arXiv subjects

Giorgio Volpe

Publications and source records attributed to Giorgio Volpe.

At least 19 recordsLinked to original sources

arXiv2026

Organic Semiconductor Alignment via Confinement in Vapor-Guided Droplets

Organic semiconductors are lightweight, solution-processable materials with strong potential for printed and flexible electronics, from deformable displays to wearable sensors. Despite significant advances in materials synthesis and manufacturing, controlling molecular and mesoscale alignment during deposition remains a central challenge, as film morphology critically governs charge transport and device performance. Here, we demonstrate that flows developing within the intrinsically confined volume of microliter vapor-guided droplets can be harnessed to produce highly aligned organic semiconductor films. As droplets move in response to an external vapor source, internal flows align organic semiconducting nanowires within the droplet prior to deposition, yielding films with pronounced directional order. Organic field-effect transistors fabricated with this approach exhibit approximately 40% enhancement in saturation current relative to spin-coated controls. Beyond improved device performance, the contactless and compact nature of our method enables the deposition and alignment of organic semiconductors on curved and flexible surfaces. More broadly, vapor-guided droplets offer a scalable framework for the confinement-induced alignment of functional soft materials, with potential for integration into existing additive manufacturing platforms for flexible electronics and beyond.

cond-mat.soft↗

arXiv2026

Spinning Living Crystals of Run-and-Tumble Particles with Environmental Feedback

Collective rotations are common in active matter, enhancing cohesion, transport, and mixing. They are typically attributed to chiral non-reciprocal dynamics due to intrinsic particle chirality, torque-generating interactions among units, or geometric confinement. Here, we uncover a different mechanism for rotational order in active matter where a dynamic environment coordinates the self-organization of non-chiral active particles into living crystals exhibiting sustained collective solid-like rotations. At intermediate densities, feedback from a fluctuating landscape of passive Brownian particles stabilizes large living crystals of obstacle-avoiding run-and-tumble agents. Strikingly, this environmental feedback also produces living crystals with qualitatively distinct dynamics: collective solid-like spinning emerges for particles with long persistence times approaching ballistic motion, rather than for particles moving by conventional enhanced diffusion. Beyond revealing a new route to collective rotational order in active matter, these findings highlight the integral role of a dynamic environment in self-organization and suggest environment-mediated design principles for active materials with unconventional dynamical responses.

cond-mat.soft↗

arXiv2025

Towards Animate Droplets: Active, Adaptive, and Autonomous

Droplets, sub-millilitre liquid volumes with at least one interface, have traditionally served as compartments for storing, transporting, and delivering materials. Beyond familiar applications in food, coatings, and consumer goods, they find cutting-edge use in energy storage, sensing, and tissue engineering. The next frontier is their integration into animate matter, emerging materials defined by their levels of activity, adaptiveness, and autonomy. Easy to produce and dispense or print into complex structures, and with enormous chemical versatility, droplets are ideal building blocks for animate matter. In this Perspective, we outline a roadmap for advancing animacy in droplets and call for a more concerted effort to integrate novel mechanisms for motility, sensing, and decision-making into droplet design. Although research on active droplets spans more than a century, achieving true autonomy, where droplets process multiple stimuli and respond without external control, remains a central challenge. We hope to inspire interdisciplinary collaboration towards applications in consumer goods, microfluidics, adaptive optics, tissue engineering, and soft robotics.

cond-mat.soft↗

arXiv2025

U-Net 3+ for Anomalous Diffusion Analysis enhanced with Mixture Estimates (U-AnD-ME) in particle-tracking data

Biophysical processes within living systems rely on encounters and interactions between molecules in complex environments such as cells. They are often described by anomalous diffusion transport. Recent advances in single-molecule microscopy and particle-tracking techniques have yielded an abundance of data in the form of videos and trajectories that contain critical information about these biologically significant processes. However, standard approaches for characterizing anomalous diffusion from these measurements often struggle in cases of practical interest, e.g. due to short, noisy trajectories. Fully exploiting this data therefore requires the development of advanced analysis methods -- a core goal at the heart of the recent international Anomalous Diffusion Challenges. Here, we introduce a novel machine-learning framework, U-net 3+ for Anomalous Diffusion analysis enhanced with Mixture Estimates (U-AnD-ME), that applies a U-Net 3+ based neural network alongside Gaussian mixture models to enable highly accurate characterisation of single-particle tracking data. In the 2024 Anomalous Diffusion Challenge, U-AnD-ME outperformed all other participating methods for the analysis of two-dimensional anomalous diffusion trajectories at both single-trajectory and ensemble levels. Using a large dataset inspired by the Challenge, we further characterize the performance of U-AnD-ME in segmenting trajectories and inferring anomalous diffusion properties.

physics.data-an↗

arXiv2024

Anomalous Dynamics of Superparamagnetic Colloidal Microrobots with Tailored Statistics

Living organisms have developed advanced motion strategies for efficient space exploration, serving as inspiration for the movements of microrobots. These real-life strategies often involve anomalous dynamics displaying random movement patterns that deviate from Brownian motion. Despite their biological inspiration, autonomous stochastic navigation strategies of current microrobots remain much less versatile than those of their living counterparts. Supported by theoretical reasoning, this work demonstrates superparamagnetic colloidal microrobots with fully customizable stochastic dynamics displaying the entire spectrum of anomalous diffusion, from subdiffusion to superdiffusion, across statistically significant spatial and temporal scales (covering at least two decades). By simultaneously tuning microrobots' step-length distribution and, critically, their velocity autocorrelation function with magnetic fields, fundamental anomalous dynamics are reproduced with tailored properties mimicking L\'evy walks and fractional Brownian motion. These findings pave the way for programmable microrobotic systems that replicate optimal stochastic navigation strategies found in nature for applications in medical robotics and environmental remediation.

cond-mat.soft↗

arXiv2024

Roadmap for Animate Matter

Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, adaptability, and autonomy, emulate properties of living systems. While only biological materials fully embody these principles, artificial versions are advancing rapidly, promising transformative impacts across various sectors. This roadmap presents authoritative perspectives on animate materials across different disciplines and scales, highlighting their interdisciplinary nature and potential applications in diverse fields including nanotechnology, robotics and the built environment. It underscores the need for concerted efforts to address shared challenges such as complexity management, scalability, evolvability, interdisciplinary collaboration, and ethical and environmental considerations. The framework defined by classifying materials based on their level of animacy can guide this emerging field encouraging cooperation and responsible development. By unravelling the mysteries of living matter and leveraging its principles, we can design materials and systems that will transform our world in a more sustainable manner.

cond-mat.mtrl-sci↗

arXiv2024

Capillary-Assisted Printing of Droplets at a Solid-Like Liquid-Liquid Interface

Capillary forces guide the motion of biomolecular condensates, water-borne insects, and breakfast cereal. These surface-mediated interactions can be harnessed to build units into materials with exotic properties deriving from mesoscale structure. Droplets are promising building blocks for these materials, finding applications in tissue engineering, adaptive optics, and structural colour. However, the instability of water droplets at many liquid-liquid interfaces hampers the use of capillarity for the assembly of droplet-based materials. Here, we use nanoparticle surfactants to form solid-like oil-water interfaces at which aqueous droplets sit for extended periods. We find that microlitre-sized droplets at these interfaces attract each other over millimetric scales. We rationalize this interaction with a modified theory of capillarity. Applying printing methods allows us to finely control initial droplet positions, from which they self-assemble into cellular materials. Finally, by functionalising the interface with gold nanoparticles, we use plasmon-assisted optofluidics to manipulate these droplet-based materials with temperature gradients.

cond-mat.soft↗

arXiv2024

3D model for surface accumulation of chiral and non-chiral microswimmers

Persistent motion of microswimmers near boundaries is known to result in surface accumulation. Recently it was shown experimentally that surface accumulation of microswimmers is impacted primarily by steric forces and short-ranged hydrodynamics. A way to control surface accumulation is by reducing the contact surface area between swimmers and surface by modifying its topography, typically through the application of microscale structure. In this work, we introduce a three-dimensional(3D) model of a microswimmer navigating a volume bounded by a top and bottom surface. We describe the swimmer-surface interaction with an effective short-ranged hydrodynamic alignment force, and study numerically the effect of surface textures, modelled by convex obstacles, on the surface accumulation of chiral and non-chiral microswimmers. We find that, depending on the angular velocity of the swimmer, and the alignment force, convex obstacles can either hinder or enhance surface accumulation. We discuss potential applications to sorting of microswimmers by their angular velocity.

cond-mat.soft↗

arXiv2024

Efficient Rare Event Sampling with Unsupervised Normalising Flows

From Physics and Biology to Seismology and Economics, the behaviour of countless systems is determined by impactful yet unlikely transitions between metastable states known as \emph{rare events}, the study of which is essential for understanding and controlling these systems' properties. Classical computational methods to sample rare events remain prohibitively inefficient, and are a bottleneck for enhanced samplers requiring prior data. Here, we introduce a novel framework, FlowRES that uses unsupervised normalising flow neural networks to enhance Monte Carlo sampling of rare events by generating high-quality nonlocal Monte Carlo proposals. We validate FlowRES by sampling the transition path ensembles of equilibrium and non-equilibrium systems of Brownian particles exploring increasingly complex potential surfaces. Beyond eliminating requirements for prior data, FlowRES features key advantages over established samplers: no collective variables need defining, its efficiency remains constant even as events become increasingly unlikely, and it can handle systems with multiple routes between states.

physics.comp-ph↗

arXiv2023

Quantitative evaluation of methods to analyze motion changes in single-particle experiments

The analysis of live-cell single-molecule imaging experiments can reveal valuable information about the heterogeneity of transport processes and interactions between cell components. These characteristics are seen as motion changes in the particle trajectories. Despite the existence of multiple approaches to carry out this type of analysis, no objective assessment of these methods has been performed so far. Here, we report the results of a competition to characterize and rank the performance of these methods when analyzing the dynamic behavior of single molecules. To run this competition, we implemented a software library that simulates realistic data corresponding to widespread diffusion and interaction models, both in the form of trajectories and videos obtained in typical experimental conditions. The competition constitutes the first assessment of these methods, providing insights into the current limitations of the field, fostering the development of new approaches, and guiding researchers to identify optimal tools for analyzing their experiments.

cond-mat.soft↗

arXiv2023

Patchy landscapes promote stability of small groups

Group formation and coordination are fundamental characteristics of living systems, essential for performing tasks and ensuring survival. Interactions between individuals play a key role in group formation, and the impact of resource distributions is a vibrant area of research. Using active particles in a tuneable optical environment as a model system, we demonstrate that heterogeneous energy source distributions result in smaller, more stable groups with reduced individual exchange between clusters compared to homogeneous conditions. Reduced group sizes can be beneficial to optimise resources in heterogeneous environments and to control information flow within populations. Devoid of biological complications, our system provides insights into the importance of patchy landscapes in ecological dynamics and holds implications for refining swarm intelligence algorithms and enhancing crowd control techniques.

cond-mat.soft↗

arXiv2023

Designing thermoplasmonic polymersomes for photothermal therapy

Polymersomes, vesicles self-assembled from amphiphilic polymers, are promising nanocarriers for the targeted intracellular delivery of therapeutics. Integrating inorganic light-absorbing materials with plasmonic properties, such as gold, into their membrane by in situ synthesis is a stepping stone to enable their use for photothermal therapy. Yet, it still needs to be determined whether the in situ synthesis of gold can produce polymersomes with thermoplasmonic properties without altering their morphology, stability, and nanocarrier functionality. Here we demonstrate that small gold nanoparticles can be controllably nucleated within biocompatible block-copolymer membranes to design hybrid polymersomes with a noteworthy thermoplasmonic response. The cumulative absorption of individual 2 nm gold nanoparticles can induce temperature increases in 10 K in dilute suspensions of hybrid polymersomes upon laser illumination. Furthermore, we develop a theoretical model to rationalize our observations and predict the thermoplasmonic response of our hybrid polymersomes. We finally demonstrate in vitro photothermal therapy of cancer cells, enhanced by the receptor-mediated endocytosis of our hybrid polymersomes. We envision that our nanotechnological platform can be translated to phenotypic cell targeting to precisely deliver effective photothermal agents.

cond-mat.soft↗

arXiv2023

Optimal face-to-face coupling for fast self-folding kirigami

Kirigami-inspired designs can enable self-folding three-dimensional materials from flat, two-dimensional sheets. Hierarchical designs of connected levels increase the diversity of possible target structures, yet they can lead to longer folding times in the presence of fluctuations. Here, we study the effect of rotational coupling between levels on the self-folding of two-level kirigami designs driven by thermal noise in a fluid. Naturally present due to hydrodynamic resistance, we find that optimization of this coupling as control parameter can significantly improve a structure's self-folding rate and yield.

cond-mat.soft↗

arXiv2023

Environmental Memory Boosts Group Formation of Clueless Individuals

The formation of groups of interacting individuals improves performance and fitness in many decentralised systems, from micro-organisms to social insects, from robotic swarms to artificial intelligence algorithms. Often, group formation and high-level coordination in these systems emerge from individuals with limited information-processing capabilities implementing low-level rules of communication to signal to each other. Here, we show that, even in a community of clueless individuals incapable of processing information and communicating, a dynamic environment can coordinate group formation by transiently storing memory of the earlier passage of individuals. Our results identify a new mechanism of indirect coordination via shared memory that is primarily promoted and reinforced by dynamic environmental factors, thus overshadowing the need for any form of explicit signalling between individuals. We expect this pathway to group formation to be relevant for understanding and controlling self-organisation and collective decision making in both living and artificial active matter in real-life environments.

cond-mat.soft↗

arXiv2023

Light, Matter, Action: Shining light on active matter

Light carries energy and momentum. It can therefore alter the motion of objects from atomic to astronomical scales. Being widely available, readily controllable and broadly biocompatible, light is also an ideal tool to propel microscopic particles, drive them out of thermodynamic equilibrium and make them active. Thus, light-driven particles have become a recent focus of research in the field of soft active matter. In this perspective, we discuss recent advances in the control of soft active matter with light, which has mainly been achieved using light intensity. We also highlight some first attempts to utilize light's additional degrees of freedom, such as its wavelength, polarization, and momentum. We then argue that fully exploiting light with all of its properties will play a critical role to increase the level of control over the actuation of active matter as well as the flow of light itself through it. This enabling step will advance the design of soft active matter systems, their functionalities and their transfer towards technological applications.

cond-mat.soft↗

arXiv2022

Roadmap for Optical Tweezers

Optical tweezers are tools made of light that enable contactless pushing, trapping, and manipulation of objects ranging from atoms to space light sails. Since the pioneering work by Arthur Ashkin in the 1970s, optical tweezers have evolved into sophisticated instruments and have been employed in a broad range of applications in life sciences, physics, and engineering. These include accurate force and torque measurement at the femtonewton level, microrheology of complex fluids, single micro- and nanoparticle spectroscopy, single-cell analysis, and statistical-physics experiments. This roadmap provides insights into current investigations involving optical forces and optical tweezers from their theoretical foundations to designs and setups. It also offers perspectives for applications to a wide range of research fields, from biophysics to space exploration.

physics.optics↗

arXiv2022

The role of disorder in the motion of chiral swimmers in the presence of obstacles

The presence of obstacles is intuitively expected to hinder the diffusive transport of micro-swimmers. However, for chiral micro-swimmers, a low density of obstacles near a surface can enhance their diffusive behavior, due to the rectification of the chiral motion by the obstacles. Here, we study numerically the role that disorder plays in determining the transport dynamics of chiral micro-swimmers on surfaces with obstacles. We consider different densities of regularly spaced obstacles and distinct types of disorder: noise in the dynamics of the micro-swimmer, quenched noise in the positions of the obstacles as well as obstacle size polydispersity. We show that, depending on the type and strength of the disorder, the presence of obstacles can either enhance or hinder transport, and discuss implications for the control of active transport in disordered media.

cond-mat.soft↗

arXiv2022

Steering self-organisation through confinement

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement occurs through interactions with boundaries, and can function as either a catalyst or inhibitor of self-organisation. It can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework for future research, we examine the role of confinement in self-organisation and identify overarching scientific challenges across disciplines that need to be addressed to harness its full scientific and technological potential. This framework will not only accelerate the generation of a common deeper understanding of self-organisation but also trigger the development of innovative strategies to steer it through confinement, with impact, e.g., on the design of smarter materials, tissue engineering for biomedicine and crowd management.

nlin.AO↗