Fiberbots: Robotic fibers for high-precision minimally invasive surgery.

Precise manipulation of flexible surgical tools is crucial in minimally invasive surgical procedures, necessitating a miniature and flexible robotic probe that can precisely direct the surgical instruments. In this work, we developed a polymer-based robotic fiber with a thermal actuation mechanism by local heating along the sides of a single fiber. The fiber robot was fabricated by highly scalable fiber drawing technology using common low-cost materials. This low-profile (below 2 millimeters in diameter) robotic fiber exhibits remarkable motion precision (below 50 micrometers) and repeatability. We developed control algorithms coupling the robot with endoscopic instruments, demonstrating high-resolution in situ molecular and morphological tissue mapping. We assess its practicality and safety during in vivo laparoscopic surgery on a porcine model. High-precision motion of the fiber robot delivered endoscopically facilitates the effective use of cellular-level intraoperative tissue identification and ablation technologies, potentially enabling precise removal of cancer in challenging surgical sites.

Hole Depth Prediction in a Femtosecond Laser Drilling Process Using Deep Learning.

In high-aspect ratio laser drilling, many laser and optical parameters can be controlled, including the high-laser beam fluence and number of drilling process cycles. Measurement of the drilled hole depth is occasionally difficult or time consuming, especially during machining processes. This study aimed to estimate the drilled hole depth in high-aspect ratio laser drilling by using captured two-dimensional (2D) hole images. The measuring conditions included light brightness, light exposure time, and gamma value. In this study, a method for predicting the depth of a machined hole by using a deep learning methodology was devised. Adjusting the laser power and the number of processing cycles for blind hole generation and image analysis yielded optimal conditions. Furthermore, to forecast the form of the machined hole, we identified the best circumstances based on changes in the exposure duration and gamma value of the microscope, which is a 2D image measurement instrument. After extracting the data frame by detecting the contrast data of the hole by using an interferometer, the hole depth was predicted using a deep neural network with a precision of within 5 µm for a hole within 100 µm.

Shape Memory Alloy (SMA) Actuators: The Role of Material, Form, and Scaling Effects.

Shape memory alloys (SMAs) are smart materials that are widely used to create intelligent devices because of their high energy density, actuation strain, and biocompatibility characteristics. Given their unique properties, SMAs are found to have significant potential for implementation in many emerging applications in mobile robots, robotic hands, wearable devices, aerospace/automotive components, and biomedical devices. Here, the state-of-the-art of thermal and magnetic SMA actuators in terms of their constituent materials, form, and scaling effects are summarized, including their surface treatments and functionalities. The motion performance of various SMA architectures (wires, springs, smart soft composites, and knitted/woven actuators) is also analyzed. Based on the assessment, current challenges of SMAs that need to be addressed for their practical application are emphasized. Finally, how to advance SMAs by synergistically considering the effects of material, form, and scale is suggested.

Advanced medical micro-robotics for early diagnosis and therapeutic interventions.

Recent technological advances in micro-robotics have demonstrated their immense potential for biomedical applications. Emerging micro-robots have versatile sensing systems, flexible locomotion and dexterous manipulation capabilities that can significantly contribute to the healthcare system. Despite the appreciated and tangible benefits of medical micro-robotics, many challenges still remain. Here, we review the major challenges, current trends and significant achievements for developing versatile and intelligent micro-robotics with a focus on applications in early diagnosis and therapeutic interventions. We also consider some recent emerging micro-robotic technologies that employ synthetic biology to support a new generation of living micro-robots. We expect to inspire future development of micro-robots toward clinical translation by identifying the roadblocks that need to be overcome.

Shape Memory Alloy (SMA)-Based Microscale Actuators with 60% Deformation Rate and 1.6 kHz Actuation Speed.

Shape memory alloys (SMAs) are widely utilized as an actuation source in microscale devices, since they have a simple actuation mechanism and high-power density. However, they have limitations in terms of strain range and actuation speed. High-speed microscale SMA actuators are developed having diamond-shaped frame structures with a diameter of 25 µm. These structures allow for a large elongation range compared with bulk SMA materials, with the aid of spring-like behavior under tensile deformation. These actuators are validated in terms of their applicability as an artificial muscle in microscale by investigating their behavior under mechanical deformation and changes in thermal conditions. The shape memory effect is triggered by delivering thermal energy with a laser. The fast heating and cooling phenomenon caused by the scale effect allows high-speed actuation up to 1600 Hz. It is expected that the proposed actuators will contribute to the development of soft robots and biomedical devices.

Site-specific characterization of beetle horn shell with micromechanical bending test in focused ion beam system.

Biological materials are the result of years of evolution and possess a number of efficient features and structures. Researchers have investigated the possibility of designing biomedical structures that take advantage of these structural features. Insect shells, such as beetle shells, are among the most promising types of biological material for biomimetic development. However, due to their intricate geometries and small sizes, it is challenging to measure the mechanical properties of these microscale structures. In this study, we developed an in-situ testing platform for site-specific experiments in a focused ion beam (FIB) system. Multi-axis nano-manipulators and a micro-force sensor were utilized in the testing platform to allow better results in the sample preparation and data acquisition. The entire test protocol, consisting of locating sample, ion beam milling and micro-mechanical bending tests, can be carried out without sample transfer or reattachment. We used our newly devised test platform to evaluate the micromechanical properties and structural features of each separated layer of the beetle horn shell. The Young's modulus of both the exocuticle and endocuticle layers was measured. We carried out a bending test to characterize the layers mechanically. The exocuticle layer bent in a brick-like manner, while the endocuticle layer exhibited a crack blunting effect. STATEMENT OF SIGNIFICANCE: This paper proposed an in-situ manipulation/test method in focused ion beam for characterizing micromechanical properties of beetle horn shell. The challenge in precise and accurate fabrication for the samples with complex geometry was overcome by using nano-manipulators having multi-degree of freedom and a micro-gripper. With the aid of this specially designed test platform, bending tests were carried out on cantilever-shaped samples prepared by focused ion beam milling. Structural differences between exocuticle and endocuticle layers of beetle horn shell were explored and the results provided insight into the structural advantages of each biocomposite structure.

CAD/CAM for scalable nanomanufacturing: A network-based system for hybrid 3D printing.

Micro- and nano-structuring have been highlighted over several decades in both science and engineering fields. In addition to continuous efforts in fabrication techniques, investigations in scalable nanomanufacturing have been pursued to achieve reduced feature size, fewer constraints in terms of materials and dimensional complexity, as well as improved process throughput. In this study, based on recent micro-/nanoscale fabrication processes, characteristics and key requirements for computer-aided design and manufacturing (CAD/CAM) systems for scalable nanomanufacturing were investigated. Requirements include a process knowledge database, standardized processing, active communication, adaptive interpolation, a consistent coordinate system, and management of peripheral devices. For scalable nanomanufacturing, it is important to consider the flexibility and expandability of each process, because hybrid and bridging processes represent effective ways to expand process capabilities. As an example, we describe a novel CAD/CAM system for hybrid three-dimensional (3D) printing at the nanoscale. This novel hybrid process was developed by bridging aerodynamically focused nanoparticle printing, focused ion beam milling, micromachining, and spin-coating processes. The system developed can print a full 3D structure using various inorganic materials, with a minimum process scale of 50 nm. The most obvious difference versus CAD/CAM at 'conventional' scales is that our system was developed based on a network to promote communication between users and process operators. With the network-based system, it is also possible to narrow the gap among different processes/resources. We anticipate that this approach can contribute to the development of CAD/CAM for scalable nanomanufacturing and a wide range of hybrid processes.