bluuebunny/crossref_metadata_2025_split huggingface dataset:
Suppression of Catalyst Diffusion Into Alumina Support in Dynamic Chemical Vapor Deposition of Carbon Nanotube
Authors: Tomaraei Golnaz , Lee Jaegeun , Kim Seung Min , Abdulhafez Moataz , Bedewy Mostafa 
Published: September 2023

Abstract
The utilization of rapid thermal processing capabilities in chemical vapor deposition of carbon nanotubes (CNTs) enables creating dynamic growth recipes engineered to independently control each of the following stages: catalyst nanoparticle preparation by thin film dewetting, and nucleation of CNTs by catalytic growth. While higher temperature pretreatment during the catalyst preparation step enables extending the catalytic lifetime to greatly increase the growth yield by more than three folds, revealing the mechanism of such improvement is crucial. Here, we combine multilayer modeling of ellipsometry results with cross-section scanning transmission electron microscopy (STEM), X-ray diffraction, and scanning electron microscopy (SEM), in order to quantify the evolution of the iron nanocatalyst on alumina thin film stacks as a function of both temperature and time of heating in a reducing environment. Cross section STEM shows the diffusion of iron into the underlying alumina support layer, and our ellipsomettry results confirm that this diffusion is suppressed at high temperature of 900 °C, compared to 700 °C. Importantly, our measurements support the hypothesis that both the loss of iron catalyst from the surface and the rate of subsurface diffusion are higher at the low annealing temperatures, because of a lower density alumina phase. We utilize SEM to estimate the percentage of iron on the surface after dewetting, which is used in the top-most layer in the stack for ellipsometry modeling. Moreover, we show that an interface layer of both iron and alumina is necessary to include in order to accurately model the multilayer system. By comparing two different sets of samples with 1 nm iron on 10 nm alumina as well as with 10 nm iron on 100 nm alumina, we confirm that these findings can be extended to different ranges of thickness.
Investigating Electrode Design Methodology for Improving Machining Performance in Silicon Using Die Sinking EDM
Authors: Karim Mahmud Anjir , Nafi Muhammad Abdun , Jahan Muhammad P. 
Published: September 2023

Abstract
Silicon is the material that is most frequently utilized in the electronic industries because of its distinctive properties which encompasses from age resistance to high temperature stability. However, it is extremely challenging to machine silicon using conventional machining processes that employs traditional cutting force. As a result, non-conventional machining techniques have gained popularity and Electrical Discharge Machining (EDM) is one of the non-conventional machining techniques that has enormous potential in terms of machining silicon. However, the slow rate of material removal is the major drawback of machining silicon using EDM. This study seeks to investigate unique electrode designs and explore their efficacy in terms of improving material removal rate (MRR), reducing electrode or tool wear rate (TWR), and improving quality of the features machined by those electrodes. In this study, graphite electrodes with different arrays (1 × 4, 2 × 4 and 3 × 4) and leg heights (0.2” and 0.3” of electrode legs) were made using milling machine and were used in the die sinking EDM process to investigate the effects of heights and arrays on the material removal rate, tool wear rate and dimensional accuracy of the fabricated features keeping the EDM parameters constant. It has been observed that the increase of arrays of electrode legs results in shorter machining times per leg due to improve flushing conditions for both cases of electrode height. For lower arrays of electrode legs, smaller height (0.2″) performs better in terms of material removal rate. At 3 × 4 arrays of electrode, both cases of height of electrode show almost identical material removal rate. In case of dimensional accuracy, the quality of features improved with increased arrays of electrode legs for both leg heights (0.2” and 0.3″) of electrode. However, for overall accuracy of the features, height does not have significant effect as both performs quite similar. In this study, electrode wear rate is found negative due to carbon deposition on the graphite electrode. With the increased arrays of electrode legs, there is a decrease in carbon deposition per legs of electrode for both cases of electrode height. In terms of the effects of electrode leg height, each case of arrays performs quite alike.
Fabrication of Superhydrophobic Surfaces Using Glancing Angle Deposition
Authors: Qu Chuang , McNamara Shamus , Walsh Kevin 
Published: September 2023

Abstract
This paper introduces the fabrication of superhydrophobic surfaces using glancing angle deposition (GLAD). GLAD is an advanced physical vapor deposition technique, during which the tilt and rotation of the substrate are maneuvered with some algorithm. GLAD has the unique advantage of creating three-dimensional nanofeature arrays, comparing to conventional top-down nanofabrication techniques. Various nanofeatures created by GLAD have been reported, including pillars, springs, chevrons, ribbons, and those structures as templates for creating nanoporous membranes. Superhydrophobicity is nature inspired, such as from lotus leaf and cicada wings, which are with highly porous micro/nanostructures that reduce the surface energy of the surfaces to achieve the water repellent property. The ability to create hierarchical and porous nanostructures makes GLAD the perfect candidate for creating superhydrophobic surfaces. GLAD processes for superhydrophobic surfaces is proposed by other research groups. However, the processes are flawed: either time consuming, or need to be assisted by templates that are challenging to be made. This paper will introduce a new approach with GLAD for creating superhydrophobic surfaces. This approach does not need the seeding layer that are proposed by for creating the hierarchical nanoporous surfaces. Superhydrophobic surfaces are achieved with the water contact angle of 155 degrees. More GLAD surfaces with higher/lower water contact angles by different GLAD recipes are created and analyzed. The superhydrophobic surfaces are potentially used for applications such as anti-icing surfaces, self-cleaning surfaces, and antimicrobial surfaces.
Highly Parsimonious Multi-Fidelity Learning of Process Parameter-Performance Relationships: A Case Study With Fused Filament Fabrication
Authors: Cleeman Jeremy , Malhotra Rajiv 
Published: September 2023

Abstract
Modeling the effects of the process parameters on the process or product performance is critical for predictive process design and control. While physics-based modeling has long been the path to such predictions, machine learning models are of increasing interest recently. But the data-hungry nature of machine learning entails prohibitive experimental cost, is hindered by large oversimplifications of computationally efficiency analytical models, or is limited by the time and cost of creating and executing more accurate numerical models. The situation becomes worse for newer processes or material for which the underlying coupled physics is often not fully known, thus decelerating process or material deployment. Transfer learning has been proposed as a solution for this problem, but the above issues remain since a source model of sufficient fidelity is still needed. This paper takes a first stab at this issue. We propose a physics-informed transfer learning that combines a large amount of data from an extremely low-fidelity but equally computationally efficient process model based on first principles with a small experimental dataset that represents ground truth. We demonstrate this approach by creating a support vector regression model of printed line width in Fused Filament Fabrication. Orders of magnitude reduction in computational cost and 60% reduction in experimental data needed is achieved, while retaining similar or lower error as compared to naïve learning on a much larger experimental dataset. We demonstrate the importance of the number and location of high-fidelity experimental data points and discuss future work in this context.
A Machine Learning Genetic Algorithm (ML-GA) Approach to Optimize Process Parameters of Trochoidal Toolpath During Hybrid-Electrochemical Magnetorheological (H-ECMR) Finishing
Authors: Rajput Atul Singh , Das Manas , Kapil Sajan 
Published: September 2023

Abstract
Hybrid-Electrochemical Magnetorheological (H-ECMR) Finishing process is an advanced surface finishing technique that produces surface roughness (Ra) up to a few nanometers required for the implants. In this study, duplex stainless steel (DSS), a biomaterial constituting ferrite and austenite in equal proportion, is considered as the workpiece. DSS is widely used for its high corrosion resistance compared with other grades of stainless steel biomaterials. Furthermore, optimization of the process parameters for the trochoidal, a high-speed finishing toolpath, is carried out to achieve optimum surface roughness parameters during H-ECMR finishing. The surface roughness parameters (i.e., average Surface roughness (Ra). Kurtosis (Rku), and Skewness (Rsk)) are attained from the integration of the Design of Experiment (DOE), Response Surface Methodology (RSM), and Machine Learning Genetic Algorithm (ML-GA). DOE is utilized to plan the experiments based on Central Composite Design (CCD) using input process parameters of the H-ECMR finishing process. The regression equation is developed with the RSM, and its optimization study is performed with ML-GA. This paper aims to analyze the impact of the process parameters for the H-ECMR finishing process on different surface roughness parameters.
Utilizing Vision-Based Object Detection Algorithms in Recognizing Uncommon Operating Conditions for CNC Milling Machine
Authors: Choudhari Sahil J. , B. J. Sujay , Singh Swarit Anand , Desai K. A. 
Published: September 2023

Abstract
Although Computer Numerical Control (CNC) machines were designed to perform tasks with the least human intervention, operator involvement is mandatory to ensure fault-free operations. Numerous technological solutions utilizing Artificial Intelligence, sensor fusion, Internet of Things (IoT), machine vision, etc., have been developed for process, component, and machine monitoring to impart smartness and autonomous operating abilities. The primary focus of these solutions is to monitor process faults such as tool wear, chatter, static deflections, and cutting forces to assist the operator in minimizing the consequences. The present work develops a vision-based solution for identifying uncommon process abnormalities like improper coolant flow, chip clogging, and tool breakage during CNC milling. The proposed solution replicates the task of a machine operator in identifying these faults and assists in fault-free operations. The study explores the feasibility of utilizing classical and deep learning-based object detection algorithms while developing these solutions. The classical image processing algorithm is ineffective during dynamic process conditions. The deep learning-based algorithm, with an average precision of about 0.75, showed proficiency in abnormalities detection. A Graphical User Interface (GUI) has been developed and integrated with the CNC milling machine to provide an interactive in-process monitoring tool. It is demonstrated that the proposed solution can reduce dependence on a machine operator while monitoring these faults.
Investigation of the Interfacial Adhesion Strength of Parts Additively Manufactured on Fabrics
Authors: Blais Maxwell , Tomlinson Scott , Khoda Bashir 
Published: September 2023

Abstract
This research first presents a method of peel testing developed by the researchers to characterize the strength of the interface between fabric and additively manufactured material. Experimentation is next presented that characterizes the interfacial strength relative to a set of parameters which include fabric fiber morphology, thickness of sizing applied to fabric, 3D printer bed temperature, and angle of additive manufacturing relative to the fabric warp direction. The interface strength within the parameter space presented was then searched and found to have a maximum of 5.18N per mm using a novel set of parameters. This interface strength indicates the method of additive manufacturing direction on fabric may be suitable for use in a broader range of applications than previously proven feasible.
Relatively rough, thick, and loose weave fabrics were found to promote interface strength compared to smoother, thinner, and finer woven fabrics. Relatively higher bed temperatures also promoted higher interface strength. Sizings on the fabric were found to promote interface strength with relatively smooth, thin, or fine fabrics which don’t themselves promote high mechanical interlocking. Using these research findings, interface strength between fabric and additively manufactured material can be modified to suit the application.
A Comparative Analysis of Cathode Stripping Methods for Direct Recycling of Spent Li-Ion Batteries
Authors: Xiao Yaohong , Su Jinrong , Chen Lei 
Published: September 2023

Abstract
The cathode is the most valuable battery component rich in precious metals and, thus, is the leading recycling target in spent lithium-ion batteries. In particular, the emerging development of direct recycling techniques requires the non-destructive spent cathode as feedstock; however, posing a challenge to effectively strip the spent cathode powders without destroying the cathode structure after disabling the binders. In this study, we compare four cathode stripping methods, including solvent dissolution & magnetic stirring, solvent dissolution & sonication, heat treatment & curling-uncurling, and solvent dissolution & resonant acoustic vibration. Our results show that solvent dissolution & resonant acoustic vibration-based cathode stripping achieves an efficiency of up to 92%, without introducing impurities such as small aluminum fragments and powders. These findings demonstrate the potential of resonant acoustic vibration-based cathode stripping for scaling up the cathode powder recovery and direct recycling of spent Li-ion batteries.
Application of Digital Twins to Laser Powder Bed Fusion Additive Manufacturing Process Control
Authors: Yeung Ho , Kim Felix , Donmez Alkan 
Published: September 2023

Abstract
Digital twins for additive manufacturing (AM) have drawn much research attention recently, thanks to advancements in artificial intelligence and machine learning. Machine learning takes the process and measurement data from the manufacturing process to build data-driven models instead of physics-based descriptive models. The latter are usually hard to obtain for complex AM processes such as laser powder bed fusion. This study proposed a digital twin framework for the laser powder bed fusion AM process control and optimization. The framework is created based on the recently developed advanced point-wise scan control method. It consists of four components: digital twin of process design, digital twin of process control, digital twin of process monitoring, and digital twin of printed part. Their construction is detailed, and potential applications are demonstrated/discussed.
A Bionic Design With Wing Structures to Assist Flexible Microelectrode Implantation
Authors: Zhang Leihan , Wang Yi , Cai Yi 
Published: September 2023

Abstract
Microelectrodes and microprobes are promising tools to explore brains at the cellular level or restore function in the nervous system. While making electrodes ultra-small and flexible is a trend with many merits in biomedical implants, it also brings a considerable challenge to insert them successfully and efficiently due to the buckling and deflection of the electrodes. Similar problems also exist in nature, like mosquito proboscis behavior and Hymenoptera oviposition. They develop a series of mechanisms to overcome the problems, such as reducing effective length, increasing stress concentration, guide-assisted insertion, reciprocating penetration, etc. Based on these mechanisms, a bionic design is presented where two wing structures are attached to the planar-type neural probe. The principles and benefits of the design are elaborated, and prototype dummy probes are fabricated. Compression buckling tests and insertion tests are conducted on tissue phantom, showing that the bionic design can enhance the stiffness of the probe and reduce the deflection angle effectively, improving the accuracy and efficiency of probe implantation. The presented design opens new approaches for the development of novel flexible microelectrodes and microprobes.
Study on Dicing Mechanism for PZT-4 Piezoelectric Ceramics Composite
Authors: Zhou Yang , Liu Yao , Jinjie Zhou , Guo Zhanling 
Published: September 2023

Abstract
The dicing and filling is the most commonly method to fabricate the piezoelectric composite by the removing parts of the piezoelectric ceramics and filling with the polymer, which can improve the piezoelectricity of piezoelectric ceramics tremendously. The ceramics dicing quality affect the composite piezoelectric performance and the dicing mechanism is not clear now. In this study, the experiments were conducted to reveal the influence of the dicing parameters such as wheel speed and feed rate on the surface quality (including surface roughness, kerf width, surface damage width and height). The results show that with the increase of wheel speed and the decrease of feed rate, the surface roughness and surface damage width and height decrease gradually, while the kerf width is opposite. The feed rate has the greatest influence on the surface quality, followed by the wheel speed. In addition, the surface roughness of each ceramic dicing surface decreases from top to bottom. This study reveals the dicing mechanism of the PZT-4 and laid a fundamental understanding for piezoelectric composite performance.
Effects of Electrolyte Bath Composition on the Surface Properties and Nickel Content of Zinc-Nickel Electroplating
Authors: Vispute Suprita , Sundaram Murali , Yang Jung Ho , Iyyer Nagaraja , Phan Nam D. , Kittur Madan G. 
Published: September 2023

Abstract
Electroplating is used as a surface protection process in several industries. The well-known cadmium electroplating needs an alternative due to the environmental hazards, and occupational safety and health risks arising from the carcinogenic nature of cadmium. Zinc-nickel alloy electroplating has the potential to replace cadmium plating in surface protection applications. This paper investigates the effect of acidic and alkaline electrolyte baths on the composition and surface properties of the zinc-nickel electroplating on 300M steel. Five electrolyte baths with different levels of chloride and citrate content were studied. Scanning Electron Microscope (SEM) imaging of specimens was done to study the surface morphology. The composition of nickel in the plating was determined using Energy Dispersive Spectroscopy (EDS) while the phase analysis was conducted by X-ray Diffraction (XRD). Incorporation of chloride in the electrolyte baths increased the nickel composition in the deposit while citrate addition reduced it in the deposit obtained from the acidic electrolyte. Surface roughness was measured using a stylus profilometer. It was observed that smoother surface was obtained with alkaline electrolyte baths. The surface wettability was obtained by measuring the contact angle between deionized water and the plating. Alkaline electrolytes produced higher surface wettability in the plating than acidic electrolytes. Also, the wettability of the surface was found to increase when the alkaline electrolyte was used without any chloride accelerators.
Relative resistance of patient-derived envelope sequences to SERINC5-mediated restriction of HIV-1 infectivity
Authors: Nkuwi Emmanuel , Judicate George P. , Tan Toong Seng , Barabona Godfrey , Toyoda Mako , Sunguya Bruno , Kamori Doreen , Ueno Takamasa 
Published: September 2023

ABSTRACT

A host cellular transmembrane protein, SERINC5, inhibits HIV-1 infectivity when incorporated into progeny virions. Recent studies suggest that certain Envelope glycoproteins can resist SERINC5-mediated restriction. However, the underlying mechanism of Envelope glycoprotein-mediated resistance to SERINC5 restriction remains unclear. Here, we investigated the extent of sensitivity of patient-derived HIV-1 Envelope sequences to SERINC5-mediated restriction and examined Envelopes’ characteristics in relation to SERINC5. A
nef
-deficient HIV-1 reporter was pseudotyped with Envelope sequences isolated from a total of 50 Tanzanians infected with non-B HIV-1 subtypes in the presence and absence of SERINC5 expression. The infectivity of resultant pseudoviruses was differentially reduced by SERINC5 by a median of 5.1-fold (IQR: 3.2–8.6) including five outliers showing ≥20-fold reduction, whereas the pseudovirus with the control NL4-3 envelope was reduced by 64-fold. The pseudovirus sensitivity to SERINC5-mediated restriction differed significantly among the subtypes of the envelope sequences but was not associated with any other Envelope characteristics or clinical parameters tested. Within some hosts, the pseudovirus sensitivity to SERINC5 varied substantially among Envelope sequences, with sensitive ones (as defined by ≥20-fold reduction) being underrepresented. Analysis of chimeric constructs between intra-host clones revealed that both N- and C-terminus of the Envelope sequences were responsible for SERINC5-mediated restriction. Taken together, these results demonstrate that the majority of naturally occurring Envelope sequences across multiple subtypes are relatively less sensitive to SERINC5-mediated restriction of infectivity and that naturally occurring polymorphisms at N- and C-terminal parts are important for this sensitivity.

IMPORTANCE
Pathogenesis of HIV-1 is enhanced through several viral-encoded proteins that counteract a range of host restriction molecules. HIV-1 Nef counteracts the cell membrane protein SERINC5 by downregulating it from the cell surface, thereby enhancing virion infectivity. Some subtype B reference Envelope sequences have shown the ability to bypass SERINC5 infectivity restriction independent of Nef. However, it is not clear if and to what extent circulating HIV-1 strains can exhibit resistance to SERINC5 restriction. Using a panel of Envelope sequences isolated from 50 Tanzanians infected with non-B HIV-1 subtypes, we show that the lentiviral reporters pseudotyped with patient-derived Envelopes have reduced sensitivity to SERINC5 and that this sensitivity differed among viral subtypes. Moreover, we found that SERINC5 sensitivity within patient-derived Envelopes can be modulated by separate regions, highlighting the complexity of viral/host interactions.