3D printing assisted development of bioinspired structure and device for advanced engineering

Smart materials with bio-inspired structure and stimuli responsive features can sense the external and internal condition changes, such as temperature, light intensity, pH or ion concentration. Those unique functions have been widely utilized in cutting edge engineering applications, such as flexible sensors, soft robotics and tissue engineering. Meanwhile, conventional manufacturing methods such as moulding, and lithography-based microfabrication still represent the mainstream force in scale up manufacturing. Considerable limitations for these technologies, such as on demand rapid prototyping, the high cost and low-volume production, remain to be overcome. In this PhD project, I explored the advanced manufacturing in facilitating the complex structure, with higher controllability, lower prototyping cost and extended applications (flexible sensors, soft robots, biomedical devices, etc.). The key practice is to utilize the high resolution 3D printing technology to create dedicated bio inspired structures based on functional materials. Combined with advanced micro/nano engineering, we have achieved a variety of techniques/prototypes for future applications, such as optical control, micro-fluidic and bio-medical systems, etc

Interfacial Interaction Enhanced Rheological Behavior in PAM/CTAC/Salt Aqueous Solution—A Coarse-Grained Molecular Dynamics Study

Interfacial interactions within a multi-phase polymer solution play critical roles in processing control and mass transportation in chemical engineering. However, the understandings of these roles remain unexplored due to the complexity of the system. In this study, we used an efficient analytical method—a nonequilibrium molecular dynamics (NEMD) simulation—to unveil the molecular interactions and rheology of a multiphase solution containing cetyltrimethyl ammonium chloride (CTAC), polyacrylamide (PAM), and sodium salicylate (NaSal). The associated macroscopic rheological characteristics and shear viscosity of the polymer/surfactant solution were investigated, where the computational results agreed well with the experimental data. The relation between the characteristic time and shear rate was consistent with the power law. By simulating the shear viscosity of the polymer/surfactant solution, we found that the phase transition of micelles within the mixture led to a non-monotonic increase in the viscosity of the mixed solution with the increase in concentration of CTAC or PAM. We expect this optimized molecular dynamic approach to advance the current understanding on chemical–physical interactions within polymer/surfactant mixtures at the molecular level and enable emerging engineering solutions

Advanced 3D morphing transducers by smart hydrogel patterning

This paper demonstrates a unique way of creating heterogeneous layered structures of soft functional materials for advanced transducer applications. Hydrogel droplets with different composites were patterned by a “two-parallel plate” configuration used in microfluidics applications. Resulted heterogeneous layered structures of hydrogel were created, generating reconfigurable 3D (3-dimensional) deformation responding to discrete levels of stimulation inputs

Controlled Cooperative Wetting Enabled Heterogeneous Structured 3D Morphing Transducers

A unique microfluidics approach for functional hydrogel patterning with multilayered heterogeneous structures is presented. Prepolymer solution droplets with differentiated sodium acrylate concentrations are dispensed/printed in a wetting‐controlled “two‐parallel plate” (TPP, like a Hele‐Shaw Cell) system. The gelation within the system enables hydrogel bilayer structures with reconfigurable 3D deformations driven by in‐plane and through‐thickness heterogeneity under stimuli‐responsive mask‐less swelling/deswelling. The cooperation between swelling mismatch of functional groups results in a higher complexity of 3D reconfiguration in responding to discrete levels of stimulation inputs. This facile patterning technology with an in‐built ionic hierarchy can be scaled up/down with advanced transducing functionalities in various fields

A tunable morphing polyelectrolyte system for smart ocular applications

For the first time, a focal-length tunable intra-ocular lens (IOL) device has been realized by a standard-shaped, homogeneous “one material” system. Different to existing technologies, this poly(N-isopropylacrylamide) gel (PNIPAM) based polyelectrolyte system doesn’t require any additional materials (e.g. metal electrodes, movable mechanical structures) to achieve a controllable lens shape transformation for the focal-length shifting actuation. The designed morphological deformation mechanism employs ionic-strength responsive mechanical buckling via controlled swelling of PNIPAM in phosphate buffered saline (PBS) with similar concentration to human eye liquid. This unique approach will unlock great potential in a wide range of smart ocular applications

Understanding complex dynamics of interfacial reconstruction in polyampholyte hydrogels undergoing mechano-chemo-electrotaxis coupling

Polyampholyte (PA) hydrogels have attracted significant attention for their superior mechanical strength and toughness compared with other conventional hydrogels. In this study, we present a novel thermodynamic approach to understanding the mechano-chemo-electrotaxis coupling and interfacial dynamics in PA hydrogels. Flory–Huggins theory, carried out through an interfacial free-energy model, is the foundation for the quantitative study of the mechanically constitutive relationship of the PA gels. The proposed free-energy model is further extended to describe the mechano-chemo-electrotaxis switching and interfacial dynamics by co-relating the Williams–Landel–Ferry equation and scaling laws. It was concluded that the interfacial bonding strength is the key factor influencing the mechanical strength and reconstruction reversibility of the PA macromolecular gel system. The resulting analytical outcomes showed good agreement with the reported experimental data. We opine that the proposed model will guide the future application of PA hydrogels

Spatially Engraving Morphological Structure on Polymeric Surface by Ion Beam Milling

Polymer surface patterning and modification at the micro/nano scale has been discovered with great impact in applications such as microfluidics and biomedical technologies. We propose a highly efficient fabricating strategy, to achieve a functional polymer surface, which has control over the surface roughness. The key development in this fabrication method is the polymer positive diffusion effect (PDE) for an ion-bombarded polymeric hybrid surface through focused ion beam (FIB) technology. The PDE is theoretically explored by introducing a positive diffusion term into the classic theory. The conductivity-induced PDE constant is discussed as functions of substrates conductivity, ion energy and flux. The theoretical results agree well with the experiential results on the conductivity-induced PDE, and thus yield good control over roughness and patterning milling depth on the fabricated surface. Moreover, we demonstrate a controllable surface wettability in hydrophobic and superhydrophobic surfaces (contact angles (CA) range from 108.3° to 150.8°) with different CA hysteresis values ranging from 31.4° to 8.3°

Spatially and Reversibly Actuating Soft Gel Structure by Harnessing Multimode Elastic Instabilities

Autonomous shape transformation is key in developing high-performance soft robotics technology; the search for pronounced actuation mechanisms is an ongoing mission. Here, we present the programmable shape morphing of a three-dimensional (3D) curved gel structure by harnessing multimode mechanical instabilities during free swelling. First of all, the coupling of buckling and creasing occurs at the dedicated region of the gel structure, which is attributed to the edge and surface instabilities resulted from structure-defined spatial nonuniformity of swelling. The subsequent developments of post-buckling morphologies and crease patterns collaboratively drive the structural transformation of the gel part from the “open” state to the “closed” state, thus realizing the function of gripping. By utilizing the multi-stimuli-responsive nature of the hydrogel, we recover the swollen gel structure to its initial state, enabling reproducible and cyclic shape evolution. The described soft gel structure capable of shape transformation brings a variety of advantages, such as easy to fabricate, large strain transformation, efficient actuation, and high strength-to-weight ratio, and is anticipated to provide guidance for future applications in soft robotics, flexible electronics, offshore engineering, and healthcare products

Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation.

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins. Several diverse pilot projects were launched to provide key insights into important features of this emerging landscape and to determine the requirements for the development and adoption of cancer patient digital twins. Projects included exploring approaches to using a large cohort of digital twins to perform deep phenotyping and plan treatments at the individual level, prototyping self-learning digital twin platforms, using adaptive digital twin approaches to monitor treatment response and resistance, developing methods to integrate and fuse data and observations across multiple scales, and personalizing treatment based on cancer type. Collectively these efforts have yielded increased insights into the opportunities and challenges facing cancer patient digital twin approaches and helped define a path forward. Given the rapidly growing interest in patient digital twins, this manuscript provides a valuable early progress report of several CPDT pilot projects commenced in common, their overall aims, early progress, lessons learned and future directions that will increasingly involve the broader research community