TPMS lattice design by varying local lattice geometry has shown to result in different mechanical performance. However, there have been limited studies in understanding the functional grading of AM process conditions (e.g., Laser-Powder Bed Fusion in this study) and lattice sheet thickness to better map the design-processing conditions-properties. The goal of this study is to achieve similar mechanical properties in TPMS sheet lattices with two different TPMS sheet thicknesses by varying laser processing conditions (e.g., contour and hatch conditions in this study). Quasi-static tensile testing of solid samples with corresponding AM conditions and 3-point bending tests of TPMS lattices were performed in accordance with ASTM E8 and ASTM E290, respectively. It was observed that the flexural properties of the 0.75 mm and 0.25 mm TPMS lattices are similar and exhibit different properties with different scan strategies and speed variations under contour-only and hatch-only laser scanning strategies. Also, the 0.75 mm TPMS sheet lattices exhibited 79 % higher flexural stiffness than the 0.25 mm sheet lattices. It was also observed that this observed trend was reversed in the case of tensile properties. Findings from this study can provide new directions towards achieving gradient TPMS lattice designs with varying local mechanical performance by grading the laser scanning strategies to achieve desired mechanical properties and surface topologies.

A simple method and case study of task planning for collaborative design based on FDSM

In multiperson collaborative mechanical product design, unreasonable task allocation can result in excessive coupling between tasks, complex design communication, and rework, particularly in small enterprises and teams that rely primarily on experience. Hence, this study proposes a simple and efficient task-planning method based on a fuzzy design structure matrix (FDSM), which involves single-level task decomposition, three-level number assignment of the coupling relationship, decoupling of the structural tree algorithm, and validation of the optimization results based on the G-value. Design tasks are promptly allocated into a single level based on the functional structure module of the product. The task-correlation degree is quantified based on three levels of numerical values through personal experience to construct an FDSM, the latter of which is decoupled by the correlation degree of the structural tree algorithm to obtain the optimized sequence and allocation of the collaborative design task. Finally, the effectiveness of the planning is verified by calculating the tightness of the corresponding matrix before and after the planning. A task-planning case of a riveting-machine design for capacitor cover plates is established to validate this method.

Customizing Bayesian multivariate generalizability theory to mixed-format tests.

Mixed-format tests, which typically include dichotomous items and polytomously scored tasks, are employed to assess a wider range of knowledge and skills. Recent behavioral and educational studies have highlighted their practical importance and methodological developments, particularly within the context of multivariate generalizability theory. However, the diverse response types and complex designs of these tests pose significant analytical challenges when modeling data simultaneously. Current methods often struggle to yield reliable results, either due to the inappropriate treatment of different types of response data separately or the imposition of identical covariates across various response types. Moreover, there are few software packages or programs that offer customized solutions for modeling mixed-format tests, addressing these limitations. This tutorial provides a detailed example of using a Bayesian approach to model data collected from a mixed-format test, comprising multiple-choice questions and free-response tasks. The modeling was conducted using the Stan software within the R programming system, with Stan codes tailored to the structure of the test design, following the principles of multivariate generalizability theory. By further examining the effects of prior distributions in this example, this study demonstrates how the adaptability of Bayesian models to diverse test formats, coupled with their potential for nuanced analysis, can significantly advance the field of psychometric modeling.

Applying design complexity metrics for post-processing cost modeling in metal additive manufacturing

The recent Additive manufacturing (AM) literature has primarily concentrated on exploring new avenues for improving the current technology and its applicability. It has also delved into research investments aimed at addressing the last remaining prediction challenges associated with current AM processes, particularly focusing to surface quality, accuracy, and internal composition. These limitations can often be mitigated though the application of post-processing techniques. Such techniques are often very costly both in time and monetary terms.When it comes to the impact that shape complexity has on post-fabrication costs for AM parts, a gap in the literature is apparent. In recent years, more attention has been devoted to researching a general shape complexity metric. It has been suggested in the literature to combine multiple of complexity metrics techniques, to reach more comprehensive model. This aspect has not received enough attention in previous works. In addition, the relationship between shape complexity and post-processing costs has not been assessed. And there are no predictive models for post-processing costs based on complexity.In this study, AM shapes for prototyping application are analysed. In this regard, previously established complexity metrics are used, together with expert’s assessments of post-processing costs, to create a model capable of predicting post-processing costs. This is achieved through a regression analysis using costs and complexity metrics values. The result of this research are two regression models, named 7 V and Vol/Sur Models, capable of predicting post-processing costs for AM parts produced through DMLS techniques with SS316L stainless steel powder. The accuracy of the two models is discussed.

Analysis of Combustion Characteristics of Can-Type and Annular-Type Combustion Chamber

Abstract High performance is always desired for the propulsion system and the assortment of a better combustion type is also a vital part of the propulsion system. The analysis of different designs of combustion chambers and comparison of their combustion characteristics. In this paper, the assessment of Can-type and Annular-type combustion chambers and the design developed with SOLIDWORKS software and analysis done with ANSYS FLUENT. The systematic and translucent method approaches reduce the design complexity and time. The combustion with turbulence interface was examined to analyze with precision results, and the analysis specified that the nowadays experiment depends on the behavior of gas exit pressure, temperature, and velocity. Parametric analysis is used to acquire the sizing of the combustion chamber.

Tailored Metal-Based Catalysts: A New Platform for Targeted Anticancer Therapies.

Innovative strategies for targeted anticancer therapies have gained significant momentum, with metal complexes emerging as tunable catalysts for more effective and safer treatments. Rational design and engineering of metal complexes enable the development of tailored molecular structures optimized for precision oncology. The strategic incorporation of metal complex catalysts within combinatorial therapies amplifies their anticancer properties. This perspective highlights the advancements in synthetic strategies and rational design since 2019, showing how tailored metal catalysts are optimized by designing structures to release or in situ synthesize active drugs, leveraging the target-specific characteristics to develop more precise cancer therapies. This review explores metal-based catalysts, including those conjugated with biomolecules, nanostructures, and metal-organic frameworks (MOFs), highlighting their catalytic activity in biological environments and their in vitro/in vivo performance. To sum up, the potential of metal complexes as catalysts to reshape the landscape of anticancer therapies and foster novel avenues for therapeutic advancement is emphasized.

Design, synthesis, and evaluation of some metal ion complexes of mannich base derived from 2-Mercaptobenzimidazole as potential antimicrobial agents

This study aims to prepare new compounds and investigate them spectroscopically and biologically against selected types of positive and negative bacteria and fungi to demonstrate their biological effectiveness. The prepared ligand combining formaldehyde, indole, sulfa benzamide, and 2-mercapto benzimidazole, a Mannich base ligand (L) was synthesized. The six metal ions including Cobalt (II), Nickel (II), Copper (II), Palladium (II), Platinum (IV), and gold (III) have interacted with the ligand and formed new complexes. Different spectroscopic methods, including C.H.N.S., FTIR, UV- Range visible, 1HNMR, 13CNMR, mass spectra, magnetic moment, and molar conductivity were used to suggest the new geometry of the complexes. The result from the infrared spectrum showed that the ligand behaves as tridentate with all prepared complexes. Conductivity analysis revealed the electrolytic nature of palladium, platinum, and gold ions complexes and non-electrolytes. The antibacterial activity of the compounds that were produced was tested using an agar-well diffusion procedure towards two strains of gram-positive as well as two strains of gram-negative bacteria and fungi (Staphylococcus, Streptococcus, Escherichia coli, Pseudomonas aeruginosa, and Candida albicans) respectively at 0.02M. The standard (∆Eo) and (∆Hfo) of ligand and six complexes were calculated using the program Hyper chem 8.0.7. The research established that complexes are more stable than ligands. Calculated HOMO and LUMO and vibration frequencies using (parametric method 3 (PM3)) to find out the active sites in the ligand showed that they can coordinate and note the extent to which the results of theoretical vibrational frequencies are close to the process when calculating the vibrational frequency of the active aggregates.

Stakeholder Opinion Survey and Analysis to Establish Priorities for the Eco-Friendly Design and Operation of Healthcare Plant Production Complexes

Stakeholder Opinion Survey and Analysis to Establish Priorities for the Eco-Friendly Design and Operation of Healthcare Plant Production Complexes

A multi-criteria decision support framework for designing seismic and thermal resilient facades

Facades play a pivotal role in the performance of a building, serving various environmental, structural and operational functions. As climate-induced extreme events become more frequent, developing resilient facades is becoming crucial. Although facades can contribute significantly to the total post-disruption losses, their resilience is not sufficiently addressed in current design approaches. In response to this research gap, this study proposes a multi-criteria decision-making methodology to select optimal facade designs using resilience criteria: resilience loss and economic loss. The framework addresses the complexity of facade design, considering multiple hazards such as earthquakes and heatwaves. For seismic hazard, the facade’s resilience is defined as its ability to mitigate damage. In the case of heat hazard, resilience is assessed based on the ability to keep indoor conditions within a comfortable thermal range. To demonstrate the applicability of the proposed methodology, a case study of an 18-story office building in Izmir (Turkey) is used to compare alternative facade packages. These packages identify the facade design cases, each coupled with a dataset of seismic and thermal fragility curves. Numerical simulations are conducted to derive seismic and thermal resilience curves for each facade package, along with resilience criteria. These criteria are embedded into a practical decision-making process to enable the selection of the optimal design case based on project specifications.

Improving Fault Tolerance for FPGA SoCs through Post-Radiation Design Analysis

FPGAs have been shown to operate reliably within harsh radiation environments by employing single-event upset (SEU) mitigation techniques, such as configuration scrubbing, triple-modular redundancy, error correction coding, and radiation aware implementation techniques. The effectiveness of these techniques, however, is limited when using complex system-level designs that employ complex I/O interfaces with single-point failures. In previous work, a complex SoC system running Linux applied several of these techniques only to obtain an improvement of 14 \(\times\) in mean time to failure (MTTF). A detailed post-radiation fault analysis found that the limitations in reliability were due to the DDR interface, the global clock network, and interconnect. This article applied a number of design-specific SEU mitigation techniques to address the limitations in reliability of this design. These changes include triplicating the global clock, optimizing the placement of the reduction output voters and input flip-flops, and employing a mapping technique called “striping.” The application of these techniques improved MTTF of the mitigated design by a factor of 1.54 \(\times\) and thus provides a 22.8X \(\times\) MTTF improvement over the unmitigated design. A post-radiation fault analysis using BFAT was also performed to find the remaining design vulnerabilities.

An 88 dB SNDR 100 kHz BW Sturdy MASH Delta-Sigma Modulator Using Self-Cascoded Floating Inverter Amplifiers

Battery-powered Internet-of-Things applications require high-resolution, energy-efficient analog-to-digital converters (ADCs). There are still limited works on sub-MHz-bandwidth ADC designs. This paper presents a sturdy multi-stage shaping (SMASH) discrete-time (DT) delta-sigma modulator (DSM) structure using a self-cascoded floating-inverter-based dynamic amplifier (FIA). The proposed structure removes the explicit quantization error extraction of the first loop and all the feedback DACs in the cascaded loop, decreasing the design complexity of the circuit. This enables the proposed DT DSM to operate at a higher speed, which is suitable for achieving high-order noise at a low oversampling ratio (OSR). The proposed self-cascoded FIA is more power-efficient and can acquire more than 45 dB DC gain under a 1.2 V supply. The DT DSM implemented in a piece of 55 nm CMOS technology measures an 88.0 dB peak signal-to-noise-and-distortion ratio (SNDR) in a 100 kHz bandwidth (BW) and an 85.3 dB dynamic range (DR), consuming 249.1 μW from a 1.2 V supply at 10 MS/s. The obtained 174.0 dB SNDR-based Schreier figure-of-merit (FoMs) is competitive within state-of-art high-resolution (SNDR > 85 dB) and general-purpose (sub-MHz-bandwidth) ΔΣ ADCs.

Use of Pulsed Potentials for Electropolishing TA6V Parts Elaborated By Additive Manufacturing in Deep Eutectic Solvent

The Ti-6Al-4V alloy's high mechanical properties, low density, excellent biocompatibility, and corrosion resistance make it an ideal material for sectors such as aeronautics, astronautics and medical technology. The demand for increasingly complex part designs is speeding up the development of Additive Manufacturing (AM) technology, enabling the creation of shapes unachievable with traditional machining. However, the parts manufactured present significant surface roughness, thus reducing resistance to corrosion and mechanical stress. To mitigate these risks, homogeneous polishing of the entire shape is required. Electrochemical polishing is an all-round part treatment technique ideal for addressing AM challenges. Deep Eutectic Solvent (DES) electrolytes are well-suited for this application. The aim of this study is to develop electropolishing of Ti-6Al-4V parts in a DES solvent of ethylene glycol and choline chloride. The challenges posed by viscous layer thickness problems, as well as two methods to overcome them, are described, including agitation control and pulsed potentials.

Overcoming bubble formation in polydimethylsiloxane-made PCR chips: mechanism and elimination with a high-pressure liquid seal

The thermal expansion of gas and the air permeability of polydimethylsiloxane (PDMS) were previously thought to be the main causes of bubbles and water loss during polymerase chain reaction (PCR), resulting in a very complex chip design and operation. Here, by calculating and characterizing bubble formation, we discovered that water vapor is the main cause of bubbling. During PCR, heat increases the volume of the bubble by a factor of only ~0.2 in the absence of water vapor but by a factor of ~6.4 in the presence of water vapor. In addition, the phenomenon of “respiration” due to the repeated evaporation and condensation of water vapor accelerates the expansion of bubbles and the loss of water. A water seal above 109 kPa can effectively prevent bubbles in a bare PDMS chip with a simple structure, which is significant for the wide application of PDMS chips.

Flavored Tobacco User Characteristics in U.S. young Adults: Wave 5 of the Population Assessment of Tobacco and Health Study

Introduction: Flavorings are one of the major appealing factors of current tobacco products, especially for young adults. They constantly evolve, and new flavorings are introduced to the market every year, but little is known about user profiles of flavored tobacco products (FTPs). Methods: We analyzed young adult (ages 18–24) tobacco product users (N = 4,707) from Wave 5 of the Population Assessment of Tobacco and Health Study. We applied bivariate analyses to compare individuals who use FTP and non-FTPs by different flavor types (i.e., menthol/mint, fruit, candy/sweets, and tobacco). Parameter estimates were weighted by applying the sample and replicate weights for the complex study design to produce population-representative estimates. Results: Sixty percent of the current combustible tobacco users and 90% of electronic nicotine delivery systems (ENDS) users were FTP users. FTP users were more likely to be multiple product users than non-FTP users. Being non-Hispanic White, drinking alcohol in the past year, experiencing internalizing problems in the past month, and having tobacco dependence were associated with FTP use. Flavored ENDS users had different sociodemographic characteristics by flavor types but did not differ significantly in vaping-related behaviors (e.g., frequency). Also, preferred flavors differed among tobacco user groups (i.e., ENDS, hookah, and cigars). Conclusions: FTPs appear to be gaining popularity among young adults and tend to show co-use with multiple tobacco products and other substances. Future studies are warranted to monitor the risk factors of young adult FTP use, especially in the context of flavor ban on ENDS products.

Syphilis among HIV-positive men who have sex with men in Ghana: The 2023 biobehavioral survey.

Apart from HIV acquisition, men who have sex with men are at a higher risk of sexually transmitted infections, especially syphilis. Although the intersection between syphilis and HIV poses a formidable challenge among key populations who are known to be vulnerable to many health threats, there is little known about syphilis infection among MSM living with HIV in Ghana. This study seeks to investigate the burden of syphilis and address the existing knowledge gap by exploring behavioral, healthcare access, and structural factors influencing the syphilis burden within the HIV-positive MSM population. This study was conducted in 2023 as part of the bio-behavioral survey (BBS) among men who have sex with men (MSM) in Ghana. A cross-sectional survey that used a respondent-driven sampling (RDS) approach was conducted in the old ten regions of Ghana. Data was collected on 3,420 participants, however, 857 HIV-positive MSM were included in this study since it focused on syphilis among HIV-positive MSM in Ghana. The study estimated the prevalence of syphilis among MSM living with HIV and provided a 95% confidence interval across different categories of explanatory variables. Bivariate and multivariable logistic regression models were used to identify factors associated with overall syphilis prevalence. All other analyses were weighted due to the complex design of the study. The overall prevalence of syphilis was 23.83% (95% CI: 20.44, 27.58). HIV-positive men who only had sex with men had a 29.77% (95% CI: 23.90, 36.40) prevalence of syphilis compared to a prevalence of 9.50% (95% CI: 2.56, 29.53) recorded by HIV-positive MSM who were attracted to mostly females. Participants who ever had receptive anal sex recorded a higher prevalence 26.79% (95% CI: 22.78, 31.23) than those who never had receptive anal sex 12.86% (95% CI: 8.02, 19.99). The odds of syphilis among HIV-positive MSM who never used condoms with regular sex partners in the last 6 months were 41.08 (aOR: 41.08 at 95% CI 1.24-136.42; p = 0.038). There is a high prevalence of syphilis among HIV-positive men who have sex with men in Ghana, especially among those who engage in unprotected anal sex and have multiple sexual partners. Our findings underscore the dire need for targeted interventions to address the dual brunt of HIV and syphilis among the MSM population in Ghana.

High‐Throughput Production of Gelatin‐Based Touch‐Spun Nanofiber for Biomedical Applications

Nanofiber production techniques have become increasingly important due to their wide range of applications. However, the complex design of the setup and difficulty in scaling up to high production rate have limited the industrial applicability of some of the conventional fiber generation techniques such as electrospinning. Herein, the touch spinning method is scaled up for nanofiber production using a simple rotating drawing setup with polymers that are relevant for biomedical applications such as polyethylene oxide and gelatin. The process is amenable to use of benign solvent such as water and production of a wide variety of submicron‐scale gelatin‐based nanofibers at a high throughput (≈2.45 g hr−1 with the single channel flow), which is an order of magnitude higher than those produced by other fiber generation methods is shown. The parametric study indicates that the fiber production process can be tuned at a desired rate without sacrificing the fiber quality by simply altering the number of drawing rods, the size of the rotating disk, and the number of solution flow supply channels. The utility of this technique for different biomedical applications such as cell culture and air filtration applications is also demonstrated.

Enhancing precision in table tennis officiating through an optimized autonomous sensor node system

PurposeThe purpose of the study is to address concerns regarding the subjectivity and imprecision of decision-making in table tennis refereeing by developing and enhancing a sensor node system. This system is designed to accurately detect the points on the table tennis table where balls collide. The study introduces the twined-reinforcement chimp optimization (TRCO) framework, which combines two novel approaches to optimize the distribution of sensor nodes. The main goal is to reduce the number of sensor units required while maintaining high accuracy in determining the locations of ball collisions, with error margins significantly below the critical 3.5 mm cutoff. Through complex optimization procedures, the study aims to improve the efficiency and reliability of decision-making in table tennis refereeing by leveraging sensor technology.Design/methodology/approachThe study employs a design methodology focused on developing a sensor array system to enhance decision-making in table tennis refereeing. It introduces the twined-reinforcement chimp optimization (TRCO) framework, combining dual adaptive weighting strategies and a stochastic approach for optimization. By meticulously engineering the sensor array and utilizing complex optimization procedures, the study aims to improve the accuracy of detecting ball collisions on the table tennis table. The methodology aims to reduce the number of sensor units required while maintaining high precision, ultimately enhancing the reliability of decision-making in the sport.FindingsThe optimization research study yielded promising outcomes, showcasing a substantial reduction in the number of sensor units required from the initial count of 60 to a more practical 49. The sensor array system demonstrated excellent accuracy in identifying the locations of ball collisions, with error margins significantly below the critical 3.5 mm cutoff. Through the implementation of the twined-reinforcement chimp optimization (TRCO) framework, which integrates dual adaptive weighting strategies and a stochastic approach, the study achieved its goal of enhancing the efficiency and reliability of decision-making in table tennis refereeing.Originality/valueThis study introduces novel contributions to the field of table tennis refereeing by pioneering the development and optimization of a sensor array system. The innovative twined-reinforcement chimp optimization (TRCO) framework, integrating dual adaptive weighting strategies and a stochastic approach, sets a new standard for sensor node distribution in sports technology. By substantially reducing the number of sensor units required while maintaining high accuracy in detecting ball collisions, this research offers practical solutions to address the inherent subjectivity and imprecision in decision-making processes. The study’s originality lies in its meticulous design methodology and complex optimization procedures, offering significant value to the field of sports technology and officiating.

Statistical Analysis of nnU-Net Models for Lung Nodule Segmentation.

This paper aims to conduct a statistical analysis of different components of nnU-Net models to build an optimal pipeline for lung nodule segmentation in computed tomography images (CT scan). This study focuses on semantic segmentation of lung nodules, using the UniToChest dataset. Our approach is based on the nnU-Net framework and is designed to configure a whole segmentation pipeline, thereby avoiding many complex design choices, such as data properties and architecture configuration. Although these framework results provide a good starting point, many configurations in this problem can be optimized. In this study, we tested two U-Net-based architectures, using different preprocessing techniques, and we modified the existing hyperparameters provided by nnU-Net. To study the impact of different settings on model segmentation accuracy, we conducted an analysis of variance (ANOVA) statistical analysis. The factors studied included the datasets according to nodule diameter size, model, preprocessing, polynomial learning rate scheduler, and number of epochs. The results of the ANOVA analysis revealed significant differences in the datasets, models, and preprocessing.