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Evaluation of occupational doses in surgical staff via Monte Carlo simulation

Applied Radiation and Isotopes 2025年 224卷 111894页

作者： Machado, Karen L. Maschio, Alessa Guimarães, Guilherme B. Santos, William S. Neves, Lucio P. Perini, Ana P. Postgraduate Program in Biomedical Engineering of Federal University of Uberlândia MG Uberlândia Brazil Institute of Physics of Federal University of Uberlândia MG Uberlândia Brazil Federal University of Sergipe Center for Exact Sciences and Technology Department of Physics SE São Cristóvão Brazil

This study evaluated radiation exposure during fluoroscopy-guided surgical procedures using Monte Carlo simulations. The methodology involved modeling femoral osteosynthesis scenarios, representing both the patient and the occupationally exposed individual (OEI) with a female reference phantom from ICRP Publication 145. The study included 24 simulations, categorized into posteroanterior (PA) and lateral cross (LC) projections, with tube voltages ranging from 60 to 90 kV for PA and 70 to 100 kV for LC. Protective equipment, such as aprons, suspended glass, and curtains, was tested using alternative materials to lead, including bismuth and tungsten. The results demonstrated that bismuth and tungsten exhibited varying levels of radiation attenuation efficiency compared to lead, with performance expressed as percentages relative to lead-based equipment. While certain scenarios showed that bismuth and tungsten outperformed lead in radiation protection, other scenarios highlighted their limitations. For instance, at 90 kV in the PA projection, both materials resulted in significant increases in radiation dose compared to lead. © 2025 Elsevier Ltd

关键词： Reactor shielding

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Phortex: Physically-Informed Operational Robotic Trajectories for Scientific Expeditions

IEEE Transactions on Field Robotics

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IEEE Transactions on Field Robotics 2024年 1卷 446-475页

作者： Victoria L. Preston Genevieve E. Flaspohler John W. Fisher Anna P. M. Michel Nicholas Roy Applied Ocean Physics and Engineering Massachusetts Institute of Technology and Woods Hole Oceanographic Institution Joint Program Cambridge MA USA Olin College of Engineering Needham MA USA Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Rhiza Research Oakland CA USA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Woods Hole MA USA

Mobile robots are increasingly used to collect valuable in situ samples during scientific expeditions. However, many phenomena of scientific interest—deep-sea hydrothermal plumes, algal blooms, warm-core eddies, and lava flows—are spatiotemporal distributions that evolve on spatial and temporal scales that complicate sample collection. Here, we consider the problem of charting the space-time dynamics of deep-sea hydrothermal plumes with the state-of-the-art autonomous underwater vehicle (AUV) Sentry. In the hydrothermal plume charting problem, the plume state is driven by complicated and unobserved dynamics in the deep sea. To effectively sample the moving plume, an autonomy system must infer plume dynamics from sparse, point observations, while respecting operational constraints of AUV Sentry that restrict the set of possible trajectories to nonadaptive, uniform-coverage patterns. We frame the plume charting problem as a sequential decision-making problem, and formulate a mission planner Phortex: physically-informed operational robotic trajectories for expeditions that strategically designs full mission trajectories for Sentry, where each mission plan is informed by the observations of the last. Phortex is composed of a trajectory optimizer that maximizes expected samples collected within a moving plume, and Phumes: physically-informed uncertainty models for environment spatiotemporality, a modeling framework that leverages an embedded simulator of idealized plume physics as an inductive bias to enable dynamics learning from extreme partial observations and few Sentry deployments. In both simulation and in field trials at a hydrothermal site in the Gulf of California, we demonstrate that Sentry using Phortex learns to track a moving hydrothermal plume and gather samples that significantly improve upon baseline spatial and temporal diversity for use in downstream science tasks.

关键词： Trajectory Robots Robot sensing systems Vehicle dynamics Spatiotemporal phenomena Predictive models Decision making Uncertainty Data models

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Antiferromagnetic V2O3 based exchange coupling

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Physical Review Materials 2024年第5期8卷 054407-054407页

作者： Ralph el Hage Tianxing D. Wang Junjie Li Ali C. Basaran Felipe Torres Ivan K. Schuller Department of Physics and Center for Advanced Nanoscience University of California San Diego La Jolla California 92093 USA Materials Science and Engineering Program University of California San Diego La Jolla California 92093 USA Department of Physics Universidad de Chile Santiago 7800024 Chile Center for the Development of Nanoscience and Nanotechnology CEDENNA Santiago 9170124 Chile

Vanadium sesquioxide (V2O3) is a strongly correlated electronic material that famously undergoes a triple coupled first-order transition where it transitions from a paramagnetic metal with a rhombohedral structure at high temperature to an antiferromagnetic insulator with a monoclinic structure. While several studies have used one of both electronic and structural transitions to control the properties of a heterostructure, evidence of magnetic coupling has notoriously yet to be found. In this paper, we report on a robust magnetic coupling between the antiferromagnetic (AFM) V2O3 and ferromagnetic (FM) Permalloy (Py) layers that results in a significant exchange bias and strain-induced coercivity enhancement. We provide a temperature and angle-dependent study of magnetic properties, which clearly indicates exchange bias at the AFM/FM interface that appears at the onset of the metal-insulator transition. The magnitude of the exchange bias is strongest when the field is applied along the [001] V2O3 crystallographic orientation which corresponds to an AFM spin configuration on the [110] surface. This opens the door to designing and implementing novel functionalities in transition metal oxide-based computing using the connection between magnetism and the metal-insulator transition.

关键词： First order phase transitions Magnetic anisotropy Magnetic coupling Magnetism Magnetization dynamics Antiferromagnets Magnetic thin films Thin films Kerr effect Magnetization measurements X-ray reflectivity

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3D Magnetization Reconstruction for Lorentz Microscopy using Differential programming

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1756-1757页

作者： McCray, Arthur R C Cherukara, Mathew Petford-Long, Amanda K. Phatak, Charudatta Materials Science Division Argonne National Laboratory Lemont IL United States Applied Physics Program Northwestern University Evanston IL United States Advanced Photon Source Argonne National Laboratory Lemont IL United States Department of Materials Science and Engineering Northwestern University Evanston IL United States

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HIGH-PERFORMANCE THERMOPLASTIC-BASED MAGNETIC COMPOSITES

HIGH-PERFORMANCE THERMOPLASTIC-BASED MAGNETIC COMPOSITES

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SAMPE 2023 Conference and Exhibition

作者： Arigbabowo, Oluwasola K. Tate, Jitendra Geerts, Wilhelmus J. Texas State University Materials Science Engineering and Commercialization Program 601 University Drive San MarcosTX78666 United States Ingram School of Engineering Texas State University 601 University Drive San MarcosTX78666 United States Department of Physics Texas State University 601 University Drive San MarcosTX78666 United States

ISBN: (纸本)9781934551431

Magnetic polymer-based composites combine the cost-effectiveness, low density, and manufacturing flexibility of conventional polymers with the unique characteristics of magnetic powders/fillers to form multifunctional magneto polymeric composites that offer superior properties to conventional materials. At higher temperatures, magnetic properties change significantly and the particles within the magnetic powders experience sporadic motion due to the heat which causes misalignment of the magnetic domains, leading to a decrease in magnetism. Due to these adverse temperature effects, high-performance polymers such as polyetheretherketone (PEEK), polyetherimide (PEI) or other high-temperature thermoplastics have been considered suitable matrix for the magnetic fillers, thereby creating a much wider usage for magneto polymeric composite in applications that requires higher temperature (typically above 175 oC). Thus, this review discusses the fabrication processes-injection molding, fused filament fabrication;magnetic performance, and applications of high-performance thermoplastic-based magnetic composites that can be viable for stringent engineering devices such as sensors, actuators, motors, and generators. © 2023 Soc. for the Advancement of Material and Process engineering. All rights reserved.

关键词： Fabrication

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Study of SiGeSn-based Multiple Quantum Well Laser for Photonics Integrated Circuits 18

Study of SiGeSn-based Multiple Quantum Well Laser for Photon...

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Silicon Photonics XVIII 2023

作者： Olorunsola, Oluwatobi Said, Abdulla Ojo, Solomon Stanchu, Hryhorii Abernathy, Grey Amoah, Sylvester Saha, Samir Wangila, Emmanuel Grant, Joshua Acharya, Sudip Jheng, Yue-Tong Chang, Guo-En Li, Baohua Salamo, Gregory Yu, Shui-Qing Du, Wei Department of Electrical Engineering University of Arkansas FayettevilleAR72701 United States Material Science and Engineering Program University of Arkansas FayettevilleAR72701 United States Institute for Nanoscience and Engineering University of Arkansas FayettevilleAR72701 United States Department of Physics University of Arkansas FayettevilleAR72701 United States Department of Mechanical Engineering National Chun Cheng University Chiayi County62101 Taiwan Arktonics LLC 1339 South Pinnacle Drive FayettevilleAR72701 United States

ISBN: (纸本)9781510659575

As one of two mainstream platforms, photonics integrated circuits (PICs) on Si photonics platform benefits from the mature complementary metal-oxide-semiconductor (CMOS) manufacturing capabilities and allows for the processing of Si-based PICs with ultra-high volume and low cost. Recent studies of SiGeSn materials, which yield true direct bandgap with sufficient Sn incorporation, hold great promise for PICs featuring scalable, cost-effective, and power-efficient. While the exciting developments in bulk devices including lasers, light emitting diodes (LEDs), and photodetector were reported, the quantum wells (QWs) structure and devices have been investigated targeting the dramatically improved and/or novel device performance via variety of quantum confinement effects. In this work, we report the recent progress on SiGeSn QW development. Particularly, the study of MQW laser is presented. Devices with higher optical confinement factors exhibit clear lasing confirmed by the threshold characteristic and the emission spectra below and above threshold. Only spontaneous emission was observed with the thinner cap layer samples. On the other hand, samples with thicker cap layers of 250 and 290 nm exhibit clear lasing at 77 K with thresholds of 214 and 664 kW/cm2, respectively. These promising results establish the guidance for the device design and pave the way for the SiGeSn QW devices towards future high-performance PICs on Si platform. © 2023 SPIE.

关键词： Timing circuits

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Nuclear mass predictions based on convolutional neural network

arXiv

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arXiv 2024年

作者： Lu, Yanhua Shang, Tianshuai Du, Pengxiang Li, Jian Liang, Haozhao Niu, Zhongming College of Physics Jilin University Changchun130012 China Department of Physics Graduate School of Science The University of Tokyo Tokyo113-0033 Japan RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program Wako351-0198 Japan School of Physics and Optoelectronic Engineering Anhui University Hefei230601 China

A convolutional neural network (CNN) is employed to investigate nuclear mass. By introducing the masses of neighboring nuclei and the paring effects at the input layer of the network, local features of the target nucleus are extracted to predict its mass. Then, through learning the differences between the experimental nuclear masses and the predicted nuclear masses by the WS4 model, a new global-local model (CNN-WS4) is developed, which incorporates both the global nuclear mass model and local features. Due to the incorporation of local features, the CNN-WS4 model achieves high accuracy on the training set. When extrapolating for newly emerged nuclei, the CNN-WS4 also exhibits appreciable stability, thereby demonstrating its robustness. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Topology of three-dimensional Dirac semimetals and quantum spin Hall systems without gapless edge modes

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Physical Review Research 2023年第1期5卷 L012019-L012019页

作者： Alexander C. Tyner Shouvik Sur Danilo Puggioni James M. Rondinelli Pallab Goswami Graduate Program in Applied Physics Northwestern University Evanston Illinois 60208USA Department of Physics and Astronomy Northwestern University Evanston Illinois 60208 USA Department of Materials Science and Engineering Northwestern University Illinois 60208 USA Northwestern Argonne Institute for Science and Engineering Evanston Illinois 60208 USA

The quantum spin Hall states are usually expected to possess gapless, helical edge modes. We show that the generic, n-fold-symmetric, momentum planes of three-dimensional, stable Dirac semimetals, which are orthogonal to the direction of nodal separation are examples of generalized quantum spin Hall systems, that possess quantized, spin or relative Chern numbers as bulk topological invariants, and gapped edge modes. We demonstrate these planes and the celebrated Bernevig-Zhang-Hughes model support identical quantized, non-Abelian Berry flux of magnitude 2π. Hence, they display identical quantized, topological response such as spin-charge separation and pumping of one Kramers-pair or SU(2) doublet, when probed with a magnetic flux tube. The Dirac points are identified as unit-strength, monopoles of SO(5) Berry connection, describing topological phase transitions between generalized quantum spin Hall and trivial insulators. Our work identifies precise bulk invariant and quantized response of Dirac semimetals, which are not diagnosed by nested Wilson loops and filling anomaly of corner-localized-states, and shows that many two-dimensional higher-order topological insulators can be understood as generalized quantum spin Hall systems.

关键词： Fractionalization Geometric & topological phases Spintronics Topological insulators Topological phase transition Topological phases of matter

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Evolution of magnetism in the magnetic topological semimetal NdSbxTe2−x+δ

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Physical Review B 2024年第18期109卷 184429-184429页

作者： Santosh Karki Chhetri Rabindra Basnet Jian Wang Krishna Pandey Gokul Acharya Md Rafique Un Nabi Dinesh Upreti Josh Sakon Mansour Mortazavi Jin Hu Department of Physics University of Arkansas Fayetteville Arkansas 72701 USA Department of Chemistry and Physics University of Arkansas at Pine Bluff Pine Bluff Arkansas 71603 USA Department of Chemistry and Biochemistry Wichita State University Wichita Kansas 67260 USA Materials Science and Engineering Program Institute for Nanoscience and Engineering University of Arkansas Fayetteville Arkansas 72701 USA Department of Chemistry and Biochemistry University of Arkansas Fayetteville Arkansas 72701 USA

Magnetic topological semimetals LnSbTe (Ln=lanthanide) have attracted intensive attention because of the presence of interplay between magnetism, topological, and electron correlations depending on the choices of magnetic Ln elements. Recently, varying Sb-Te composition has been found to effectively control the electronic and magnetic states in LnSbxTe2−x. With this motivation, we report the evolution of magnetic properties with Sb-Te substitution in NdSbxTe2−x+δ, (0≤x≤1). Our work reveals the interesting nonmonotonic change in magnetic ordering temperature with varying composition stoichiometry. In addition, reducing the Sb content x drives the reorientation of moments from in-plane (ab-plane) to out-of-plane (c-axis) direction that results in the distinct magnetic structures for two end compounds NdTe2 (x=0) and NdSbTe (x=1). Furthermore, the moment orientation in NdSbxTe2−x+δ is also found to be strongly tunable upon application of a weak magnetic field, leading to rich magnetic phases depending on the composition stoichiometry, temperature, and magnetic field. Such strong tuning of magnetism in this material establishes it as a promising platform for investigating tunable topological states and correlated topological physics.

关键词： Charge density waves Magnetic phase transitions Spin reorientation transition

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Parameter Identification of Signal Attenuation for High Speed Rail Communication System Using Grey Box Neural Network

Parameter Identification of Signal Attenuation for High Spee...

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International Conference on Instrumentation Control and Automation (ICA)

作者： Selvi Lukman Yul Yunazwin Nazaruddin Endra Joelianto Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Department of Engineering Physics Instrumentation Control Research Group Institut Teknologi Bandung Bandung Indonesia National Center for Sustainable Transportation Technology Bandung Indonesia

A reliable connected digital railways must face a huge challenge of network and frequency planning in order to deploy a dedicated infrastructure for High Speed Rail (HSR). This paper investigates the parameter identification of signal attenuation for HSR in a free space propagation case. A neural network based optimization of Grey Box Neural Network (GBNN) is utilized to validate the parameter identification results. Satisfying results of minimum convergences of RMSE = 1.6371 and MAPE = 0.015 have been achieved. Furthermore, the ability of identified parameter in adjusting the dynamic scenario of the real signal attenuation measurement dataset is displayed when the distance is 118.45 meter and the path loss value is 116.82 dB. Through this applied neural network based technique, network designers are able to plan and design the best possible of network performances and frequency planning for HSR.

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