Magnetic field-driven particle assembly and jamming for bistable memory and response plasticity

Opto-Thermal-Tension Mediated Precision Large-Scale Particle Manipulation and Flexible Patterning

Large-scale particle manipulation with single-particle precision and further flexible patterning into functional structures is of huge potentials in many fields including bio-optoelectronic sensing, colloidal lithography, and wearable devices. However, it is very challenging for the precision manipulation and flexible patterning of particles on complicated curved and functional substrates. In this work, opto-thermal-tension (OTT) mediated precision large-scale particle manipulation and flexible patterning based on soap film are reported. Flexible manipulation and subsequent patterning of particles with single-particle resolution is realized by optothermal regulated surface tension on soap films. Reconfigurable patterning of particle structures with different shapes as well as large-scale ordered structures (up to 2000 particles) with particle sizes spanning two orders of magnitude (0.5-20 µm) is realized using this OTT mediation method. Importantly, due to the high flexibility of soap films, the patterned large-scale particle structures can be non-destructively transferred to curved and rough substrates, including rough iron pipe surface, leaf and skin surface. This OTT mediated method provides a new method for precision large-scale particle manipulation and flexible patterning with high versatility on complicated functional substrates, with great potentials for optoelectronic and biophotonic sensing and wearable device design on different curved and rough functional substrates.

Randomizing the growth of silica nanofibers for whiteness

In colloids, the shape influences the function. In silica, straight nanorods have already been synthesized from water-in-oil emulsions. By contrast, curly silica nanofibers have been less reported because the underlying growth mechanism remains unexplored, hindering further morphology control for applications. Herein, we describe the synthetic protocol for silica nanofibers with a tunable curliness based on the control of the water-in-oil emulsion droplets. Systematically decreasing the droplet size and increasing their contact angle, the Brownian motion of the droplets intensifies during the silica growth, thus increasing the random curliness of the nanofibers. This finding is supported by simplistic theoretical arguments and experimentally verified by varying the temperature to finely tune the curliness. Assembling these nanofibers toward porous disordered films enhances multiple scattering in the visible range, resulting in increased whiteness in contrast to films constructed by spherical and rod-like building units, which can be useful for, e.g., coatings and pigments.

Trainable bioinspired magnetic sensitivity adaptation using ferromagnetic colloidal assemblies

Nature has already suggested bioinspired functions. Beyond them, adaptive and trainable functions could be the inspiration for novel responsive soft matter beyond the state-of-the-art classic static bioinspired, stimulus-responsive, and shape-memory materials. Here, we describe magnetic assembly/disassembly of electrically conducting soft ferromagnetic nickel colloidal particles into surface topographical pillars for bistable electrical trainable memories. They allow magnetic sensing with adaptable and rescalable sensitivity ranges, enabled by bistable memories and kinetic concepts inspired by biological sensory adaptations. Based on the soft ferromagnetism of the nanogranular composition and the resulting rough particle surfaces prepared via a solvothermal synthesis, triggerable structural memory is achieved by the magnetic field-driven particle assembly and disassembly, promoted by interparticle jamming. Electrical conversion from current to frequency for electrical spikes facilitates rescalable and trainable frequency-based sensitivity on magnetic fields. This work suggests an avenue for designing trainable and adaptable life-inspired materials, for example, for soft robotics and interactive autonomous devices.

Magnetically controlled assembly: a new approach to organic integrated photonics

Hierarchical self-assembly of organic molecules or assemblies is of great importance for organic photonics to move from fundamental research to integrated and practical applications. Magnetic fields with the advantages of high controllability, non-contact manipulation, and instantaneous response have emerged as an elegant way to prepare organic hierarchical nanostructures. In this perspective, we outline the development history of organic photonic materials and highlight the importance of organic hierarchical nanostructures for a wide range of applications, including microlasers, optical displays, information encoding, sensing, and beyond. Then, we will discuss recent advances in magnetically controlled assembly for creating organic hierarchical nanostructures, with a particular focus on their potential for enabling the development of integrated photonic devices with unprecedented functionality and performance. Finally, we present several perspectives on the further development of magnetically controlled assembly strategies from the perspective of performance optimization and functional design of organic integrated photonics.

Thermally trainable dual network hydrogels

Inspired by biological systems, trainable responsive materials have received burgeoning research interests for future adaptive and intelligent material systems. However, the trainable materials to date typically cannot perform active work, and the training allows only one direction of functionality change. Here, we demonstrate thermally trainable hydrogel systems consisting of two thermoresponsive polymers, where the volumetric response of the system upon phase transitions enhances or decreases through a training process above certain threshold temperature. Positive or negative training of the thermally induced deformations can be achieved, depending on the network design. Importantly, softening, stiffening, or toughening of the hydrogel can be achieved by the training process. We demonstrate trainable hydrogel actuators capable of performing increased active work or implementing an initially impossible task. The reported dual network hydrogels provide a new training strategy that can be leveraged for bio-inspired soft systems such as adaptive artificial muscles or soft robotics.

pH-feedback systems to program autonomous self-assembly and material lifecycles

pH-responsive systems have gained importance for the development of smart materials and for biomedical applications because they can switch between different states by simple acid/base triggers. However, such equilibrium systems lack the autonomous behaviour that is so ubiquitous in living systems that self-regulate out of equilibrium. As a contribution to the emerging field of autonomous chemical systems, we have developed pH-feedback systems (pH-FS) based on the coupling of acid- and base-producing steps in chemical reaction networks. The resulting autonomous nonlinear pH curves can be coupled with a variety of pH-sensitive building blocks to program the lifecycles of the associated transient state at the level of self-assemblies and material systems. In this article, we discuss the different generations of such pH-feedback systems, the principles of their coupling to self-assemblies with lifecycles and highlight emerging concepts for the design of autonomous functional materials. The specificity, robustness, and flexible operation of such pH-FS can also be used to realize chemo-structural and chemo-mechanical feedbacks that extend the behaviour of such materials systems toward complex and functional life-like systems.