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Magnesium Technology Symposium, 2025, held as part of the TMS Annual Meeting and Exhibition, TMS 2025

作者： McArthur Sehar, Daniel Saito, Kenichi Telgerafchi, Armaghan Gallego, Maya Sridhar, Meera Iurkovskyi, Artem Powell, Adam Department of Materials Science and Engineering Program Worcester Polytechnic Institute 100 Institute Rd. WorcesterMA01609 United States Department of Mechanical Engineering Shibaura Institute of Technology Tokyo Japan Department of Mechanical Engineering Worcester Polytechnic Institute WorcesterMA United States

ISBN: (纸本)9783031810602

MagnesiumMagnesium’s remarkable stiffnessStiffness-to-weight and high strengthStrength-to-weight ratios could enable substantial vehicle lightweighting versus aluminum and steel. However, primary production is very energy- and emissions-intensive, and recyclingRecycling cannot cost-effectively produce magnesiumMagnesium of sufficient purity for die casting and other structural applications. Distillation can produce high-purity magnesiumMagnesium but is capital- and energy-intensive. Gravity-Driven Multiple Effect Thermal System (G-METS) is a continuous low-pressure magnesiumMagnesium distillation process used in primary production or recyclingRecycling in which heat re-use leads to just 0.5–1 kWh energy consumption per kgMg Mg product—which is 80–90% less energy than current Mg distillation. This paper presents new partial distillation experiments showing 99.96% product purity. An industrial distiller design can help to estimate capital costs. New modeling work describes temperature and pressure change in the vapor conduit, energy use and losses in the industrial distiller, and effects of evaporator flow vanes on the separation of volatile elements such as zinc. © The Minerals, Metals & Materials Society 2025.

关键词： Magnesium alloys

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PFAS Incineration: Known Unknowns, Reaction Simulation, and ML to Predict Product Properties

PFAS Incineration: Known Unknowns, Reaction Simulation, and ...

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2023 IEEE MIT Undergraduate Research Technology Conference, URTC 2023

作者： Soiffer, Duncan Pyorre, Tuomas Kenney, David Teixeira, Andrew Worcester Polytechnic Institute Department of Computer Science and Mathematical Sciences WorcesterMA United States Worcester Polytechnic Institute Department of Robotics Engineering WorcesterMA United States Worcester Polytechnic Institute Department of Chemical Engineering WorcesterMA United States

ISBN: (纸本)9798350308600

Per- and polyfluoroalkyl substances (PFAS) are a group of chemicals used for their impressive stability, a property which has also led them to be found polluting virtually every sector of the environment-including our own bodies. Presently, our ability to destroy PFAS is limited largely to incineration, whose products and side effects are poorly understood. Research on PFAS incineration is constrained by high experimental costs and difficulty in accurately measuring reaction products. This presents an opportunity for computer simulation and machine learning to provide valuable assistance. In this study, three kinds of thermal PFAS decomposition are simulated. Further, to broaden physical understanding of PFAS incineration products, a recent in-house machine learning model for predicting the octanol-water partition coefficient (LogP) of chemicals is improved and applied to simulation results. A decrease in LogP is observed in all treatments, with the most dramatic effect (-2 average LogP) observed in oxidative pyrolysis. © 2023 IEEE.

关键词： Machine learning

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Reflector-Integrated Ultrasound Image-Guided Access: Towards Clinical Applications

Reflector-Integrated Ultrasound Image-Guided Access: Towards...

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Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Tang, Yichuan Chheda, Dhruv Hersum, Mikkel Taubert, Jena Murakami, Ryo Zhang, Haichong Dept. of Robotics Engineering Worcester Polytechnic Institute WorcesterMA United States Dept. of Mechanical Engineering Worcester Polytechnic Institute WorcesterMA United States Dept. of Biomedical Engineering Worcester Polytechnic Institute WorcesterMA United States Dept. of Computer Science Worcester Polytechnic Institute WorcesterMA United States

ISBN: (纸本)9781510685949

Ultrasound (US) image-guided access is widely used in surgical operations such as percutaneous nephrolithotomy (PCNL), percutaneous coronary intervention (PCI) and lumbar puncture (LP). One major challenge conventional US image-guided access faces is sustaining proper alignment between the needle path and the US image plane to maximize needle visibility, since the needle and the US transducer are controlled by each individual hand. Reflector-integrated ultrasound (ref-US) image-guided access was originally proposed to provide by-default alignment of the needle path and the image plane, however issues like bulky size, unconventional handling style and encapsulation of acoustic medium pose difficulties to clinical application of ref-US image-guided access. In this work we focused on improving clinical applicability of ref-US image-guided needle access mechanism. First, the size of the ref-US image guided access mechanism is minimized, and handling style of the mechanism is modified to follow the handling style of a normal ultrasound transducer by using double acoustic reflectors. Second, we use gel-like medium to encapsulate ref-US image-guided access mechanism to reduce imaging artifacts and to prevent medium leakage, while both are common issues in encapsulation using liquid medium. We conducted imaging validation using gelatin phantom with embedded point targets to show the mechanism's sensitivity to the needle tip and small targets. We also conducted insertion validation where needle is inserted into the kidney inside a pig cadaver using proposed ref-US image-guided access mechanism. Validation results indicate that the gap between the concept of ref-US image-guided access towards clinical applications has been bridged. © 2025 SPIE

关键词： Ultrasonography

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Hand Gesture Classification Based on Forearm Ultrasound Video Snippets Using 3D Convolutional Neural Networks

Hand Gesture Classification Based on Forearm Ultrasound Vide...

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IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Keshav Bimbraw Ankit Talele Haichong Zhang Robotics Engineering Worcester Polytechnic Institute Worcester USA Robotics and Biomedical Engineering Worcester Polytechnic Institute Worcester USA

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

Ultrasound based hand movement estimation is a crucial area of research with applications in human-machine interaction. Forearm ultrasound offers detailed information about muscle morphology changes during hand movement which can be used to estimate hand gestures. Previous work has focused on analyzing 2-Dimensional (2D) ultrasound image frames using techniques such as convolutional neural networks (CNNs). However, such 2D techniques do not capture temporal features from segments of ultrasound data corresponding to continuous hand movements. This study uses 3D CNN based techniques to capture spatio-temporal patterns within ultrasound video segments for gesture recognition. We compared the performance of a 2D convolution-based network with (2+1)D convolution-based, 3D convolution-based, and our proposed network. Our methodology enhanced the gesture classification accuracy to 98.8 ± 0.9%, from 96.5 ± 2.3% compared to a network trained with 2D convolution layers. These results demonstrate the advantages of using ultrasound video snippets for improving hand gesture classification performance.

关键词： Hands Human computer interaction Image segmentation Solid modeling Ultrasonic imaging Three-dimensional displays Accuracy Gesture recognition Spatiotemporal phenomena Convolutional neural networks

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Improving Intersession Reproducibility for Forearm Ultrasound based Hand Gesture Classification through an Incremental Learning Approach

Improving Intersession Reproducibility for Forearm Ultrasoun...

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IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Jack Rothenberg Keshav Bimbraw Haichong Zhang Robotics and Biomedical Engineering Worcester Polytechnic Institute Worcester USA Robotics Engineering Worcester Polytechnic Institute Worcester USA

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

Ultrasound images of the forearm can be used to classify hand gestures towards developing human machine interfaces. In our previous work, we have demonstrated gesture classification using ultrasound on a single subject without removing the probe before evaluation. This has limitations in usage as once the probe is removed and replaced, the accuracy declines since the classifier performance is sensitive to the probe location on the arm. In this paper, we propose training a model on multiple data collection sessions to create a generalized model, utilizing incremental learning through fine tuning. Ultrasound data was acquired for 5 hand gestures within a session (without removing and putting the probe back on) and across sessions. A convolutional neural network (CNN) with 5 cascaded convolution layers was used for this study. A pre-trained CNN was fine tuned with the convolution blocks acting as a feature extractor, and the parameters of the remaining layers updated in an incremental fashion. Fine tuning was done using different session splits within a session and between multiple sessions. We found that incremental fine tuning can help enhance classification accuracy with more fine tuning sessions. After 2 fine tuning sessions for each experiment, we found an approximate 10% increase in classification accuracy. This work demonstrates that incremental learning through fine tuning on ultrasound based hand gesture classification can be used improves accuracy while saving storage, processing power, and time. It can be expanded to generalize between multiple subjects and towards developing personalized wearable devices.

关键词： Hands Training Ultrasonic imaging Accuracy Incremental learning Feature extraction Data models Convolutional neural networks Probes Tuning

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Multiview Compounding for Linear Array-Based 3D Photoacoustic Imaging

Multiview Compounding for Linear Array-Based 3D Photoacousti...

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Photons Plus Ultrasound: Imaging and Sensing 2023

作者： Garje, Yash Tang, Yichuan Jaupi, Enxhi Zhang, Haichong K. Robotics Engineering Department Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Biomedical Engineering Department Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Computer Science Department Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States

ISBN: (纸本)9781510658639

Two-dimensional and three-dimensional photoacoustic (PA) visualization is an emerging diagnostic procedure for investigation and research in vascular studies. Current manual/mechanized target scanning techniques involve sweeping the target along the elevation to generate 3D visuals. However, since the linear array probes exhibit poor resolution along the direction orthogonal to its focal plane, these techniques are prone to miss out on the organic structures parallel to the lateral direction. This could result in a misrepresentation of the target and is a critical shortfall of the method. We propose a multiview scanning and compounding technique to overcome the directionality bias and obtain more accurate and isotropic imaging performance. Using electromechanical translatory and rotary stages for multiview data acquisition, we generate a unified 3D visualization. A data processing pipeline illustrates an axial implementation of the Hilbert transform followed by spatial integration of the volumetric data to obtain the output. A 6-directional scanning approach improves the completeness of the structural details. We validated the technique using sub-millimeter-sized balls and wire phantoms. We first observed an enhanced resemblance of the outcome with the actual target in the ball phantom. Secondly, we observed imaging quality improvement with isotropic intensity distribution prominently in the wire phantom. A comparative analysis showed around a 50% reduction in the standard deviation of intensity distribution as compared to conventional unidirectional 3D PA imaging. © 2023 SPIE.

关键词： Phantoms

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Forearm Ultrasound Based Gesture Recognition on Edge

Forearm Ultrasound Based Gesture Recognition on Edge

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International Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Keshav Bimbraw Haichong K. Zhang Bashima Islam Robotics Engineering Worcester Polytechnic Institute Worcester USA Robotics Engineering and Biomedical Engineering Worcester Polytechnic Institute Worcester USA Electrical and Computer Engineering Worcester Polytechnic Institute Worcester USA

ISBN: (数字)9798331530143

ISBN: (纸本)9798331530150

Ultrasound imaging of the forearm has demon-strated significant potential for accurate hand gesture classification. Despite this progress, there has been limited focus on developing a stand -alone end-to-end gesture recognition system which makes it mobile, real-time and more user friendly. To bridge this gap, this paper explores the deployment of deep neural networks for forearm ultrasound-based hand gesture recognition on edge devices. Utilizing quantization techniques, we achieve substantial reductions in model size while maintaining high accuracy and low latency. Our best model, with Float16 quantization, achieves a test accuracy of 92% and an inference time of 0.31 seconds on a Raspberry Pi. These results demonstrate the feasibility of efficient, real-time gesture recognition on resource-limited edge devices, paving the way for wearable ultrasound-based systems.

关键词： Deep learning Ultrasonic imaging Accuracy Quantization (signal) Imaging Gesture recognition Real-time systems Biomedical monitoring Low latency communication Monitoring

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Design of the Continuous Gravity-Driven Multiple-Effect Thermal System (G-METS) for Efficient Low-Cost Magnesium Recycling

Design of the Continuous Gravity-Driven Multiple-Effect Ther...

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Magnesium Technology Symposium held during the 152nd TMS Annual Meeting and Exhibition, TMS 2023

作者： Sehar, Daniel Mcarthur Espinosa, Gabriel Telgerafchi, Armaghan Ehsani Chinwego, Chinenye Lynch, Keira Perrin, Benjamin Powell, Adam Materials Science and Engineering Program Department of Mechanical Engineering Worcester Polytechnic Institute WorcesterMA United States Department of Mechanical Engineering Worcester Polytechnic Institute WorcesterMA United States 100 Institute Rd WorcesterMA01609 United States

ISBN: (纸本)9783031226458

Recent global supply shortages, combined with need for light-weight structural components for efficient transportation, have led to very high prices for magnesium due to its low density and high part stiffness/weight. This study continues prior work on magnesium recycling using multiple-effect distillation with gravity as the parameter to create the pressure difference between effects, called G-METS. The long-term vision is for continuous distillation, but experiments to date have only used batch distillers with maximum rate of 1 kg/h. and minimum energy consumption of 2 kWh/kg. This study presents the design of laboratory-scale continuous distiller including a custom-made furnace to sustain a high-power density and temperature gradient for rapid boiling and efficient recovery of magnesium. © The Minerals, Metals & Materials Society 2023.

关键词： Distillation

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Improving Intersession Reproducibility for Forearm Ultrasound based Hand Gesture Classification through an Incremental Learning Approach

arXiv

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arXiv 2024年

作者： Bimbraw, Keshav Rothenberg, Jack Zhang, Haichong K. Robotics Engineering Worcester Polytechnic Institute Worcester United States Robotics and Biomedical Engineering Worcester Polytechnic Institute Worcester United States

关键词： Convolutional neural networks

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Laparoscopic Photoacoustic Imaging System Integrated with the da Vinci Surgical System

Laparoscopic Photoacoustic Imaging System Integrated with th...

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Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Gao, Shang Wang, Yang Zhou, Haoying Yang, Kehan Jiang, Yiwei Lu, Liang Wang, Shiyue Ma, Xihan Nephew, Benjamin C. Fichera, Loris Fischer, Gregory S. Zhang, Haichong K. Robotics Engineering Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Computer Sciencev Biology & Biotechnology Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Neuroscience Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Biomedical Engineering Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Mechanical & Materials Engineering Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States Electrical & Computer Engineering Worcester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States

ISBN: (纸本)9781510660373

This paper presents the design, fabrication, and experimental validation of a photoacoustic (PA) imaging probe for robotic surgery. PA is an emerging imaging modality that combines the high penetration of ultrasound (US) imaging with high optical contrast. When equipped with a PA probe, a surgical robot can provide intraoperative guidance to the operating physician, alerting them of the presence of vital substrate anatomy (e.g., nerves or blood vessels) invisible to the naked eye. Our probe is designed to work with the da Vinci surgical system to produce three-dimensional PA images: We propose an approach wherein the robot provides remote center-of-motion (RCM) scanning across a region of interest, and successive PA tomographic images are acquired and interpolated to produce a three-dimensional PA image. To demonstrate the accuracy of the PA guidance in scanning 3D tomography actuated by the robot, we conducted an experimental study that involved the imaging of a multi-layer wire phantom. The computed Target Registration Error (TRE) between the acquired PA image and the phantom was 1.5567±1.3605 mm. The ex vivo study demonstrated the function of the proposed laparoscopic device in 3D vascular detection. These results indicate the potential of our PA system to be incorporated into clinical robotic surgery for functional anatomical guidance. © 2023 SPIE.

关键词： Robotic surgery

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