Multi-objective robust parameter optimization using the extended and weighted k-means (EWK-means) clustering in laser powder bed fusion (LPBF)

Metal additive manufacturing (AM) technology, especially laser powder bed fusion (LPBF), has received abundant interest from industries and the research community. Process optimization methods have thus multiplied to improve the overall quality of the final parts. However, little attention has been given to the quality repeatability issue. This paper proposes a novel multi-objective robust parameter optimization framework to explore optimal process parameters with respect to relative density and dimensional accuracy of LPBF-fabricated parts. Specifically, a modified k-means clustering, named the Extended and Weighted K-means (EWK-means), was constructed to simultaneously optimize the mean and the variance of the multiple responses. Experiments were conducted to verify the effectiveness of the proposed optimization framework. In addition, the effects of the process parameters, environment-related parameters, and physical properties on the hardness of the parts were analyzed using several machine learning models. The results showed that the proposed method achieved a set of optimal process parameters with better quality and satisfactory variability in the printed parts compared with other robust parameter optimization methods

Enhancing catalytic performance and hot electron generation through engineering metal-oxide and oxide-oxide interfaces

Interfaces are of utmost importance in catalytic reactions, influencing reaction kinetics and electron transfer processes. However, investigations in combined interfaces of metal-oxide and oxide-oxide at heterogeneous catalysts still have challenges due to their complex structure. Herein, we synthesized well-defined Co3O4 and CeO2 cubes with distinct facets and investigated their catalytic performance when deposited on a Pt-thin film, focusing on the influence of metal-oxide and oxide-oxide interfaces. Catalytic measurements demonstrated that the CeO2/Pt interface significantly enhanced turnover frequency (TOF) and selectivity for partial methanol oxidation compared to Co3O4/Pt and bare Pt. Notably, the CeO2/Co3O4/Pt nanodevice exhibited improved partial oxidation selectivity, highlighting the role of the CeO2/Co3O4 interface in methyl formate production. Chemicurrent measurements demonstrate enhanced hot electron generation due to increased overall TOF and partial oxidation production. We also conducted near ambient pressure X-ray photoelectron spectroscopy (NAPXPS) analysis, revealing a higher concentration of Ce3+ ions and increased oxygen vacancies in the CeO2/Co3O4/ Pt catalyst, suggesting oxygen migration from CeO2 to Co3O4, leading to methoxy species stabilization and promoting methyl formate formation

On detecting the trivial rational 3-tangle

An important issue in classifying rational 3-tangles is how to know whether or not a given tangle is the trivial rational 3-tangle called infinity-tangle. The author [4] provided a certain algorithm to detect the infinity-tangle. In this paper, we give a much simpler method to detect the infinity-tangle by using the bridge arc replacement. We hope that this method can help prove many application problems such as a classification of 3-bridge knots.(c) 2023 Elsevier B.V. All rights reserved

Significance of body acceleration and gold nanoparticles through blood flow in an uneven/composite inclined stenosis artery: A finite difference computation

Stenosis is a tiny plaque-like structure that builds up in the arterial wall owing to the sediment of cholesterol, fats, and pearly substances. Such inward proliferation in arteries significantly inhibits blood flow, which leads to a lack of nutrients and oxygen in the organs. Therefore, exploring the transport characteristics of blood fluid flow in stenosis arteries plays a prominent role in enhancing blood transportation. As a result, the present mathematical model is devoted to scrutinizing the flow of Sutterby gold blood nanofluid in two distinct stenosis arteries with periodic body acceleration. It is observed that the Sutterby rheology model is treated as blood, and the single-phase model is used for exposing the nanofluid behaviour. Dimensional non-linear PDEs of the current model are reduced to the set of dimensionless PDEs with the help of non-similar variables. A finite-difference approach is manipulated to compute the dimensionless PDEs. The physical features of governing flow parameters on the Sutterby nanofluid velocity, temperature, resistance impedance, flow rate, and wall shear stress are exposed through graphs. It is found that the composite stenosis has a lower wall shear stress than the irregular stenosis. Sutterby blood nanofluid velocity is elevated with the rising of nanoparticle volume fraction. When employing a gold nanofluid containing 5% volume fraction, the temperature in the irregular artery rises by 26.004% compared to the base fluid (blood). Similarly, in the composite artery, utilizing the same 5% volume fraction of the gold nanofluid leads to a temperature increase of 32.6207%. The blood flow pattern exhibits a 0.2340% higher in the irregular artery as compared to the composite artery. & COPY; 2023 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved

The production scheduling problem employing non-identical parallel machines with due dates considering carbon emissions and multiple types of energy sources

This paper addresses the production scheduling problem with non-identical parallel machines in a high-mix, low-volume production environment with due dates, considering carbon emissions savings and diverse types of energy sources for machine operation. To this end, we present a bi-objective mixed-integer programming model that minimizes both the total production-related cost and the total carbon emissions in the production process to determine the optimal production strategy. For each machine, we consider various types of energy sources with different electricity generation costs and different amounts of carbon emissions. The proposed model is validated with an application to a manufacturer in Ulsan, the industrial capital of the Republic of Korea. Our results showcase the potential use of non-identical parallel machines to minimize the total cost and carbon emissions in green manufacturing. Furthermore, the results identify the trade-off between different energy sources and the total cost under different carbon emissions limits. Generally, as the carbon emissions limit increases, our proposed model tends to replace natural gas with coal to minimize the total cost. Also, we perform sensitivity analyses with respect to the energy price of different types of energy sources combined with nuclear and renewable energy sources. We find that coal provides more stability than natural gas in terms of the total cost, particularly when there are fluctuations in the price for coal and natural gas. Additionally, we determine the optimal combination of energy sources for various carbon emissions limits, aiming to minimize the total cost while simultaneously satisfying all production-related and environmental constraints

Leveraging ChatGPT and Bard: What does it convey for water treatment/desalination and harvesting sectors?

Artificial intelligence (AI) has emerged as a prominent tool in the modern day. The utilization of AI and advanced language models such as chat generative pre-trained transformer (ChatGPT) and Bard is not only innovative but also crucial for handling challenges related to water research. ChatGPT is an AI chatbot that uses natural language processing to create humanlike conversations. ChatGPT has recently gained considerable public interest, owing to its unique ability to simplify tasks from various backgrounds. Similarly, Google introduced Bard, an AI-powered chatbot to simulate human conversations. Herein, we investigated how ChatGPT and Bard (AI powdered chatbots) tools can impact water research through interactive sessions. Typically, ChatGPT and Bard offer significant benefits to various fields, including research, education, scientific publications, and outreach. ChatGPT and Bard simplify complex and challenging tasks. For instance, 50 important questions about water treatment/desalination techniques and 50 questions about water harvesting techniques were provided to both chatbots. Time analytics was performed by ChatGPT 3.5, and Bard was used to generate full responses. In particular, the effectiveness of this emerging tool for research purposes in the field of conventional water treatment techniques, advanced water treatment techniques, membrane technology and seawater desalination has been thoroughly demonstrated. Moreover, potential pitfalls and challenges were also highlighted. Thus, sharing these experiences may encourage the effective and responsible use of Bard and ChatGPT in research purposes. Finally, the responses were compared from the perspective of an expert. Although ChatGPT and Bard possess huge benefits, there are several issues, which are discussed in this study. Based on this study, we can compare the abilities of artificial intelligence and human intelligence in water sector research

Synergistic effect of non-thermal plasma and CH4 addition on turbulent NH3/air premixed flames in a swirl combustor

The synergistic effect of non-thermal plasma (NTP) induced by a dielectric barrier discharge (DBD) and CH4 addition on turbulent swirl-stabilized NH3/air premixed flames in a laboratory-scale gas turbine combustor is experimentally investigated by varying the mixture equivalence ratio, ??, the mixt velocity, U0, and the mole fraction of CH4 in the fuel, . It is found that the streamer intensity is significantly increased by adding CH4 to NH3/air flames compared with that by adding H2. This is because positive ions generated by CH4 addition play a critical role in generating streamers. Such streamers intensified by CH4 addition enhance the ammonia combustion more together with CH4, and hence, the lean blowout (LBO) limits of NH3/CH4/air flames are significantly extended compared with those without applying NTP. The maximum streamer intensity is found to be linearly proportional to in wide ranges of ??, , and U0. NTP is also found to significantly reduce the amount of NOx and CO emissions simultaneously. All of the results suggest that NTP can be used more effectively with CH4 addition to stabilize turbulent premixed NH3/air flames and reduce NOx/CO emissions, which is attributed to their synergistic effect on the ammonia combustion

Magnetic nanoparticles for ferroptosis cancer therapy with diagnostic imaging

Ferroptosis offers a novel method for overcoming therapeutic resistance of cancers to conventional cancer treatment regimens. Its effective use as a cancer therapy requires a precisely targeted approach, which can be facilitated by using nanoparticles and nanomedicine, and their use to enhance ferroptosis is indeed a growing area of research. While a few review papers have been published on iron-dependent mechanism and inducers of ferroptosis cancer therapy that partly covers ferroptosis nanoparticles, there is a need for a comprehensive review focusing on the design of magnetic nanoparticles that can typically supply iron ions to promote ferroptosis and simultaneously enable targeted ferroptosis cancer nanomedicine. Furthermore, magnetic nanoparticles can locally induce ferroptosis and combinational ferroptosis with diagnostic magnetic resonance imaging (MRI). The use of remotely controllable magnetic nanocarriers can offer highly effective localized image-guided ferroptosis cancer nanomedicine. Here, recent developments in magnetically manipulable nanocarriers for ferroptosis cancer nanomedicine with medical imaging are summarized. This review also highlights the advantages of current state-of-the-art image-guided ferroptosis cancer nanomedicine. Finally, image guided combinational ferroptosis cancer therapy with conventional apoptosis-based therapy that enables synergistic tumor therapy is discussed for clinical translations

Catalytic behavior of Pt single-atoms supported on CeO2

In this study, we demonstrate that the CO oxidation activity of Pt/CeO2 single-atom catalysts (& LE;0.4 Pt/nm2) is significantly low despite the increase in reducibility, which is associated with the formation of oxygen vacancies that are critical for oxygen activation, with increasing Pt surface density. This result can be related to the negligible amount of CO adsorbed onto the Pt/CeO2 single-atom catalysts. As the Pt surface density increases to 0.8 Pt/nm2, the activity sharply increases; at this loading, Pt clusters are formed and the interactions with CO are enhanced. Notably, after the controlled reduction treatment using CO, the catalytic activity of 0.4 Pt/CeO2 in-creases to the level of 0.8 Pt/CeO2. The sudden increase in activity can be explained by the formation of a partially reduced Pt cluster and the enhanced CO interactions with the Pt atoms of the cluster. These results indicate that Pt cluster formation and its partial reduction are essential for low-temperature CO oxidation. Our study explains the cause of the significantly low CO oxidation activity of Pt/CeO2 single-atom catalysts and how controlled reduction treatment of these catalysts enhances their activity