Search for: All records

Abstract Extrusion 3D‐printing of biopolymers and natural fiber‐based biocomposites enables the fabrication of complex structures, ranging from implants' scaffolds to eco‐friendly structural materials. However, conventional polymer extrusion requires high energy consumption to reduce viscosity, and natural fiber reinforcement often requires harsh chemical treatments to improve adhesion. We address these challenges by introducing a sustainable framework to fabricate natural biocomposites usingChlorella vulgarismicroalgae as the matrix. Through bioink optimization and process refinement, we produced lightweight, multifunctional materials with hierarchical architectures. Infrared spectroscopy analysis reveals that hydrogen bonding plays a critical role in the binding and reinforcement ofChlorellacells by hydroxyethyl cellulose (HEC). As water content decreases, the hydrogen bonding network evolves from water‐mediated interactions to direct hydrogen bonds between HEC andChlorella, enhancing the mechanical properties. A controlled dehydration process maintains continuous microalgae morphology, preventing cracking. The resulting biocomposites exhibit a bending stiffness of 1.6 GPa and isotropic heat transfer and thermal conductivity of 0.10 W/mK at room temperature, demonstrating effective thermal insulation. These characteristics makeChlorellabiocomposites promising candidates for applications requiring both structural performance and thermal insulation, offering a sustainable alternative to conventional materials in response to growing environmental demands. 

We provide the first experimental realization of wavenumber bandgap (𝑞−gap) breathers. Experiments are obtained in the setting of a time-periodic phononic lattice where the model and experiment exhibit good qualitative agreement. 𝑞−gap breathers are localized in time and periodic in space, and are the counterparts to the classical breathers found in space-periodic systems. We derive an exact condition for modulation instability that leads to the opening of wavenumber bandgaps in which the 𝑞−gap breathers can arise. The 𝑞−gap breathers become more narrow and larger in amplitude as the wavenumber goes further into the bandgap. In the presence of damping, these structures acquire a nonzero, oscillating tail. The controllable temporal localization that 𝑞−gap breathers make possible has potential applications in the creation of phononic frequency combs, energy harvesting or acoustic signal processing. 

Bacteria can swim upstream in a narrow tube and pose a clinical threat of urinary tract infection to patients implanted with catheters. Coatings and structured surfaces have been proposed to repel bacteria, but no such approach thoroughly addresses the contamination problem in catheters. Here, on the basis of the physical mechanism of upstream swimming, we propose a novel geometric design, optimized by an artificial intelligence model. UsingEscherichia coli, we demonstrate the anti-infection mechanism in microfluidic experiments and evaluate the effectiveness of the design in three-dimensionally printed prototype catheters under clinical flow rates. Our catheter design shows that one to two orders of magnitude improved suppression of bacterial contamination at the upstream end, potentially prolonging the in-dwelling time for catheter use and reducing the overall risk of catheter-associated urinary tract infection. 

A strategy for developing irregular materials can lead to a wide range of functional properties. 

An object’s interior material properties, while invisible to the human eye, determine motion observed on its surface. We propose an approach that esti- mates heterogeneous material properties of an object directly from a monoc- ular video of its surface vibrations. Specifically, we estimate Young’s modulus and density throughout a 3D object with known geometry. Knowledge of how these values change across the object is useful for characterizing defects and simulating how the object will interact with different environments. Traditional non-destructive testing approaches, which generally estimate homogenized material properties or the presence of defects, are expensive and use specialized instruments. We propose an approach that leverages monocular video to (1) measure an object’s sub-pixel motion and decompose this motion into image-space modes, and (2) directly infer spatially-varying Young’s modulus and density values from the observed image-space modes. On both simulated and real videos, we demonstrate that our approach is able to image material properties simply by analyzing surface motion. In particular, our method allows us to identify unseen defects on a 2D drum head from real, high-speed video. 

A flexible biomimetic polymer with high thermal response is created for temperature mapping and long-wave IR sensing. 

Mechanical cloaks are materials engineered to manipulate the elastic response around objects to make them indistinguishable from their homogeneous surroundings. Typically, methods based on material-parameter transformations are used to design optical, thermal, and electric cloaks. However, they are not applicable in designing mechanical cloaks, since continuum-mechanics equations are not form invariant under general coordinate transformations. As a result, existing design methods for mechanical cloaks have so far been limited to a narrow selection of voids with simple shapes. To address this challenge, we present a systematic, data-driven design approach to create mechanical cloaks composed of aperiodic metamaterials using a large precomputed unit cell database. Our method is flexible to allow the design of cloaks with various boundary conditions, multiple loadings, different shapes and numbers of voids, and different homogeneous surroundings. It enables a concurrent optimization of both topology and properties distribution of the cloak. Compared to conventional fixed-shape solutions, this results in an overall better cloaking performance and offers unparalleled versatility. Experimental measurements on additively manufactured structures further confirm the validity of the proposed approach. Our research illustrates the benefits of data-driven approaches in quickly responding to new design scenarios and resolving the computational challenge associated with multiscale designs of functional structures. It could be generalized to accommodate other applications that require heterogeneous property distribution, such as soft robots and implants design.