Guido T. van Moolenbroek, Tania Patiño, J. Llop, S. Sánchez
Medical imaging serves to obtain anatomical and physiological data, supporting medical diagnostics as well as providing therapeutic evaluation and guidance. A variety of contrast agents have been developed to enhance the recorded signals and to provide molecular imaging. However, fast clearance from the body or nonspecific biodistribution often limit their efficiency, constituting challenges that need to be overcome. Nanoparticle‐based systems are currently emerging as versatile and highly integrated platforms providing improved circulating times, tissue specificity, high loading capacity for signaling moieties, and multimodal imaging features. Furthermore, nanoengineered devices can be tuned for specific applications and the development of responsive behaviors. Responses include in situ modulation of nanoparticle size, increased intratissue mobility through active propulsion of motorized particles, and active modulation of the particle surroundings such as the extracellular matrix for an improved penetration and retention at the desired locations. Once accumulated in the targeted tissue, smart nanoparticle‐based contrast agents can provide molecular sensing of biomarkers or characteristics of the tissue microenvironment. In this case, the signal or contrast provided by the nanosystem is responsive to the presence or concentration of an analyte. Herein, recent developments of intelligent nanosystems to improve medical imaging are presented.
{"title":"Engineering Intelligent Nanosystems for Enhanced Medical Imaging","authors":"Guido T. van Moolenbroek, Tania Patiño, J. Llop, S. Sánchez","doi":"10.1002/aisy.202000087","DOIUrl":"https://doi.org/10.1002/aisy.202000087","url":null,"abstract":"Medical imaging serves to obtain anatomical and physiological data, supporting medical diagnostics as well as providing therapeutic evaluation and guidance. A variety of contrast agents have been developed to enhance the recorded signals and to provide molecular imaging. However, fast clearance from the body or nonspecific biodistribution often limit their efficiency, constituting challenges that need to be overcome. Nanoparticle‐based systems are currently emerging as versatile and highly integrated platforms providing improved circulating times, tissue specificity, high loading capacity for signaling moieties, and multimodal imaging features. Furthermore, nanoengineered devices can be tuned for specific applications and the development of responsive behaviors. Responses include in situ modulation of nanoparticle size, increased intratissue mobility through active propulsion of motorized particles, and active modulation of the particle surroundings such as the extracellular matrix for an improved penetration and retention at the desired locations. Once accumulated in the targeted tissue, smart nanoparticle‐based contrast agents can provide molecular sensing of biomarkers or characteristics of the tissue microenvironment. In this case, the signal or contrast provided by the nanosystem is responsive to the presence or concentration of an analyte. Herein, recent developments of intelligent nanosystems to improve medical imaging are presented.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80807782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mengya Xu, Seenivasan Lalithkumar, L. Yeo, Hongliang Ren
A lack of sensory feedback often hinders minimally invasive operations. Although endoscopy has addressed this limitation to an extent, endovascular procedures such as angioplasty or stenting still face significant challenges. Sensors that rely on a clear line of sight cannot be used because it is unable to gather feedback in blood environments. During the stent deployment procedure, feedback on the deployed stent's state is critical because a partially open stent can affect the blood flow. Despite this, no robust and noninvasive clinical solutions that allow real‐time monitoring of the stent deployment exists. In recent years, radio frequency (RF)‐based sensors can detect the shape and material of an object that is hidden from the direct line of sight. Herein, the use of a 3D RF‐based imaging sensor and a novel Convolutional Neural Network (CNN) called StentNet is proposed for detecting the stent's state without a need for a clear line of sight. The StentNet achieves an overall accuracy of 90% in detecting the state of an occluded stent in the test dataset. Compared with an existing CNN model, the StentNet significantly outperforms the 3D LeNet in the evaluation metrics such as accuracy, precision, recall, and F1‐score.
{"title":"Stent Deployment Detection Using Radio Frequency‐Based Sensor and Convolutional Neural Networks","authors":"Mengya Xu, Seenivasan Lalithkumar, L. Yeo, Hongliang Ren","doi":"10.1002/aisy.202000092","DOIUrl":"https://doi.org/10.1002/aisy.202000092","url":null,"abstract":"A lack of sensory feedback often hinders minimally invasive operations. Although endoscopy has addressed this limitation to an extent, endovascular procedures such as angioplasty or stenting still face significant challenges. Sensors that rely on a clear line of sight cannot be used because it is unable to gather feedback in blood environments. During the stent deployment procedure, feedback on the deployed stent's state is critical because a partially open stent can affect the blood flow. Despite this, no robust and noninvasive clinical solutions that allow real‐time monitoring of the stent deployment exists. In recent years, radio frequency (RF)‐based sensors can detect the shape and material of an object that is hidden from the direct line of sight. Herein, the use of a 3D RF‐based imaging sensor and a novel Convolutional Neural Network (CNN) called StentNet is proposed for detecting the stent's state without a need for a clear line of sight. The StentNet achieves an overall accuracy of 90% in detecting the state of an occluded stent in the test dataset. Compared with an existing CNN model, the StentNet significantly outperforms the 3D LeNet in the evaluation metrics such as accuracy, precision, recall, and F1‐score.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"178 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73656083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Integrated circuits designed to perform mathematical operations, such as Fourier transforms and matrix multiplications, in artificial visual perception and intelligent image processing are mainly constructed of conventional logic gates. However, Boolean logic is probably not the most optimal approach for brain‐inspired computing due to the fuzzy nature of biologic neural networks. This work demonstrates an application based on programmable fuzzy‐logic gates capable of combined photoelectric computations. Such an apparatus may be used to perform image compression immediately upon acquisition without having the need to rely on interaction between separate processor and sensor modules. It is based on resistive memory devices capable of state transitions in response to both electronic and light stimulations. Material nonimplication and logical true operations are first presented. A more complex functionality for material nonimplication of a logic conjunction is then demonstrated. These gates are then used as building blocks in the design and simulation of a configurable matrix multiplication unit that effectively implements in situ image compression. A membership function (FUZZIFY) that may be used to map strict logic levels to incremental fuzzy analog ones is also shown. Finally, an approach for integrating conventional logic with a fuzzy computation is discussed.
{"title":"Programmable Photoelectric Memristor Gates for In Situ Image Compression","authors":"D. Berco, D. Ang, P. S. Kalaga","doi":"10.1002/aisy.202000079","DOIUrl":"https://doi.org/10.1002/aisy.202000079","url":null,"abstract":"Integrated circuits designed to perform mathematical operations, such as Fourier transforms and matrix multiplications, in artificial visual perception and intelligent image processing are mainly constructed of conventional logic gates. However, Boolean logic is probably not the most optimal approach for brain‐inspired computing due to the fuzzy nature of biologic neural networks. This work demonstrates an application based on programmable fuzzy‐logic gates capable of combined photoelectric computations. Such an apparatus may be used to perform image compression immediately upon acquisition without having the need to rely on interaction between separate processor and sensor modules. It is based on resistive memory devices capable of state transitions in response to both electronic and light stimulations. Material nonimplication and logical true operations are first presented. A more complex functionality for material nonimplication of a logic conjunction is then demonstrated. These gates are then used as building blocks in the design and simulation of a configurable matrix multiplication unit that effectively implements in situ image compression. A membership function (FUZZIFY) that may be used to map strict logic levels to incremental fuzzy analog ones is also shown. Finally, an approach for integrating conventional logic with a fuzzy computation is discussed.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80576656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Herein, a new method for steering liquid metals (LMs) using only a magnetic field in open 3D space is proposed. The magnetic LM is composed of the alloy Galinstan and iron particles. The 3D horizontal and vertical manipulation of a magnetic LM can be realized via an external magnetic field. The magnetically actuated LM is not only manipulated on various complex pathways in the horizontal plane, but also vertically in 3D space without the use of electrolytes and electrodes. As a proof‐of‐principle, an intelligent delivery vehicle that can avoid obstacles and traps horizontally and overcome gravity vertically to offload a cargo is designed and implemented successfully. Furthermore, a biomimetic soft robotics that can realize both in‐plane and out‐of‐plane locomotion is demonstrated using only magnetic field. The novel 3D motion of the demonstrated system facilitates the development of practical LM‐based smart structures and devices.
{"title":"3D Manipulation of Magnetic Liquid Metals","authors":"Wenqing Zhou, Qingxuan Liang, Tianning Chen","doi":"10.1002/aisy.201900170","DOIUrl":"https://doi.org/10.1002/aisy.201900170","url":null,"abstract":"Herein, a new method for steering liquid metals (LMs) using only a magnetic field in open 3D space is proposed. The magnetic LM is composed of the alloy Galinstan and iron particles. The 3D horizontal and vertical manipulation of a magnetic LM can be realized via an external magnetic field. The magnetically actuated LM is not only manipulated on various complex pathways in the horizontal plane, but also vertically in 3D space without the use of electrolytes and electrodes. As a proof‐of‐principle, an intelligent delivery vehicle that can avoid obstacles and traps horizontally and overcome gravity vertically to offload a cargo is designed and implemented successfully. Furthermore, a biomimetic soft robotics that can realize both in‐plane and out‐of‐plane locomotion is demonstrated using only magnetic field. The novel 3D motion of the demonstrated system facilitates the development of practical LM‐based smart structures and devices.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"945 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77572240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robot audition aims at developing robot's ears that work in the real world, that is, machine listening of multiple sound sources. Its critical problem is noise. Speech interfaces have become more familiar and more indispensable as smartphones and artificial intelligence (AI) speakers spread. Their critical problems are noise and multiple simultaneous speakers. Recently two technological advances have contributed to significantly improve the performance of speech interfaces and robot audition. Emerging deep learning technology has improved noise robustness of automatic speech recognition, whereas microphone array processing has improved the performance of preprocessing such as noise reduction. Herein, an overview and history of robot audition are provided together with introduction of an open‐source software for robot audition and its wide applications in the real world. Also, it is discussed how robot audition contributes to the development of computational auditory scene analysis, that is, understanding of real‐world auditory environments.
{"title":"Robot Audition and Computational Auditory Scene Analysis","authors":"K. Nakadai, Hiroshi G. Okuno","doi":"10.1002/aisy.202000050","DOIUrl":"https://doi.org/10.1002/aisy.202000050","url":null,"abstract":"Robot audition aims at developing robot's ears that work in the real world, that is, machine listening of multiple sound sources. Its critical problem is noise. Speech interfaces have become more familiar and more indispensable as smartphones and artificial intelligence (AI) speakers spread. Their critical problems are noise and multiple simultaneous speakers. Recently two technological advances have contributed to significantly improve the performance of speech interfaces and robot audition. Emerging deep learning technology has improved noise robustness of automatic speech recognition, whereas microphone array processing has improved the performance of preprocessing such as noise reduction. Herein, an overview and history of robot audition are provided together with introduction of an open‐source software for robot audition and its wide applications in the real world. Also, it is discussed how robot audition contributes to the development of computational auditory scene analysis, that is, understanding of real‐world auditory environments.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90437881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Nasti, S. Coppola, V. Vespini, S. Grilli, A. Vettoliere, C. Granata, P. Ferraro
Liquids are the primary environments in which chemical, physical, and biological processes occur. Considering a liquid bridge as liquid unit volume (LUV) element, it is highly desirable to develop reliable tools for handling such volumes. Herein, a sort of intelligent microfluidic platform based on the pyroelectric‐electrohydrodynamics (EHD) is shown for manipulating liquid bridges and thus performing multiple functions in a flexible and simple way. Several basic operations with liquid bridges using an EHD‐pin matrix based on the pyroelectric effect engineered in ferroelectric crystals are demonstrated. By activating pyro‐EHD effect in predetermined positions (pins of the array), the locomotion and handling of single or multiple LUVs simultaneously are controlled. In particular, multiple operations such as lift, displacement, mixing, stretching, and carrying vector for microparticles, are shown. These tweezers based on a pyro‐EHD matrix can open the route for a multipurpose platform driven by physical intelligence and can be used for driving locomotion and operate manifolds functionalities in many areas of science and technology at microscale as well as nanoscale with advantages to be activated by the sole thermal stimulus, controlled remotely, and in noncontact mode.
{"title":"Pyroelectric Tweezers for Handling Liquid Unit Volumes","authors":"G. Nasti, S. Coppola, V. Vespini, S. Grilli, A. Vettoliere, C. Granata, P. Ferraro","doi":"10.1002/aisy.202000044","DOIUrl":"https://doi.org/10.1002/aisy.202000044","url":null,"abstract":"Liquids are the primary environments in which chemical, physical, and biological processes occur. Considering a liquid bridge as liquid unit volume (LUV) element, it is highly desirable to develop reliable tools for handling such volumes. Herein, a sort of intelligent microfluidic platform based on the pyroelectric‐electrohydrodynamics (EHD) is shown for manipulating liquid bridges and thus performing multiple functions in a flexible and simple way. Several basic operations with liquid bridges using an EHD‐pin matrix based on the pyroelectric effect engineered in ferroelectric crystals are demonstrated. By activating pyro‐EHD effect in predetermined positions (pins of the array), the locomotion and handling of single or multiple LUVs simultaneously are controlled. In particular, multiple operations such as lift, displacement, mixing, stretching, and carrying vector for microparticles, are shown. These tweezers based on a pyro‐EHD matrix can open the route for a multipurpose platform driven by physical intelligence and can be used for driving locomotion and operate manifolds functionalities in many areas of science and technology at microscale as well as nanoscale with advantages to be activated by the sole thermal stimulus, controlled remotely, and in noncontact mode.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"200 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80128380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lorenzo Cenceschi, C. D. Santina, Giuseppe Averta, M. Garabini, Qiushi Fu, M. Santello, M. Bianchi, A. Bicchi
In the execution of repetitive tasks, humans can capitalize on experience to improve their motor performance. Prominent examples of this ability can be recognized in our capacity of grasping and manipulating in uncertain conditions. With the aim of providing a mathematical description for such behavior, experiments are considered where participants are required to lift an object with an unexpected mass distribution. By repeating multiple times the same lifting action, participants can learn the correct motor command for task accomplishment. Three models are proposed that combine reactive terms and a learned anticipatory action to explain experimental data. The models feature intratrial and intertrial memory, and the effect of slowly and fast adaptive sensory receptors. The architectures’ effectiveness in explaining experimental data is compared with a general‐purpose state of the art model. The proposed algorithms conspicuously outperform the state of the art in all the considered validation routines. Global and within‐trial human behavior is predicted with 88% of accuracy in nominal conditions. When the object's center of mass is moved, the accuracy is maintained up to 83%. Finally, convergence properties of proposed algorithms are analytically discussed, and their stability and robustness against measurement noise are evaluated in simulation.
{"title":"Modeling Previous Trial Effect in Human Manipulation through Iterative Learning Control","authors":"Lorenzo Cenceschi, C. D. Santina, Giuseppe Averta, M. Garabini, Qiushi Fu, M. Santello, M. Bianchi, A. Bicchi","doi":"10.1002/aisy.201900074","DOIUrl":"https://doi.org/10.1002/aisy.201900074","url":null,"abstract":"In the execution of repetitive tasks, humans can capitalize on experience to improve their motor performance. Prominent examples of this ability can be recognized in our capacity of grasping and manipulating in uncertain conditions. With the aim of providing a mathematical description for such behavior, experiments are considered where participants are required to lift an object with an unexpected mass distribution. By repeating multiple times the same lifting action, participants can learn the correct motor command for task accomplishment. Three models are proposed that combine reactive terms and a learned anticipatory action to explain experimental data. The models feature intratrial and intertrial memory, and the effect of slowly and fast adaptive sensory receptors. The architectures’ effectiveness in explaining experimental data is compared with a general‐purpose state of the art model. The proposed algorithms conspicuously outperform the state of the art in all the considered validation routines. Global and within‐trial human behavior is predicted with 88% of accuracy in nominal conditions. When the object's center of mass is moved, the accuracy is maintained up to 83%. Finally, convergence properties of proposed algorithms are analytically discussed, and their stability and robustness against measurement noise are evaluated in simulation.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90208478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Kan‐Tor, Nir Zabari, Ity Erlich, Adi Szeskin, Tamar Amitai, D. Richter, Y. Or, Z. Shoham, A. Hurwitz, I. Har-Vardi, M. Gavish, A. Ben-Meir, A. Buxboim
In in vitro fertilization (IVF) treatments, early identification of embryos with high implantation potential is required for shortening time to pregnancy while avoiding clinical complications to the newborn and the mother caused by multiple pregnancies. Current classification tools are based on morphological and morphokinetic parameters that are manually annotated using time‐lapse video files. However, manual annotation introduces interobserver and intraobserver variability and provides a discrete representation of preimplantation development while ignoring dynamic features that are associated with embryo quality. A fully automated and standardized classifiers are developed by training deep neural networks directly on the raw video files of >6200 blastulation‐labeled and >5500 implantation‐labeled embryos. Prediction of embryo implantation is more accurate than the current state‐of‐the‐art morphokientic classifier. Embryo classification improves with video length where the most predictive images show only partial association with morphological features. Deep learning substitute to human evaluation of embryo developmental competence thus contributes to implementing single embryo transfer methodology.
{"title":"Automated Evaluation of Human Embryo Blastulation and Implantation Potential using Deep‐Learning","authors":"Y. Kan‐Tor, Nir Zabari, Ity Erlich, Adi Szeskin, Tamar Amitai, D. Richter, Y. Or, Z. Shoham, A. Hurwitz, I. Har-Vardi, M. Gavish, A. Ben-Meir, A. Buxboim","doi":"10.1002/aisy.202000080","DOIUrl":"https://doi.org/10.1002/aisy.202000080","url":null,"abstract":"In in vitro fertilization (IVF) treatments, early identification of embryos with high implantation potential is required for shortening time to pregnancy while avoiding clinical complications to the newborn and the mother caused by multiple pregnancies. Current classification tools are based on morphological and morphokinetic parameters that are manually annotated using time‐lapse video files. However, manual annotation introduces interobserver and intraobserver variability and provides a discrete representation of preimplantation development while ignoring dynamic features that are associated with embryo quality. A fully automated and standardized classifiers are developed by training deep neural networks directly on the raw video files of >6200 blastulation‐labeled and >5500 implantation‐labeled embryos. Prediction of embryo implantation is more accurate than the current state‐of‐the‐art morphokientic classifier. Embryo classification improves with video length where the most predictive images show only partial association with morphological features. Deep learning substitute to human evaluation of embryo developmental competence thus contributes to implementing single embryo transfer methodology.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83679544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Bachmann, J. Giltinan, Agnese Codutti, S. Klumpp, M. Sitti, D. Faivre
Magnetic microswimmers are promising devices for biomedical and environmental applications. Bacterium flagella‐inspired magnetic microhelices with perpendicular magnetizations are currently considered standard for propulsion at low Reynolds numbers because of their well‐understood dynamics and controllability. Deviations from this system have recently emerged: randomly shaped magnetic micropropellers with nonlinear swimming behaviors show promise in sensing, sorting, and directional control. The current progresses in 3D micro/nanoprinting allow the production of arbitrary 3D microstructures, increasing the accessible deterministic design space for complex micropropeller morphologies. Taking advantage of this, a shape is systematically reproduced that was formerly identified while screening randomly shaped propellers. Its nonlinear behavior, which is called frequency‐induced reversal of swimming direction (FIRSD), allows a propeller to swim in opposing directions by only changing the applied rotating field's frequency. However, the identically shaped swimmers do not only display the abovementioned swimming property but also exhibit a variety of swimming behaviors that are shown to arise from differences in their magnetic moment orientations. This underlines not only the role of shape in microswimmer behavior but also the importance of determining magnetic properties of future micropropellers that act as intelligent devices, as single‐shape templates with different magnetic moments can be utilized for different operation modes.
{"title":"Selection for Function: From Chemically Synthesized Prototypes to 3D‐Printed Microdevices","authors":"F. Bachmann, J. Giltinan, Agnese Codutti, S. Klumpp, M. Sitti, D. Faivre","doi":"10.1002/aisy.202000078","DOIUrl":"https://doi.org/10.1002/aisy.202000078","url":null,"abstract":"Magnetic microswimmers are promising devices for biomedical and environmental applications. Bacterium flagella‐inspired magnetic microhelices with perpendicular magnetizations are currently considered standard for propulsion at low Reynolds numbers because of their well‐understood dynamics and controllability. Deviations from this system have recently emerged: randomly shaped magnetic micropropellers with nonlinear swimming behaviors show promise in sensing, sorting, and directional control. The current progresses in 3D micro/nanoprinting allow the production of arbitrary 3D microstructures, increasing the accessible deterministic design space for complex micropropeller morphologies. Taking advantage of this, a shape is systematically reproduced that was formerly identified while screening randomly shaped propellers. Its nonlinear behavior, which is called frequency‐induced reversal of swimming direction (FIRSD), allows a propeller to swim in opposing directions by only changing the applied rotating field's frequency. However, the identically shaped swimmers do not only display the abovementioned swimming property but also exhibit a variety of swimming behaviors that are shown to arise from differences in their magnetic moment orientations. This underlines not only the role of shape in microswimmer behavior but also the importance of determining magnetic properties of future micropropellers that act as intelligent devices, as single‐shape templates with different magnetic moments can be utilized for different operation modes.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85803367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isabella De Bellis, Bin Ni, D. Martella, C. Parmeggiani, P. Keller, D. Wiersma, Min‐Hui Li, S. Nocentini
Nature provides well‐engineered and evolutionary optimized examples of brilliant structural colors in animals and plants. Morpho butterflies are among the well‐known species possessing iridescent bright blue coloration due to multiple optical effects generated by the complex structuration of the wing scales. Such surprising solution can be replicated to fabricate efficient devices. Maybe even more interesting, novel approaches can be developed to combine wings with synthetic smart materials to achieve complex structures responsive to external stimuli. This study demonstrates the proof of concept of an innovative biotic–abiotic hybrid smart structure made by the integration of a butterfly wing with thermoresponsive liquid crystalline elastomers, and their capability to actuate the mechanical action of the wing, thus controlling its spectral response. Exploiting two fabrication strategies, it is demonstrated how different mechanisms of color tuning can be achieved by temperature control. In addition, due to the thermally induced mechanical deformation of the elastomer and superhydrophobic properties of the wing, a potential self‐cleaning behavior of the bilayer material is demonstrated.
{"title":"Color Modulation in Morpho Butterfly Wings Using Liquid Crystalline Elastomers","authors":"Isabella De Bellis, Bin Ni, D. Martella, C. Parmeggiani, P. Keller, D. Wiersma, Min‐Hui Li, S. Nocentini","doi":"10.1002/aisy.202000035","DOIUrl":"https://doi.org/10.1002/aisy.202000035","url":null,"abstract":"Nature provides well‐engineered and evolutionary optimized examples of brilliant structural colors in animals and plants. Morpho butterflies are among the well‐known species possessing iridescent bright blue coloration due to multiple optical effects generated by the complex structuration of the wing scales. Such surprising solution can be replicated to fabricate efficient devices. Maybe even more interesting, novel approaches can be developed to combine wings with synthetic smart materials to achieve complex structures responsive to external stimuli. This study demonstrates the proof of concept of an innovative biotic–abiotic hybrid smart structure made by the integration of a butterfly wing with thermoresponsive liquid crystalline elastomers, and their capability to actuate the mechanical action of the wing, thus controlling its spectral response. Exploiting two fabrication strategies, it is demonstrated how different mechanisms of color tuning can be achieved by temperature control. In addition, due to the thermally induced mechanical deformation of the elastomer and superhydrophobic properties of the wing, a potential self‐cleaning behavior of the bilayer material is demonstrated.","PeriodicalId":7187,"journal":{"name":"Advanced Intelligent Systems","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89732996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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