arXiv subjects

Chiara Daraio

Publications and source records attributed to Chiara Daraio.

At least 19 recordsLinked to original sources

arXiv2026

FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms

Molecular crystal structure prediction (CSP) is essential for applications in pharmaceuticals and organic electronics. However, CSP remains challenging and computationally intensive due to the need to explore a large search space with sub-kJ/mol accuracy to distinguish between competing polymorphs. While dispersion-inclusive density functional theory (DFT) offers the necessary precision, its computational cost is impractical for a large number of putative structures. Here, we present FastCSP, an open-source, end-to-end CSP workflow driven entirely by a single pretrained universal machine learning interatomic potential (MLIP), the Universal Model for Atoms (UMA), without any system-specific fine-tuning or DFT calculations. FastCSP integrates conformer generation, random structure generation via Genarris 3, geometry optimization, free energy evaluation, and conformer energy corrections, all powered by UMA. Benchmarked on 28 semi-rigid and 10 flexible molecules spanning 74 experimental polymorphs, FastCSP reliably recovers all known structures, ranking them within 9 kJ/mol of the global minimum. UMA reproduces dispersion-inclusive DFT results with high fidelity across chemically diverse compounds. Conformer corrections are particularly beneficial for flexible compounds with conformational polymorphism, such as ROY. UMA's accuracy, transferability, and computational cost thus eliminate the need for classical force fields in early-stage screening and DFT-based re-ranking in CSP workflows. The open-source release of the entire FastCSP workflow lowers the barrier to accessing CSP, enabling both pharmaceutical-grade and high-throughput polymorph screening within practical computational reach.

physics.chem-ph↗

arXiv2026

Irregular Metamaterial Networks

Metamaterials can achieve exceptional functionality through careful engineering of their mesoscale structure. Although appropriately introduced irregularities can be advantageous, current approaches largely conform to regular structures to preserve tractability. Here, we contend that network theory, enriched with geometry and physics, provides a natural framework for designing metamaterials with controlled irregularities at relevant scales, thereby enabling the discovery of new property-enhancing structures. We examine how this augmented network theory can facilitate the creation of irregular metamaterials with enhanced or novel properties and how metamaterial research, in turn, is opening new directions in network science. Supported by machine learning and advanced self-assembly, the emerging field of irregular metamaterial networks is poised to transform inverse design and scalable manufacturing of novel materials.

cond-mat.dis-nn↗

arXiv2026

Nonlinear Wave Propagation in 1D Polycatenated Ring Chains

We study the nonlinear wave dynamics of one-dimensional chains of polycatenated rings. These interlocked structures support amplitude-dependent nonlinear wave propagation driven by tensile activation and internal structural flexibility, unlike traditional granular crystals. Through dynamic impact experiments, finite-element modeling, and discrete-particle simulations of vertical chains pretensioned by gravity, we observe and explain nonlinear waves characterized by a compact leading wavefront followed by persistent trailing oscillations, which arise from energy partitioning into the rings' internal bending modes. Further, we demonstrate that the system's nonlinearity is not a fixed material constant. By altering the rings' geometric aspect ratio and contact angles, we can tune the effective contact exponent and the amplitude scaling of the wave speed. This work builds upon nonlinear wave propagation in classical granular crystals and establishes polycatenated systems as a highly tunable and designable platform to study and control nonlinear dynamics.

cond-mat.soft↗

arXiv2026

Graded anisotropic metamaterials for elastic wave mode conversion

Efficient transmission of elastic waves across interfaces is central to several applications, including medical imaging, seismic isolation, and transducer design. Interfaces with abrupt changes in the material properties significantly impede wave transmission, leading to reflections. This limitation, known as impedance mismatch, becomes even more prominent for mode conversion between different wave types due to polarization mismatch. In this study, we investigate a mechanism employing two-dimensional functionally graded anisotropic metamaterials to facilitate longitudinal--shear mode conversion as waves propagate from a stiff to a compliant medium. By embedding density and anisotropic shape gradients within the functionally graded metamaterial, polarization-induced impedance mismatch is mitigated and efficient mode conversion is enabled. We use unit cell dispersion analysis to tailor the frequency range for mode conversion through gradation in the dispersion behavior and coupling between modes. Using frequency-domain finite element analysis, we demonstrate broadband mode conversion across interfaces with large stiffness contrast operating in the 1--10 kHz range. We then experimentally validate and quantify mode conversion through full-field velocity measurements on an additively manufactured specimen. We further apply the methodology to design a device capable of converting radial--tangential wave modes.

physics.optics↗

arXiv2026

Trichome entanglement enhances damage tolerance in microstructured biocomposites

Achieving damage tolerance in composite materials remains a central challenge in materials science. Conventional strategies often rely on filler incorporation or chemical modification, which can limit energy dissipation and constrain structural stability. Here, we leverage the unique morphology of Spirulina trichomes to investigate a reinforcement mechanism based on physical filament entanglement. By comparing helical trichomes with their morphologically straightened counterparts, we isolate filament geometry as the key parameter governing mechanical performance. Trichome-based suspensions exhibit enhanced viscoelastic response and a threefold increase in yield stress. When processed via extrusion-based 3D printing using hydroxyethyl cellulose (HEC) as a matrix, entangled trichomes yield a 290% improvement in bending strength and a 15-fold enhancement in work of fracture. Fracture surface analysis reveals a transition from interfacial debonding and pull-out (in filaments) to crack propagation through the entangled network, indicating structure-mediated toughening. These findings establish trichome entanglement as a scalable, physically driven mechanism for enhancing damage tolerance through microstructural architecture.

cond-mat.mtrl-sci↗

arXiv2025

Deformation Driven Suction Cups: A Mechanics-Based Approach to Wearable Electronics

Wearable electronics are emerging as essential tools for health monitoring, haptic feedback, and human-computer interactions. While stable contact at the device-body interface is critical for these applications, it remains challenging due to the skin's softness, roughness, and mechanical variability. Existing methods, such as grounding structures or adhesive tapes, often suffer from contact loss, limited repeatability, and restrictions on the types of electronics they can support. Suction-based adhesives offer a promising alternative by generating negative pressure without requiring tight bands or chemical adhesives. However, most existing cup designs rely on rigid-surface assumptions and overlook mechanical interactions between suction cups and skin. Inspired by traditional cupping therapies, we present a suction-based adhesive system that attaches through elastic deformation and recovery. Using analytical modeling, numerical simulations, and experiments, we present a mechanics-based framework showing how suction performance depends on cup geometry, substrate compliance, and interfacial adhesion. We show that cup geometry should be tailored to substrate stiffness. Wide, flat suction cups perform well on rigid surfaces but fail on soft ones like skin due to substrate intrusion into the chamber. Narrow and tall domes better preserve recoverable volume and generate stronger suction. To improve sealing on rough, dry skin, we introduce a soft, tacky interfacial layer informed by a contact mechanics model. Using our design principles for skin suction adhesives, we demonstrate secure attachment of rigid and flexible components including motion sensors, haptic actuators, and electrophysiological electrodes across diverse anatomical regions. These findings provide a fundamental basis for designing the next generation of skin-friendly adhesives for wearable electronics.

physics.med-ph↗

arXiv2025

Computational Design and Fabrication of Modular Robots with Untethered Control

Natural organisms utilize distributed actuation through their musculoskeletal systems to adapt their gait for traversing diverse terrains or to morph their bodies for varied tasks. A longstanding challenge in robotics is to emulate this capability of natural organisms, which has motivated the development of numerous soft robotic systems. However, such systems are generally optimized for a single functionality, lack the ability to change form or function on demand, or remain tethered to bulky control systems. To address these limitations, we present a framework for designing and controlling robots that utilize distributed actuation. We propose a novel building block that integrates 3D-printed bones with liquid crystal elastomer (LCE) muscles as lightweight actuators, enabling the modular assembly of musculoskeletal robots. We developed LCE rods that contract in response to infrared radiation, thereby providing localized, untethered control over the distributed skeletal network and producing global deformations of the robot. To fully capitalize on the extensive design space, we introduce two computational tools: one for optimizing the robot's skeletal graph to achieve multiple target deformations, and another for co-optimizing skeletal designs and control gaits to realize desired locomotion. We validate our framework by constructing several robots that demonstrate complex shape morphing, diverse control schemes, and environmental adaptability. Our system integrates advances in modular material building, untethered and distributed control, and computational design to introduce a new generation of robots that brings us closer to the capabilities of living organisms.

cs.RO↗

arXiv2025

Graphene Design with Parallel Cracks: Abnormal Crack Coalescence and Its Impact on Mechanical Properties

Graphene is a material with potential applications in electric, thermal, and mechanical fields, and has seen significant advancements in growth methods that facilitate large-scale production. However, defects during growth and transfer to other substrates can compromise the integrity and strength of graphene. Surprisingly, the literature suggests that, in certain cases, defects can enhance or, at most, not affect the mechanical performance of graphene. Further research is necessary to explore how defects interact within graphene structure and affect its properties, especially in large-area samples. In this study, we investigate the interaction between two preexisting cracks and their effect on the mechanical properties of graphene using molecular dynamics simulations. The behavior of zigzag and armchair graphene structures with cracks separated by distances ($W_\text{gap}$) is analyzed under tensile loading. The findings reveal that crack coalescence, defined as the formation of a new crack from two existing crack tips, occurs for lower values of the distance between cracks, $W_\text{gap}$, resulting in a decline in the strength of structures. As $W_\text{gap}$ increases, the stress-strain curves shift upward, with the peak stress rising in the absence of crack coalescence. The effective stress intensity factor formulated in this study exhibits a clear upward trend with increasing $W_\text{gap}$. Furthermore, an increase in $W_\text{gap}$ induces a transition in fracture behavior from crack coalescence to independent propagation with intercrack undulation. This shift in fracture behavior demonstrates a brittle-to-ductile transition, as evidenced by increased energy absorption and delayed failure. A design guideline for the initial crack geometry is suggested by correlating peak stress with the $W_\text{gap}$, within a certain range.

cond-mat.mtrl-sci↗

arXiv2025

Visual Surface Wave Elastography: Revealing Subsurface Physical Properties via Visible Surface Waves

Wave propagation on the surface of a material contains information about physical properties beneath its surface. We propose a method for inferring the thickness and stiffness of a structure from just a video of waves on its surface. Our method works by extracting a dispersion relation from the video and then solving a physics-based optimization problem to find the best-fitting thickness and stiffness parameters. We validate our method on both simulated and real data, in both cases showing strong agreement with ground-truth measurements. Our technique provides a proof-of-concept for at-home health monitoring of medically-informative tissue properties, and it is further applicable to fields such as human-computer interaction.

cs.CV↗

arXiv2025

Controllable Interlocking from Irregularity in Two-Phase Composites

Natural materials often feature a combination of soft and stiff phases, arranged to achieve excellent mechanical properties, such as high strength and toughness. Many natural materials have even independently evolved to have similar structures to obtain these properties. For example, interlocking structures are observed in many strong and tough natural materials, across a wide range of length scales. Inspired by these materials, we present a class of two-phase composites with controllable interlocking. The composites feature tessellations of stiff particles connected by a soft matrix and we control the degree of interlocking through irregularity of particle size, geometry and arrangement. We generate the composites through stochastic network growth, using an algorithm which connects a hexagonal grid of nodes according to a coordination number, defined as the average number of connections per node. The generated network forms the soft matrix phase of the composites, while the areas enclosed by the network form the stiff reinforcing particles. At low coordination, composites feature highly polydisperse particles with irregular geometries, which are arranged non-periodically. In response to loading, these particles interlock with each other and primarily rotate and deform to accommodate non-uniform kinematic constraints from adjacent particles. In contrast, higher coordination composites feature more monodisperse particles with uniform geometries, which collectively slide. We then show how to control the degree of interlocking as a function of coordination number alone, demonstrating how irregularity facilitates controllability.

cond-mat.soft↗

arXiv2024

Polycatenated Architected Materials

Architected materials derive their properties from the geometric arrangement of their internal structural elements. Their designs rely on continuous networks of members to control the global mechanical behavior of the bulk. Here, we introduce a class of materials that consist of discrete concatenated rings or cage particles interlocked in three-dimensional networks, forming polycatenated architected materials (PAMs). We propose a general design framework that translates arbitrary crystalline networks into particles' concatenations and geometries. In response to small external loads, PAMs behave like non-Newtonian fluids, showing both shear-thinning and shear-thickening responses. At larger strains, PAMs behave like lattices and foams, with a nonlinear stress-strain relation. At microscale, we demonstrate that PAMs can change their shapes in response to applied electrostatic charges. PAM's unique properties pave the path for developing stimuli-responsive materials, energy-absorbing systems and morphing architectures.

cond-mat.soft↗

arXiv2024

Fracture Characterization of Bioinspired Irregular Network Reinforced Composites

The mechanical behavior of composite materials is significantly influenced by their structure and constituent materials. One emerging class of composite materials is irregular network reinforced composites (NRC's), whose reinforcing phase is generated by a stochastic algorithm. Although design of the reinforcing phase network offers tailorable control over both the global mechanical properties, like stiffness and strength, and the local properties, like fracture nucleation and propagation, the fracture properties of irregular NRC's has not yet been fully characterized. This is because both the irregular reinforcing structure and choice of matrix phase material significantly affect the fracture response, often resulting in diffuse damage, associated with multiple crack nucleation locations. Here, we propose irregular polymer NRC's whose matrix phase has a similar stiffness but half the strength of the reinforcing phase, which allows the structure of the reinforcing phase to control the fracture response, while still forming and maintaining a primary crack. Across a range of network coordination numbers, we obtain J-integral and R-curve measurements, and we determine that low coordination polymer NRC's primarily dissipate fracture energy through plastic zone formation, while high coordination polymer NRC's primarily dissipate energy through crack extension. Finally, we determine that there are two critical length scales to characterize and tailor the fracture response of the composites across the coordination numbers: (i) the size of the plastic zone, and (ii) the size and geometry of the structural features, defined as the areas enclosed by the reinforcing network.

cond-mat.soft↗

arXiv2024

Thermo-mechanical Properties of Hierarchical Biocomposite Materials from Photosynthetic Microorganisms

Extrusion 3D-printing of biopolymers and natural fiber-based biocomposites allows for the fabrication of complex structures, ranging from gels for healthcare applications to eco-friendly structural materials. However, traditional polymer extrusion demands high-energy consumption to pre-heat the slurries and reduce material viscosity. Additionally, natural fiber reinforcement often requires harsh treatments to improve adhesion to the matrix. Here, we overcome these challenges by introducing a systematic framework to fabricate natural biocomposite materials via a sustainable and scalable process. Using Chlorella vulgaris microalgae as the matrix, we optimize the bioink composition and the 3D-printing process to fabricate multifunctional, lightweight, hierarchical materials. A systematic dehydration approach prevents cracking and failure of the 3D-printed structure, maintaining a continuous morphology of aggregated microalgae cells that can withstand high shear forces during processing. Hydroxyethyl cellulose acts as a binder and reinforcement for Chlorella cells, leading to biocomposites with a bending stiffness above 1.5 GPa. The Chlorella biocomposites demonstrate isotropic heat transfer, functioning as effective thermal insulators with a thermal conductivity of 0.10 W/mK at room temperature. These materials show promise in applications requiring balanced thermal insulation and structural capabilities, positioning them as a sustainable alternative to conventional materials in response to increasing global materials demand.

physics.bio-ph↗

arXiv2024

Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning

Manipulating the dispersive characteristics of vibrational waves is beneficial for many applications, e.g., high-precision instruments. architected hierarchical phononic materials have sparked promise tunability of elastodynamic waves and vibrations over multiple frequency ranges. In this article, hierarchical unit-cells are obtained, where features at each length scale result in a band gap within a targeted frequency range. Our novel approach, the ``hierarchical unit-cell template method,'' is an interpretable machine-learning approach that uncovers global unit-cell shape/topology patterns corresponding to predefined band-gap objectives. A scale-separation effect is observed where the coarse-scale band-gap objective is mostly unaffected by the fine-scale features despite the closeness of their length scales, thus enabling an efficient hierarchical algorithm. Moreover, the hierarchical patterns revealed are not predefined or self-similar hierarchies as common in current hierarchical phononic materials. Thus, our approach offers a flexible and efficient method for the exploration of new regions in the hierarchical design space, extracting minimal effective patterns for inverse design in applications targeting multiple frequency ranges.

physics.app-ph↗

arXiv2024

Planar structured materials with extreme elastic anisotropy

Designing anisotropic structured materials by reducing symmetry results in unique behaviors, such as shearing under uniaxial compression or tension. This direction-dependent coupled mechanical phenomenon is crucial for applications such as energy redirection. While rank-deficient materials such as hierarchical laminates have been shown to exhibit extreme elastic anisotropy, there is limited knowledge about the fully anisotropic elasticity tensors achievable with single-scale fabrication techniques. No established upper and lower bounds on anisotropic moduli achieving extreme elastic anisotropy exist, similar to Hashin-Shtrikman bounds in isotropic composites. In this paper, we estimate the range of anisotropic stiffness tensors achieved by single-scale two-dimensional structured materials. To achieve this, we first develop a database of periodic anisotropic single-scale unit cell geometries using linear combinations of periodic cosine functions. The database covers a wide range of anisotropic elasticity tensors, which are then compared with the elasticity tensors of hierarchical laminates. Through this comparison, we identify the regions in the property space where hierarchical design is necessary to achieve extremal properties. We demonstrate a method to construct various 2D functionally graded structures using this cosine function representation for the unit cells. These graded structures seamlessly interpolate between unit cells with distinct patterns, allowing for independent control of several functional gradients, such as porosity, anisotropic moduli, and symmetry. The graded structures exhibit unique mechanical behaviors when designed with unit cells positioned at extreme parts of the property space. Specific graded designs are numerically studied to observe behaviors such as selective strain energy localization, compressive strains under tension, and localized rotations.

cond-mat.mtrl-sci↗

arXiv2024

Programmable Multi-responsive Nanocellulose-based Hydrogels with Embodied Logic

Programmable materials are desirable for a variety of functional applications that range from biomedical devices, actuators and soft robots to adaptive surfaces and deployable structures. However, current smart materials are often designed to respond to single stimuli (like temperature, humidity, or light). Here, a novel multi-stimuli-responsive composite is fabricated using direct ink writing (DIW) to enable programmability in both space and time and computation of logic operations. The composite hydrogels consist of double-network matrices of poly(N-isopropylacrylamide) (PNIPAM) or poly(acrylic acid) (PAA) and sodium alginate (SA) and are reinforced by a high content of cellulose nanocrystals (CNC) (14 wt%) and nanofibers (CNF) (1 wt%). These composites exhibit a simultaneously tunable response to external stimuli, such as temperature, pH, and ion concentration, enabling precise control over their swelling and shrinking behavior, shape, and mechanical properties over time. Bilayer hydrogel actuators are designed to display bidirectional bending in response to various stimuli scenarios. Finally, to leverage the multi-responsiveness and programmability of this new composite, Boolean algebra concepts are used to design and execute NOT, YES, OR, and AND logic gates, paving the way for self-actuating materials with embodied logic.

cond-mat.mtrl-sci↗

arXiv2024

Extracting Geometry and Topology of Orange Pericarps for the Design of Bioinspired Energy Absorbing Materials

As a result of evolution, many biological materials have developed irregular structures that lead to outstanding mechanical properties, like high stiffness-to-weight ratios and good energy absorption. To reproduce these properties in synthetic materials, biomimicry typically replicates the irregular natural structure, often leading to fabrication challenges. Here, we present a bioinspired material design method that instead reduces the irregular natural structure to a finite set of building blocks, also known as tiles, and rules to connect them, and then uses these elements as instructions to generate synthetic materials with mechanical properties similar to the biological materials. We demonstrate the method using the pericarp of the orange, a member of the citrus family known for its protective, energy-absorbing capabilities. We generate polymer samples and characterize them under quasi-static and dynamic compression and observe spatially-varying stiffness and good energy absorption, as seen in the biological materials. By quantifying which tiles and connectivity rules locally deform in response to loading, we determine how to spatially control the stiffness and energy absorption.

cond-mat.mtrl-sci↗

arXiv2024

Sparse metapiles for shear wave attenuation in half-spaces

We show that shear waves traveling towards the surface of a half-space medium can be attenuated via buried one-dimensional arrays of resonators -- here called metapiles -- arranged according to sparse patterns around a site to be isolated. Our focus is on shear waves approaching the surface along a direction perpendicular to the surface itself. First, we illustrate the behavior of metapiles, both experimentally and numerically, using 3D printed resonators embedded in an acrylic plate. Then, via numerical simulations, we extend this idea to the case study of an idealized soil half-space, and elucidate the influence of various design parameters on wave attenuation. Results of this work demonstrate that significant wave attenuation can be achieved by installing sparse resonating piles around a selected site on the free surface of the medium, rather than placing resonators directly underneath that same site. This work might have implications in metamaterial-based wave attenuation applications across scales.

physics.app-ph↗