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McCaskill JS, Karnaushenko D, Zhu M, Schmidt OG. Microelectronic Morphogenesis: Smart Materials with Electronics Assembling into Artificial Organisms. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2306344. [PMID: 37814374 DOI: 10.1002/adma.202306344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/27/2023] [Indexed: 10/11/2023]
Abstract
Microelectronic morphogenesis is the creation and maintenance of complex functional structures by microelectronic information within shape-changing materials. Only recently has in-built information technology begun to be used to reshape materials and their functions in three dimensions to form smart microdevices and microrobots. Electronic information that controls morphology is inheritable like its biological counterpart, genetic information, and is set to open new vistas of technology leading to artificial organisms when coupled with modular design and self-assembly that can make reversible microscopic electrical connections. Three core capabilities of cells in organisms, self-maintenance (homeostatic metabolism utilizing free energy), self-containment (distinguishing self from nonself), and self-reproduction (cell division with inherited properties), once well out of reach for technology, are now within the grasp of information-directed materials. Construction-aware electronics can be used to proof-read and initiate game-changing error correction in microelectronic self-assembly. Furthermore, noncontact communication and electronically supported learning enable one to implement guided self-assembly and enhance functionality. Here, the fundamental breakthroughs that have opened the pathway to this prospective path are reviewed, the extent and way in which the core properties of life can be addressed are analyzed, and the potential and indeed necessity of such technology for sustainable high technology in society is discussed.
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Affiliation(s)
- John S McCaskill
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09126, Chemnitz, Germany
- Material Systems for Nanoelectronics, Chemnitz University of Technology, 09126, Chemnitz, Germany
- European Centre for Living Technology (ECLT), Ca' Bottacin, Dorsoduro 3911, Venice, 30123, Italy
| | - Daniil Karnaushenko
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09126, Chemnitz, Germany
- Material Systems for Nanoelectronics, Chemnitz University of Technology, 09126, Chemnitz, Germany
| | - Minshen Zhu
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09126, Chemnitz, Germany
- Material Systems for Nanoelectronics, Chemnitz University of Technology, 09126, Chemnitz, Germany
| | - Oliver G Schmidt
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09126, Chemnitz, Germany
- Material Systems for Nanoelectronics, Chemnitz University of Technology, 09126, Chemnitz, Germany
- European Centre for Living Technology (ECLT), Ca' Bottacin, Dorsoduro 3911, Venice, 30123, Italy
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Kumar A, Kempski Leadingham KM, Kerensky MJ, Sankar S, Thakor NV, Manbachi A. Visualizing tactile feedback: an overview of current technologies with a focus on ultrasound elastography. FRONTIERS IN MEDICAL TECHNOLOGY 2023; 5:1238129. [PMID: 37854637 PMCID: PMC10579802 DOI: 10.3389/fmedt.2023.1238129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 09/14/2023] [Indexed: 10/20/2023] Open
Abstract
Tissue elasticity remains an essential biomarker of health and is indicative of irregularities such as tumors or infection. The timely detection of such abnormalities is crucial for the prevention of disease progression and complications that arise from late-stage illnesses. However, at both the bedside and the operating table, there is a distinct lack of tactile feedback for deep-seated tissue. As surgical techniques advance toward remote or minimally invasive options to reduce infection risk and hasten healing time, surgeons lose the ability to manually palpate tissue. Furthermore, palpation of deep structures results in decreased accuracy, with the additional barrier of needing years of experience for adequate confidence of diagnoses. This review delves into the current modalities used to fulfill the clinical need of quantifying physical touch. It covers research efforts involving tactile sensing for remote or minimally invasive surgeries, as well as the potential of ultrasound elastography to further this field with non-invasive real-time imaging of the organ's biomechanical properties. Elastography monitors tissue response to acoustic or mechanical energy and reconstructs an image representative of the elastic profile in the region of interest. This intuitive visualization of tissue elasticity surpasses the tactile information provided by sensors currently used to augment or supplement manual palpation. Focusing on common ultrasound elastography modalities, we evaluate various sensing mechanisms used for measuring tactile information and describe their emerging use in clinical settings where palpation is insufficient or restricted. With the ongoing advancements in ultrasound technology, particularly the emergence of micromachined ultrasound transducers, these devices hold great potential in facilitating early detection of tissue abnormalities and providing an objective measure of patient health.
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Affiliation(s)
- Avisha Kumar
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
- HEPIUS Innovation Lab, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Kelley M. Kempski Leadingham
- HEPIUS Innovation Lab, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Max J. Kerensky
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
- HEPIUS Innovation Lab, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Sriramana Sankar
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Nitish V. Thakor
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Amir Manbachi
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
- HEPIUS Innovation Lab, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Fu C, Gao C, Zhang W. A Digital-Twin Framework for Predicting the Remaining Useful Life of Piezoelectric Vibration Sensors with Sensitivity Degradation Modeling. SENSORS (BASEL, SWITZERLAND) 2023; 23:8173. [PMID: 37837003 PMCID: PMC10575226 DOI: 10.3390/s23198173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 09/20/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023]
Abstract
Piezoelectric vibration sensors (PVSs) are widely applied to vibration detection in aerospace engines due to their small size, high sensitivity, and high-temperature resistance. The precise prediction of their remaining useful life (RUL) under high temperatures is crucial for their maintenance. Notably, digital twins (DTs) provide enormous data from both physical structures and virtual models, which have potential in RUL predictions. Therefore, this work establishes a DT framework containing six modules for sensitivity degradation detection and assessment on the foundation of a five-dimensional DT model. In line with the sensitivity degradation mechanism at high temperatures, a DT-based RUL prediction was performed. Specifically, the PVS sensitivity degradation was described by the Wiener-Arrhenius accelerated degradation model based on the acceleration factor constant principle. Next, an error correction method for the degradation model was proposed using real-time data. Moreover, parameter updates were conducted using a Bayesian method, based on which the RUL was predicted using the first hitting time. Extensive experiments on distinguishing PVS samples demonstrate that our model achieves satisfying performance, which significantly reduces the prediction error to 8 h. A case study was also conducted to provide high RUL prediction accuracy, which further validates the effectiveness of our model in practical use.
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Affiliation(s)
- Chengcheng Fu
- School of Energy and Power Engineering, Beihang University, Beijing 100191, China;
| | - Cheng Gao
- School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;
| | - Weifang Zhang
- School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;
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Herickhoff CD, van Schaijk R. cMUT technology developments. Z Med Phys 2023; 33:256-266. [PMID: 37316428 PMCID: PMC10517396 DOI: 10.1016/j.zemedi.2023.04.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/28/2023] [Accepted: 04/29/2023] [Indexed: 06/16/2023]
Abstract
Capacitive micromachined ultrasonic transducer (cMUT) technology has steadily advanced since its advent in the mid-1990's. Though cMUTs have not supplanted piezoelectric transducers for medical ultrasound imaging to date, researchers and engineers are continuing to improve cMUTs and leverage unique cMUT characteristics toward new applications. While not intended to be an exhaustive review of every aspect of cMUT state-of-the-art, this article provides a brief overview of cMUT benefits, challenges, and opportunities, as well as recent progress in cMUT research and translation.
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Affiliation(s)
- Carl D Herickhoff
- Department of Biomedical Engineering, University of Memphis, TN, USA.
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Khairalseed M, Hoyt K. High-Resolution Ultrasound Characterization of Local Scattering in Cancer Tissue. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:951-960. [PMID: 36681609 PMCID: PMC9974749 DOI: 10.1016/j.ultrasmedbio.2022.11.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 11/21/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
Ultrasound (US) has afforded an approach to tissue characterization for more than a decade. The challenge is to reveal hidden patterns in the US data that describe tissue function and pathology that cannot be seen in conventional US images. Our group has developed a high-resolution analysis technique for tissue characterization termed H-scan US, an imaging method used to interpret the relative size of acoustic scatterers. In the present study, the objective was to compare local H-scan US image intensity with registered histologic measurements made directly at the cellular level. Human breast cancer cells (MDA-MB 231, American Type Culture Collection, Manassas, VA, USA) were orthotopically implanted into female mice (N = 5). Tumors were allowed to grow for approximately 4 wk before the study started. In vivo imaging of tumor tissue was performed using a US system (Vantage 256, Verasonics Inc., Kirkland, WA, USA) equipped with a broadband capacitive micromachined ultrasonic linear array transducer (Kolo Medical, San Jose, CA, USA). A 15-MHz center frequency was used for plane wave imaging with five angles for spatial compounding. H-scan US image reconstruction involved use of parallel convolution filters to measure the relative strength of backscattered US signals. Color codes were applied to filter outputs to form the final H-scan US image display. For histologic processing, US imaging cross-sections were carefully marked on the tumor surface, and tumors were excised and sliced along the same plane. By use of optical microscopy, whole tumor tissue sections were scanned and digitized after nuclear staining. US images were interpolated to have the same number of pixels as the histology images and then spatially aligned. Each nucleus from the histologic sections was automatically segmented using custom MATLAB software (The MathWorks Inc., Natick, MA, USA). Nuclear size and spacing from the histology images were then compared with local H-scan US image features. Overall, local H-scan US image intensity exhibited a significant correlation with both cancer cell nuclear size (R2 > 0.27, p < 0.001) and the inverse relationship with nuclear spacing (R2 > 0.17, p < 0.001).
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Affiliation(s)
- Mawia Khairalseed
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA
| | - Kenneth Hoyt
- Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA.
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Wu S, Liu K, Wang W, Li W, Wu T, Yang H, Li X. Aluminum Nitride Piezoelectric Micromachined Ultrasound Transducer Arrays for Non-Invasive Monitoring of Radial Artery Stiffness. MICROMACHINES 2023; 14:539. [PMID: 36984946 PMCID: PMC10052539 DOI: 10.3390/mi14030539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 02/19/2023] [Accepted: 02/22/2023] [Indexed: 06/18/2023]
Abstract
An aluminum nitride (AlN) piezoelectric micromachined ultrasound transducer (PMUT) array was proposed and fabricated for non-invasive radial artery stiffness monitoring, which could be employed in human vascular health monitoring applications. Using surface micromachining techniques, four hexagonal PMUT arrays were fabricated within a chip area of 3 × 3 mm2. The mechanical displacement sensitivity and quality factor of a single PMUT were tested and found to be 24.47 nm/V at 5.94 MHz and 278 (in air), respectively. Underwater pulse-echo tests for the array demonstrated a -3 dB bandwidth of 0.76 MHz at 3.75 MHz and distance detection limit of approximately 25 mm. Using the PMUT array as an ultrasonic probe, the depth and diameter changes over cardiac cycles of the radial artery were measured to be approximately 3.8 mm and 0.23 mm, respectively. Combined with blood pressure calibration, the biomechanical parameters of the radial artery vessel were extracted using a one-dimensional vascular model. The cross-sectional distensibility, compliance, and stiffness index were determined to be 4.03 × 10-3/mmHg, 1.87 × 10-2 mm2/mmHg, and 5.25, respectively, consistent with the newest medical research. The continuous beat-to-beat blood pressure was also estimated using this model. This work demonstrated the potential of miniaturized PMUT devices for human vascular medical ultrasound applications.
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Affiliation(s)
- Sheng Wu
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
- School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
- School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kangfu Liu
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
- School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
- School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenjing Wang
- East China Institute of Photo-Electron IC, Bengbu 233030, China
| | - Wei Li
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
- School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tao Wu
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
- School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
- School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Heng Yang
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
- School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xinxin Li
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
- School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
- School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
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Yuan J, Li Z, Ma Q, Li J, Li Z, Zhao Y, Qin S, Shi X, Zhao L, Yang P, Luo G, Wang X, Teh KS, Jiang Z. Noninvasive fluid bubble detection based on capacitive micromachined ultrasonic transducers. MICROSYSTEMS & NANOENGINEERING 2023; 9:20. [PMID: 36844939 PMCID: PMC9946994 DOI: 10.1038/s41378-023-00491-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 12/06/2022] [Accepted: 01/12/2023] [Indexed: 06/18/2023]
Abstract
Ultrasonic fluid bubble detection is important in industrial controls, aerospace systems and clinical medicine because it can prevent fatal mechanical failures and threats to life. However, current ultrasonic technologies for bubble detection are based on conventional bulk PZT-based transducers, which suffer from large size, high power consumption and poor integration with ICs and thus are unable to implement real-time and long-term monitoring in tight physical spaces, such as in extracorporeal membrane oxygenation (ECMO) systems and dialysis machines or hydraulic systems in aircraft. This work highlights the prospect of capacitive micromachined ultrasonic transducers (CMUTs) in the aforementioned application situations based on the mechanism of received voltage variation caused by bubble-induced acoustic energy attenuation. The corresponding theories are established and well validated using finite element simulations. The fluid bubbles inside a pipe with a diameter as small as 8 mm are successfully measured using our fabricated CMUT chips with a resonant frequency of 1.1 MHz. The received voltage variation increases significantly with increasing bubble radii in the range of 0.5-2.5 mm. Further studies show that other factors, such as bubble positions, flow velocities, fluid medium types, pipe thicknesses and diameters, have negligible effects on fluid bubble measurement, demonstrating the feasibility and robustness of the CMUT-based ultrasonic bubble detection technique.
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Affiliation(s)
- Jiawei Yuan
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Zhikang Li
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
- Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, 265503 Yantai, China
| | - Qi Ma
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Jie Li
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi’an, 710049 Xi’an, China
| | - Zixuan Li
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Yihe Zhao
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Shaohui Qin
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Xuan Shi
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Libo Zhao
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
- Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, 265503 Yantai, China
| | - Ping Yang
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
- Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, 265503 Yantai, China
| | - Guoxi Luo
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
- Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, 265503 Yantai, China
| | - Xiaozhang Wang
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
| | - Kwok Siong Teh
- School of Engineering, San Francisco State University, San Francisco, CA 94132 USA
| | - Zhuangde Jiang
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, Xi’an Jiaotong University (Yantai) Research Institute for Intelligent Sensing Technology and Systems, Xi’an Jiaotong University, 710049 Xi’an, China
- School of Mechanical Engineering, Xi’an Jiaotong University, 710049 Xi’an, China
- Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing, 265503 Yantai, China
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Gholampour A, Muller JW, Cano C, van Sambeek MRHM, Lopata R, Schwab HM, Wu M. Multiperspective Photoacoustic Imaging Using Spatially Diverse CMUTs. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:16-24. [PMID: 36350862 DOI: 10.1109/tuffc.2022.3220999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Photoacoustic imaging (PAI) is a promising technique to assess different constituents in tissue. In PAI, the propagating waves are low-amplitude, isotropic, and broadband. A common approach in PAI is the use of a single linear or curved piezoelectric transducer array to perform both PA and ultrasound imaging. These systems provide freedom, agility, and versatility for performing imaging, but have limited field of view (FOV) and directivity that degrade the final image quality. Capacitive micromachined ultrasonic transducers (CMUTs) have a great potential to be used for PAI since they provide larger bandwidth and better cost efficiency. In this study, to improve the FOV, resolution, and contrast, we propose a multiperspective PAI (MP-PAI) approach using multiple CMUTs on a flexible array with shared channels. The designed array was used to perform MP-PAI in an in vitro experiment using a plaque mimicking phantom where the images were compounded both incoherently and coherently. The MP-PAI approach showed a significant improvement in overall image quality. Using only three CMUTs led to about 20% increase in generalized-contrast-to-noise ratio (gCNR), 2-dB improvement in peak signal-to-noise ratio (PSNR), and double the structural coverage in comparison to a single CMUT setup. In numerical studies, the MP-PAI was thoroughly evaluated for both the coherent and incoherent compounding methods. The assessments showed that the image quality further improved for increased number of transducers and angular coverage. For 15 transducers, the improvement for resolution and contrast could be up to three times the amount in a single-perspective image. Nonetheless, the most prominent improvement of MP-PAI was its ability to resolve the structural information of the phantoms.
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Zhao L, Annayev M, Oralkan O, Jia Y. An Ultrasonic Energy Harvesting IC Providing Adjustable Bias Voltage for Pre-Charged CMUT. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2022; 16:842-851. [PMID: 35671313 DOI: 10.1109/tbcas.2022.3178581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Ultrasonic wireless power transmission (WPT) using pre-charged capacitive micromachined ultrasonic transducers (CMUT) is drawing great attention due to the easy integration of CMUT with CMOS techniques. Here, we present an integrated circuit (IC) that interfaces with a pre-charged CMUT device for ultrasonic energy harvesting. We implemented an adaptive high voltage charge pump (HVCP) in the proposed IC, which features low power, overvoltage stress (OVS) robustness, and a wide output range. The ultrasonic energy harvesting IC is fabricated in the 180 nm HV BCD process and occupies a 2 × 2.5 mm2 silicon area. The adaptive HVCP offers a 2× - 12× voltage conversion ratio (VCR), thereby providing a wide bias voltage range of 4 V-44 V for the pre-charged CMUT. Moreover, a VCR tunning finite state machine (FSM) implemented in the proposed IC can dynamically adjust the VCR to stabilize the HVCP output (i.e., the pre-charged CMUT bias voltage) to a target voltage in a closed-loop manner. Such a closed-loop control mechanism improves the tolerance of the proposed IC to the received power variation caused by misalignments, amount of transmitted power change, and/or load variation. Besides, the proposed ultrasonic energy harvesting IC has an average power consumption of 35 μW-554 μW corresponding to the HVCP output from 4 V-44 V. The CMUT device with a local surface acoustic intensity of 3.78 mW/mm2, which is well below the FDA limit for power flux (7.2 mW/mm2), can deliver sufficient power to the IC.
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