A tool-based hybrid laser-electrochemical micromachining process involves concurrent application of two process energies i.e. electrochemical and laser in the same machining zone by means of a hybrid tool which serves as an ECM tool as well as a multimode waveguide. It is a relatively novel process finding applications in defect-free machining of difficult-to-cut materials without affecting their microstructure. In order to understand the physical phenomena occurring during this process, in-situ observations are required. Therefore, in this work, a real time observation was carried out of a novel tool-based hybrid laser electrochemical micromachining process. A combination of high-speed imaging and Large Scale Particle Image Velocimetry (LSPIV) was used to visualize the tool-based hybrid laser-ECM process in real time. It also allowed to carry out experimental investigations on the by-products and bubble generation which have a direct effect on process performance in terms of accuracy and efficiency. The real-time on-machine observations are unique of its kind and they will facilitate the understanding of underlying mechanisms governing this hybrid laser-electrochemical micromachining process. This will ultimately help in improving the quality of parts manufactured. This research is also a step forward towards making these physics-based hybrid processes deterministic by employing high-speed imaging in a closed loop control.
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http://dx.doi.org/10.1038/s41598-020-73821-7 | DOI Listing |
Sci Prog
January 2024
Institute of Training and International Cooperation (ITIC), University of Transport Technology, Thanh Xuan, Hanoi, Vietnam.
This study presents a novel approach to accurately predict the settlement of shallow foundations using advanced machine learning techniques while assessing the influence of key variables. Four machine learning models Gradient Boosting (GB), Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) are enhanced with Particle Swarm Optimization (PSO) for hyperparameter tuning, resulting in hybrid models GB-PSO, RF-PSO, SVM-PSO, and KNN-PSO. The experimental dataset comprises 189 samples, and model performance is rigorously evaluated through K-Fold Cross-Validation alongside R², RMSE, MAE, and MAPE metrics.
View Article and Find Full Text PDFJ Chem Theory Comput
September 2024
College of Energy, Soochow Institute for Energy and Materials InnovationS (SIEMIS), Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy Technologies, Soochow University, Suzhou 215006, China.
Comprehending the structure and dynamics of water is crucial in various fields, such as water desalination, ion separation, electrocatalysis, and biochemical processes. While reported works show that the molecular dynamics (AIMD) can accurately portray water's structure, the artificial high temperature (AHT) from 120 to 30 K is needed to mimic the quantum nature of hydrogen-bond network from GGA, metaGGA to hybrid functionals. The AHT proves to be an inadequate approach for systems involving aqueous multiphase mixtures, such as water-solid interfaces and aqueous solutions.
View Article and Find Full Text PDFPLoS One
August 2024
Institute of Innovation for Future Society of Nagoya University, Nagoya, Aichi, Japan.
Spinal muscular atrophy (SMA) is an intractable neuromuscular disorder primarily caused by homozygous deletions in exon 7 of the SMN1 gene. Early diagnosis and prompt treatment of patients with SMA have a significant impact on prognosis, and several therapies have recently been developed. Current SMA screening tests require a significant turnaround time to identify patients with suspected SMA, due both to the interval between the birth of a newborn and the collection of blood for newborn mass screening and the difficulty in distinguishing between SMN1 and SMN2, a paralog gene that requires testing in specialized laboratories.
View Article and Find Full Text PDFJ Alzheimers Dis
February 2024
Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China.
Background: Emotion and cognition are intercorrelated. Impaired emotion is common in populations with Alzheimer's disease (AD) and mild cognitive impairment (MCI), showing promises as an early detection approach.
Objective: We aim to develop a novel automatic classification tool based on emotion features and machine learning.
Child Health Nurs Res
October 2023
Professor, Department of Nursing Science, Chungbuk National University, Cheongju, Korea.
Purpose: This study aimed to derive a conceptual definition and attributes for nursing students' rights in clinical practice in South Korea.
Methods: This concept-analysis study was conducted at a nursing school in South Korea. The participants were recruited using purposive sampling.
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