Emerging themes in soft matter: responsive and active soft materials

Soft Matter ◽  
2010 ◽  
Vol 6 (4) ◽  
pp. 703 ◽  
Author(s):  
Anna C. Balazs ◽  
Julia M. Yeomans
Keyword(s):  
Soft Matter ◽  
Soft Materials ◽  
Emerging Themes

1. The science of softness

2020 ◽  
pp. 1-18
Author(s):  
Tom McLeish
Keyword(s):  
Scientific Community ◽  
Soft Matter ◽  
Soft Materials ◽  
Visionary Leadership ◽  
Slow Dynamics ◽  
Length Scales ◽  
New Science ◽  
Motion Structure

‘The science of softness’ provides a brief history and overview of soft matter science. The development of soft matter science was propelled by a combination of communication within the scientific community; intrinsic conceptual overlap and commonality; and visionary leadership from a small number of pioneering scientists. Chemistry proved as essential an ingredient to the new science of soft matter as ideas and techniques from physics. The characteristics of soft matter include motion; structure on intermediate length scales; slow dynamics; and universality. Microscopy is the most obvious and direct example of experimental tools applied across the gamut of soft materials.

scholarly journals A dynamically reprogrammable metasurface with self-evolving shape morphing

2021 ◽  
Author(s):  
Xiaoyue Ni ◽  
Yun Bai ◽  
Heling Wang ◽  
Yeguang Xue ◽  
Yuxin Pan ◽  
...  
Keyword(s):  
Flexible Electronics ◽  
Soft Matter ◽  
Response Times ◽  
Control Strategies ◽  
Soft Materials ◽  
Theoretical Models ◽  
Shape Morphing ◽  
Wide Range ◽  
Data Driven Approach ◽  
Actuation Scheme

Abstract Dynamic shape-morphing soft materials systems are ubiquitous in living organisms; they are also of rapidly increasing relevance to emerging technologies in soft machines1–4, flexible electronics5–7, and smart medicines8,9. Soft matter equipped with responsive components can switch between designed shapes or structures, but cannot support the types of dynamic morphing capabilities needed to reproduce natural, continuous processes of interest for many applications10–27. Challenges lie in the development of schemes to reprogram target shapes post fabrication, especially when complexities associated with the operating physics and disturbances from the environment can prohibit the use of deterministic theoretical models to guide inverse design and control strategies3,28–32. Here, we present a mechanical metasurface constructed from a matrix of filamentary metal traces, driven by reprogrammable, distributed Lorentz forces that follow from passage of electrical currents in the presence of a static magnetic field. The resulting system demonstrates complex, dynamic morphing capabilities with response times within 0.1 s. Implementing an in-situ stereo-imaging feedback strategy with a digitally controlled actuation scheme guided by an optimization algorithm, yields surfaces that can self-evolve into a wide range of 3-dimensional (3D) target shapes with high precision, including an ability to morph against extrinsic or intrinsic perturbations. These concepts support a data-driven approach to the design of dynamic, soft matter, with many unique characteristics.

scholarly journals 4D imaging of soft matter in liquid water

2021 ◽  
Author(s):  
Gabriele Marchello ◽  
Cesare De Pace ◽  
Silvia Acosta-Gutierrez ◽  
Ciro Lopez-Vazquez ◽  
Neil Wilkinson ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Liquid Phase ◽  
Liquid State ◽  
Soft Matter ◽  
Protein Structures ◽  
Soft Materials ◽  
Thermal Fluctuations ◽  
Natural State ◽  
Particle Analysis ◽  
Polymer Micelle

Water is a critical component for both function and structure of soft matter and it is what bestows the adjective soft. Imaging samples in liquid state is thus paramount to gathering structural and dynamical information of any soft materials. Herein we propose the use of liquid phase electron microscopy to expand ultrastructural analysis into dynamical investigations. We imaged two soft matter examples: a polymer micelle and a protein in liquid phase using transmission electron microscopy and demonstrate that the inherent Brownian motion associated with the liquid state can be exploited to gather three-dimensional information of the materials in their natural state. We call such an approach brownian tomography (BT). We combine BT with single particle analysis (Brownian particle analysis BPA) to image protein structures with a spatial resolution close that achievable using cryogenic TEM. We show that BPA allows sub-nanometer resolution of soft materials and enables to gather information on conformational changes, hydration dynamics, and the effect of thermal fluctuations.Abstract Figure

scholarly journals Scaling law to determine peak forces in tapping-mode AFM experiments on finite elastic soft matter systems

2017 ◽  
Vol 8 ◽  
pp. 968-974 ◽  
Author(s):  
Horacio V Guzman
Keyword(s):  
Soft Matter ◽  
Scaling Law ◽  
Soft Materials ◽  
Operating Conditions ◽  
Peak Force ◽  
Liquid Environment ◽  
Tapping Mode ◽  
Force Microscopy ◽  
Mechanics Model ◽  
Tapping Mode Afm

Analytical equations to estimate the peak force will facilitate the interpretation and the planning of amplitude-modulation force microscopy (tapping mode) experiments. A closed-form analytical equation to estimate the tip–sample peak forces while imaging soft materials in liquid environment and within an elastic deformation regime has been deduced. We have combined a multivariate regression method with input from the virial–dissipation equations and Tatara’s bidimensional deformation contact mechanics model. The equation enables to estimate the peak force based on the tapping mode observables, probe characteristics and the material properties of the sample. The accuracy of the equation has been verified by comparing it to numerical simulations for the archetypical operating conditions to image soft matter with high spatial resolution in tapping-mode AFM.

VISUALIZING SOFT MATTER: MESOSCOPIC SIMULATIONS OF MEMBRANES, VESICLES AND NANOPARTICLES

2007 ◽  
Vol 02 (01) ◽  
pp. 33-55 ◽  
Author(s):  
JULIAN SHILLCOCK ◽  
REINHARD LIPOWSKY
Keyword(s):  
Smart Materials ◽  
Soft Matter ◽  
Dissipative Particle Dynamics ◽  
Lipid Vesicles ◽  
Soft Materials ◽  
Coarse Grained ◽  
Molecular Characteristics ◽  
Dynamics Simulations ◽  
And Behavior ◽  
Mesoscopic Simulations

Biological membranes have properties and behavior that emerge from the propagation of the molecular characteristics of their components across many scales. Artificial smart materials, such as drug delivery vehicles and nanoparticles, often rely on modifying naturally-occurring soft matter, such as polymers and lipid vesicles, so that they possess useful behavior. Mesoscopic simulations allow in silico experiments to be easily and cheaply performed on complex, soft materials requiring as input only the molecular structure of the constituents at a coarse-grained level. They can therefore act as a guide to experimenters prior to performing costly assays. Additionally, mesoscopic simulations provide the only currently feasible window on the length and time scales relevant to important biophysical processes such as vesicle fusion. We describe here recent work using Dissipative Particle Dynamics simulations to explore the structure and behavior of amphiphilic membranes, the fusion of vesicles, and the interactions between rigid nanoparticles and soft surfaces.

scholarly journals A soft matter computer for soft robots

2019 ◽  
Vol 4 (33) ◽  
pp. eaaw6060 ◽  
Author(s):  
M. Garrad ◽  
G. Soter ◽  
A. T. Conn ◽  
H. Hauser ◽  
J. Rossiter
Keyword(s):  
Smart Materials ◽  
Soft Matter ◽  
Autonomous Robots ◽  
Low Cost ◽  
Input Parameter ◽  
Soft Materials ◽  
Soft Robots ◽  
Stimulus Response ◽  
Bending Actuator ◽  
Two Degree Of Freedom

Despite the growing interest in soft robotics, little attention has been paid to the development of soft matter computational mechanisms. Embedding computation directly into soft materials is not only necessary for the next generation of fully soft robots but also for smart materials to move beyond stimulus-response relationships and toward the intelligent behaviors seen in biological systems. This article describes soft matter computers (SMCs), low-cost, and easily fabricated computational mechanisms for soft robots. The building block of an SMC is a conductive fluid receptor (CFR), which maps a fluidic input signal to an electrical output signal via electrodes embedded into a soft tube. SMCs could perform both analog and digital computation. The potential of SMCs is demonstrated by integrating them into three soft robots: (i) a Softworm robot was controlled by an SMC that generated the control signals necessary for three distinct gaits; (ii) a soft gripper was given a set of reflexes that could be programmed by adjusting the parameters of the CFR; and (iii) a two–degree of freedom bending actuator was switched between three distinct behaviors by varying only one input parameter. SMCs are a low-cost way to integrate computation directly into soft materials and an important step toward entirely soft autonomous robots.

Introduction to peptide soft materials

Soft Matter ◽  
2020 ◽  
Vol 16 (44) ◽  
pp. 9998-10000
Author(s):  
Arindam Banerjee ◽  
Ian W. Hamley
Keyword(s):  
Soft Matter ◽  
Soft Materials

Arindam Banerjee and Ian W. Hamley introduce the Soft Matter themed collection on peptide soft materials.

scholarly journals Tracking the time evolution of soft matter systems via topological structural heterogeneity

2022 ◽  
Vol 3 (1) ◽  
Author(s):  
Ingrid Membrillo Solis ◽  
Tetiana Orlova ◽  
Karolina Bednarska ◽  
Piotr Lesiak ◽  
Tomasz R. Woliński ◽  
...  
Keyword(s):  
Time Evolution ◽  
Soft Matter ◽  
Structural Changes ◽  
Persistent Homology ◽  
Soft Materials ◽  
Structural Heterogeneity ◽  
Dynamical Behaviour ◽  
Topological Data Analysis ◽  
Analysis Tool ◽  
Wide Range

AbstractPersistent homology is an effective topological data analysis tool to quantify the structural and morphological features of soft materials, but so far it has not been used to characterise the dynamical behaviour of complex soft matter systems. Here, we introduce structural heterogeneity, a topological characteristic for semi-ordered materials that captures their degree of organisation at a mesoscopic level and tracks their time-evolution, ultimately detecting the order-disorder transition at the microscopic scale. We show that structural heterogeneity tracks structural changes in a liquid crystal nanocomposite, reveals the effect of confined geometry on the nematic-isotropic and isotropic-nematic phase transitions, and uncovers physical differences between these two processes. The system used in this work is representative of a class of composite nanomaterials, partially ordered and with complex structural and physical behaviour, where their precise characterisation poses significant challenges. Our developed analytic framework can provide both a qualitative and quantitative characterisation of the dynamical behaviour of a wide range of semi-ordered soft matter systems.

Sign in / Sign up

Export Citation Format

Share Document