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In recent years, many researchers have aimed to construct robotic soft grippers that can handle fragile or unusually shaped objects without causing damage. This study proposes a smart textile-composite actuator and its application to a soft robotic gripper. An active fiber and an inactive fiber are combined together using knitting techniques to manufacture a textile actuator. The active fiber is a shape memory alloy (SMA) that is wire-wrapped with conventional fibers, and the inactive fiber is a knitting yarn. A knitted textile structure is flexible, with an excellent structure retention ability and high compliance, which is suitable for developing soft grippers. A driving source of the actuator is the SMA wire, which deforms under heating due to the shape memory effect. Through experiments, the course-to-wale ratio, the number of bundling SMA wires, and the driving current value needed to achieve the maximum deformation of the actuator were investigated. Three actuators were stitched together to make up each finger of the gripper, and layer placement research was completed to find the fingers’ suitable bending angle for object grasping. Finally, the gripping performance was evaluated through a test of grasping various object shapes, which demonstrated that the gripper could successfully lift flat/spherical/uniquely shaped objects.

The goal of sustainable production of biochemicals and biofuels has driven the engineering of microbial cell as factories that convert low-value substrates to high-value products. Xylose is the second most abundant sugar substrate in lignocellulosic hydrolysates. We analyzed the mechanisms of xylose metabolism using genome sequencing data of 492 industrially relevant bacterial species in the mini-review. The analysis revealed the xylose isomerase and Weimberg pathways as the major routes across diverse routes of bacterial xylose metabolism. In addition, we discuss recent developments in metabolic engineering of xylose metabolism in industrial microorganisms. Genome-scale analyses have revealed xylose pathway-specific flux landscapes. Overall, a comprehensive understanding of bacterial xylose metabolism could be useful for the feasible development of microbial cell factories.

Soft actuators that execute diverse motions have recently been proposed to improve the usability of soft robots. Nature-inspired actuators, in particular, are emerging as a means of accomplishing efficient motions based on the flexibility of natural creatures. In this research, we present an actuator capable of executing multi-degree-of-freedom motions that mimics the movement of an elephant’s trunk. Shape memory alloys (SMAs) that actively react to external stimuli were integrated into actuators constructed of soft polymers to imitate the flexible body and muscles of an elephant’s trunk. The amount of electrical current provided to each SMA was adjusted for each channel to achieve the curving motion of the elephant’s trunk, and the deformation characteristics were observed by varying the quantity of current supplied to each SMA. It was feasible to stably lift and lower a cup filled with water by using the operation of wrapping and lifting objects, as well as effectively performing the lifting task of surrounding household items of varying weights and forms. The designed actuator is a soft gripper that incorporates a flexible polymer and an SMA to imitate the flexible and efficient gripping action of an elephant trunk, and its fundamental technology is expected to be used as a safety-enhancing gripper that requires environmental adaptation.

As the use of drones grows, so too does the demand for physical protection against drone damage resulting from collisions and falls. In addition, as the flight environment becomes more complicated, a shock absorption system is required, in which the protective structure can be deformed based on the circumstances. Here, we present an origami- and kirigami-based structure that provides protection from various directions. This research adds a deformation capacity to existing fixed-shape guards; by using shape memory alloys, the diameter and height of the protective structure are controlled. We present three protective modes (1: large diameter/low height; 2: small diameter/large height; and 3: lotus shaped) that mitigate drone falls and side collisions. From the result of the drop impact test, mode 2 showed a 78.2% reduction in the maximum impact force at side impact. We incorporated kirigami patterns into the origami structures in order to investigate the aerodynamic effects of the hollow patterns. Airflow experiments yielded a macro understanding of flow-through behaviors on each kirigami pattern. In the wind speed experiment, the change in airflow velocity induced by the penetration of the kirigami pattern was measured, and in the force measurement experiment, the air force applied to the structure was determined.

Shape memory alloys (SMAs) are widely used as soft actuators due to their shape memory effect, variable stiffness, and simple actuation via Joule heating. To achieve larger and more diverse deformations, SMA wires can be integrated as fibers into textile structures, enabling the fabrication of textile actuators using conventional textile manufacturing methods. These actuators provide high compliance and ergonomic conformability, making them more human-friendly than other types of soft actuators. Nevertheless, few studies have examined their modal behavior, limiting the application of SMA-based textile actuators. This study focuses on knitted SMA-based textile actuators and investigates nine morphing patterns—six plane-based and three band-based—designed with knitting codes. The actuators exhibited deformations that matched the predicted shapes. In addition, the plane-based patterns were analyzed to examine the relationship between loop transition boundaries and deformation axes in controlling bending angles. Demonstrations of knitted morphing flowers highlighted the scalability of the designs. Furthermore, quantitative evaluation of actuation forces in horizontal and vertical directions confirmed that actuator performance can be tuned through structural design.

Textiles composed of fibers can have their mechanical properties adjusted by changing the arrangement of the fibers, such as strength and flexibility. Particularly, in the case of smart textiles incorporating active materials, various deformations could be created based on fiber patterns that determine the directivity of active materials. In this study, we design a smart fiber-based textile actuator with a chain structure and evaluate its actuation characteristics. Smart fiber composed of shape memory alloy (SMA) generates deformation when the electric current is applied, causing the phase transformation of SMA. We fabricated the smart chain column and evaluated its actuating mechanism based on the size of the chain and the number of rows. In addition, a crochet textile actuator was designed using interlooping smart chains and developed into a soft gripper that can grab objects. With experimental verifications, this study provides an investigation of the relationship between the chain actuator’s deformation, actuating force, actuator temperature, and strain. The results of this study are expected to be relevant to textile applications, wearable devices, and other technical fields that require coordination with the human body. Additionally, it is expected that it can be utilized to configure a system capable of flexible operation by combining rigid elements such as batteries and sensors with textiles.

A Dielectric Elastomer Actuator (DEA) consists of electrodes with a dielectric layer between them. By controlling the design of the electrodes, voltage, and frequency, the operating range and speed of the DEA can be adjusted. These DEAs find applications in biomimetic robots, artificial muscles, and similar fields. When voltage is applied to the DEA, the dielectric layer undergoes compression and expansion due to electrostatic forces, which can lead to electrical breakdown. This phenomenon is closely related to the performance and lifespan of the DEA. To enhance stability and improve dielectric properties, a DEA Reservoir layer is introduced. Here, stability refers to the ability of the DEA to perform its functions even as the applied voltage increases. The Reservoir layer delays electrical breakdown and enhances stability due to its enhanced thickness. The proposed DEA in this paper is composed of a Reservoir layer and electrode layer. The Reservoir layer is placed between the electrode layers and is independently configured, not subjected to applied voltage like the electrode layers. The performance of the DEA was evaluated by varying the number of polymer layers in the Reservoir and electrode designs. Introducing the Reservoir layer improved the dielectric properties of the DEA and delayed electrical breakdown. Increasing the dielectric constant through the DEA Reservoir can enhance output characteristics in response to electrical signals. This approach can be utilized in various applications in wearable devices, artificial muscles, and other fields.

Microbial production of 2,3-butanediol (2,3-BDO) has been attracting increasing interest because of its high value and various industrial applications. In this study, high production of 2,3-BDO using a previously isolated bacterium Klebsiella oxytoca M1 was carried out by optimizing fermentation conditions and overexpressing acetoin reductase (AR). Supplying complex nitrogen sources and using NaOH as a neutralizing agent were found to enhance specific production and yield of 2,3-BDO. In fed-batch fermentations, 2,3-BDO production increased with the agitation speed (109.6 g/L at 300 rpm vs. 118.5 g/L at 400 rpm) along with significantly reduced formation of by-product, but the yield at 400 rpm was lower than that at 300 rpm (0.40 g/g vs. 0.34 g/g) due to acetoin accumulation at 400 rpm. Because AR catalyzing both acetoin reduction and 2,3-BDO oxidation in K. oxytoca M1 revealed more than 8-fold higher reduction activity than oxidation activity, the engineered K. oxytoca M1 overexpressing the budC encoding AR was used in fed-batch fermentation. Finally, acetoin accumulation was significantly reduced by 43% and enhancement of 2,3-BDO concentration (142.5 g/L), yield (0.42 g/g) and productivity (1.47 g/L/h) was achieved compared to performance with the parent strain. This is by far the highest titer of 2,3-BDO achieved by K. oxytoca strains. This notable result could be obtained by finding favorable fermentation conditions for 2,3-BDO production as well as by utilizing the distinct characteristic of AR in K. oxytoca M1 revealing the nature of reductase.

Background Hyaluronic acid (HA) is widely used in pharmaceuticals, medicine, and cosmetics. Sustainable production has shifted to microbial fermentation using engineered GRAS strains. Diverse carbon sources and CO 2 conversion via engineered microorganisms enhance HA production. Herein we applied advances in CRISPR technologies and tools to optimize metabolic pathway by redirecting carbon portioning in cyanobacterium Synechoccous elongatus PCC 7942, demonstrating enhanced HA production. Results S. elongatus PCC 7942 lacking hyaluronan synthase (HAS) required pathway engineering for HA production. By expressing heterologous Class I HAS, a modular gene expression system was employed, incorporating hasB and hasC for the HA-GlcA module and glmU , glmM , and glmS for the GlcNAc module. This approach resulted in construction of four engineered cyanobacterial strains. Optimizing metabolic pathway involving the HA-GlcA and GlcNAc modules led to SeHA220 (wild-type with HA-GlcA and GlcNAc modules) producing 2.4 ± 0.85 mg/L HA at 21 d, a 27.5-fold increase compared to the control. Targeting F6P and G6P metabolic nodes via CRISPR interference to repress zwf and pfk genes further improved production, with SeHA226 (SeHA220 with a gene repression module) achieving 5.0 ± 0.3 mg/L HA from CO 2 at 15 d. Notably, SeHA226 produced photosynthetic HA with a molecular weight (Mw) of 4.2 MDa, comparable to native producers, emphasizing the importance of precursor balance and growth conditions. Conclusions This study engineered cyanobacteria for efficient HA biosynthesis using modular gene expression and CRISPR-interference systems. Optimizing heterologous metabolic pathway was key to achieving high-molecular-weight photosynthetic HA production from CO 2 . The findings provide insights into tunable HA production, with future efforts aimed at scaling up photosynthetic HA production for larger-scale applications.

Every year, almost 4 million patients received medical care for knee osteoarthritis. Osteoarthritis involves progressive deterioration or degenerative changes in the cartilage, leading to inflammation and pain as the bones and ligaments are affected. To enhance treatment and surgical outcomes, various studies analyzing the biomechanics of the human skeletal system by fabricating simulated bones, particularly those reflecting the characteristics of patients with knee osteoarthritis, are underway. In this study, we fabricated replicated bones that mirror the bone characteristics of patients with knee osteoarthritis and developed a skeletal model that mimics the actual movement of the knee. To create patient-specific replicated bones, models were extracted from computerized tomography (CT) scans of knee osteoarthritis patients. Utilizing 3D printing technology, we replicated the femur and tibia, which bear the weight of the body and support movement, and manufactured cartilage capable of absorbing and dispersing the impact of knee joint loads using flexible polymers. Furthermore, to implement knee movement in the skeletal model, we developed artificial muscles based on shape memory alloys (SMAs) and used them to mimic the rolling, sliding, and spinning motions of knee flexion. The knee movement was investigated by changing the SMA spring’s position, the number of coils, and the applied voltage. Additionally, we developed a knee-joint-mimicking system to analyze the movement of the femur. The proposed artificial-skeletal-model-based knee-joint-mimicking system appears to be applicable for analyzing skeletal models of knee patients and developing surgical simulation equipment for artificial joint replacement surgery.