Stuck on Repeat: Dynamic Liquid Crystal Elastomers as (Re)trainable Adhesives

ACS Applied Materials & Interfaces · 2026-01-08

Polymeric networks whose performance can be trained as a function of mechanical inputs provide additional possibilities, as they offer an opportunity to further modulate a material’s properties post-synthesis and processing. Herein, disulfide-containing dynamic liquid crystal elastomer (LCE) adhesives exhibiting (re)trainable multistage adhesive character are reported. Synthetic tailoring of the mesogen lateral substituent size allows for direct tuning of the thermal properties (Tg and TNI) of the network. These dynamic LCEs exhibit pressure-tunable adhesive behavior as a result of their inherent soft elasticity and stimuli-responsive dynamic bonds. Furthermore, higher-strength hot melt adhesive joints can be formed through the activation of the incorporated dynamic disulfide bonds at high temperatures (>150 °C). General adhesive performance can be tuned through mesogen structure, while multicycle probe-tack tests show that their force of adhesion increases with each cycle, demonstrating the trainability of the pressure-tunable adhesive response with repeated use. Thermal disruption of the LC phase resets the adhesive character, which can be subsequently reattained through mechanical training.

Synthesis of Vinylogous Urea and Urethane Vitrimers with Varying Monomer Chain Lengths

Knowledge@UChicago (University of Chicago) · 2026-01-01

Vinylogous urea and urethane vitrimers are a class of dynamically cross-linked materials which undergo rapid bond exchange. They engage in associative cross-linking, a type of dynamic covalent bonding in which new bonds form before old bonds break, maintaining a fixed cross-link density and allowing for self-healing. Due to the nature of their dynamic cross-links, the networks are degradable and chemically recyclable, presenting a potential sustainable alternative for commercial plastics. However, current research has not significantly explored the impact of varying the monomer chain length, which could enable control of the cross-link density and access differing mechanical properties of the material. This work aims to synthesize vinylogous urea and urethane networks with varying molecular weight of the monomer. Utilizing a chain-transfer agent, we control the repeat units in the monomer. Synthesis of amine-terminated monomers, acetoacetate synthesis, and incorporation of trifunctional cross-linkers are carried out with the goal of network creation. In future work, the properties of the synthesized networks can be characterized and compared to those of commercial plastics.

Fully biodegradable printed electronic sensors based on biomass-derived graphene inks and agripapers

npj Advanced Manufacturing · 2026-01-28 · 3 citations

While printed electronic sensors present significant opportunities for the Internet of Things (IoT), industrial-scale production of these devices also raises numerous environmental concerns, including electronic waste generation and critical mineral depletion. Here, we circumvent these issues by demonstrating high-performance biodegradable printed electronic sensors based exclusively on agripaper substrates and graphene inks sourced from biomass. The agripaper substrate is produced from miscanthus and hemp, which are hardy, drought-tolerant agricultural crops. Meanwhile, the sensing layer is composed of cellulose nanocrystals derived from miscanthus, and graphene nanoplatelets derived from hardwood biochar. These plant-based printing materials are renewable, biodegradable, and readily processable at scale. The resulting printed electronic sensors exhibit superlative humidity sensitivity, showing a relative resistance change of 2.6 over a humidity range of 35–85% RH with response and recovery times of ~1 second and ~4 seconds, respectively. These sensors also perform well under humidity cycling and possess minimal confounding temperature dependence, outperforming traditional devices based on plastic substrates and metallic inks. By utilizing biomass for all raw materials, this additive manufacturing methodology is sustainable, minimizes supply chain risks, and provides an enabling step towards a circular bioeconomy.

Control of Dynamic Composites through Filler Surface Chemistry

ACS Macro Letters · 2026-02-06 · 1 citations

The addition of hard fillers to polymeric networks allows for enhancement of mechanical properties, generally at the expense of extensibility. In the case of filled elastomers (such as tires), the hard particles cause damage to the underlying network when strained, resulting in severe mechanical hysteresis in cyclic loading experiments (the Mullins effect). As such, dynamic networks, which are able to heal damage through exchange reactions, are a promising candidate for composite matrices. This work investigates the influence of tunable dynamic bonds at the surface of silica particles in the presence of a fixed, complementary dynamic network matrix. The surface chemistry, composed of benzalcyanoacetamide Michael acceptors, undergoes room temperature, catalyst-free dynamic exchange with thiols with equilibrium constants (Keq) that can be manipulated by the electronic nature of the acceptor. Increasing the Keq of the particle surface relative to the dynamic matrix was found to promote the overall reinforcement of the composites, while also influencing the phase separation behavior of the matrix. Critically, tensile experiments reveal that ambient dynamic exchange allows for the recovery of network damage as a function of waiting time between loading cycles.

Designing Thermally Compatible Template‐Coating Pairs Toward Dimensionally Stable 3D Porous Carbons with Tunable Density

Advanced Functional Materials · 2025-10-01

Abstract The macroscale fabrication of 3D porous carbons with adjustable density and hierarchical architecture is crucial for emerging applications in energy storage, chemical separations, and lightweight structural materials. The pyrolytic conversion of polymer precursors is a common route to 3D porous carbon architectures, which typically relies on a single porous polymer precursor to function both as the structural blueprint and the carbon source. However, this approach can lead to substantial volume reduction, poor mass retention, and loss of architectural features, necessitating compromises between structural inheritance, dimensional stability, and control of density during pyrolysis. Here, a template‐coating platform is utilized to separate these conflicting requirements, facilitating independent optimization of mass and architecture. Specifically, a series of polybenzoxazine coatings is investigated to target early carbonization, minimal degradation, and high char yield. Concurrently, a complementary series of hierarchically porous polystyrene template architectures with tunable thermal properties is developed to meet synthetic and thermal compatibility criteria. The optimized template‐coating combination results in porous carbons that retain the architectural features of the template while maintaining their dimensional integrity (<10% linear shrinkage). By adjusting the coating weight fraction and pyrolysis temperature, we demonstrated a broad range of bulk densities (≈0.1–0.7 g cm −3 ) while preserving structural and dimensional integrity (>80% volume retention). Importantly, these materials occupy a previously inaccessible region in the density‐retention landscape, showcasing low‐density porous carbons with minimal shrinkage (<20 vol%). This work presents a versatile design platform for the macroscale fabrication of structurally and dimensionally stable 3D porous carbons, allowing deterministic control over density across a wide range.

Understanding Capacity Accessibility in Polymer-Based Redox Targeting Flow Batteries

ECS Meeting Abstracts · 2025-11-24

Solid liquid flow electrochemistry is gaining traction in technologies ranging from CO 2 capture to fuel cells. A promising application is redox targeting flow batteries, where solid materials, particularly redox active polymers, serve as the primary energy storage medium and are charged via redox mediators. These architectures are increasingly explored as a strategy to overcome the historically low energy density of flow battery systems. A key challenge is achieving high capacity utilization of the solid polymeric materials in the storage tank. Our work focuses on identifying conditions that enable high capacity accessibility in a model system based on ferrocene and using this understanding to inform future designs. We investigate two systems: one with a single redox mediator and another with two mediators facilitating charge transfer. For each, we experimentally quantify the mediator’s ability to access the solid phase and validate a simple thermodynamic model based on the Nernst-Equation. This analysis provides design insights for mediator selection, such as voltage offset and state of charge management, and confirms the model’s applicability under relevant operating flow cell conditions.

Hierarchical Tissue-like Material from Nematic Synthetic Colloids with Adaptive Internal Microstructures

ChemRxiv · 2025-12-22

In living organisms, individual cells can evolve their cytoskeletal structures and adapt their shape and stiffness to the mechanical environment, a capability that is critical for the formation of collective order in tissues. Inspired by this behavior, we design a colloid-based material in which collective order arises from mechanical adaptation within individual elastomeric liquid crystalline microparticles. Through simulation and experiment, we reveal that the ordering within individual particles evolves and differentiates in response to mechanical loading and geometric confinement. We then examine emergent collective behaviors by jamming the particles into assemblies that exhibit pronounced particle-particle contacts. We find that distinct topological defects with unusual topological charges derive from geometric confinement in 2D. In 3D, colloidal films display high stiffness and a suppressed nematic-to-isotropic transition. Together, this work offers a platform for the design of hierarchically ordered materials with adaptive properties that reflect key aspects of living organisms.

Short-Time Relaxation and Anomalous Diffusion in Dynamic Covalent Networks

ACS Macro Letters · 2025-09-09 · 2 citations

Introducing dynamic covalent chemistries into polymer networks allows access to complex linear viscoelasticity, owing to the reversible nature of the dynamic bonds. While this macroscopic mechanical behavior is influenced by the dynamic exchange of these chemistries, connecting the microscopic dynamics to the bulk properties is hindered by the time scale conventional techniques can observe. Here, light scattering passive microrheology is applied to probe short-time dynamics of dynamic covalent networks that consist of telechelic benzalcyanoacetate (BCA) Michael acceptors and thiol-functionalized cross-linkers. The mean-squared displacement of probe particles embedded in the dynamic covalent networks is analyzed to explore the microscopic short-term dynamics and relaxation behavior. A series of Michael acceptors with varying equilibrium constants when reacted with thiols confirms that the observed microscopic relaxation arises from the bond dissociation. The data suggest the particles undergo local superdiffusivity, suggesting that bond breaking and bond reformation exert external force on the probe particles driving this non-Brownian anomalous diffusion.

Molecular Simulation-Driven Design of Functionalized Cellulose Nanocrystals toward Improved Dispersibility and Stabilization in Ethanol

Langmuir · 2025-06-03

Cellulose nanocrystals (CNCs) are commonly produced with carboxylic acid surface functionalities, as it aids the dispersion in aqueous solvents. However, the carboxylic acid-functionalized CNCs (CNC-COOHs) exhibit poor dispersibility in nonaqueous solvents due to their self-aggregation, limiting their integration into many biosourced solvent-based technologies, such as inkjet printing, spin-coating, etc. Aimed at improving the dispersibility of CNCs in nonaqueous solvents, molecular dynamics simulations were performed to study the underlying reasons for the low dispersibility of CNC-COOHs in biosourced ethanol and investigate how surface functionalization impacts their self-aggregation tendency in this solvent. The potential of mean force (PMF) calculations revealed that the aggregation of CNC-COOHs through their hydrophilic surfaces drives their low dispersibility in ethanol and that the functionalization of CNC-COOHs with alkyl groups (CNC-COOH-alkyl, with alkyl being ethyl, butyl, hexyl, and octyl) reduces their aggregation tendency. The lower binding tendency of the alkylated CNCs than CNC-COOHs stems from a higher binding entropy loss and a lower attraction between their surfaces, as alkylation increases the distance between bound CNCs. The higher binding entropy loss of CNC-COOH-alkyls is attributed to alkyl groups' reduced degrees of freedom at the contact point between CNC-COOH-alkyls. As a result, the highest dispersibility can be achieved when the CNC-COOHs are functionalized with the longer alkyl groups, i.e., hexyl and octyl. PMF-derived binding free energy values predict the dispersibility trend as CNC-COOH-octyl ≈ CNC-COOH-hexyl > CNC-COOH-butyl > CNC-COOH-ethyl > CNC-COOH. Experimental tests for synthesized CNC-COOH-alkyls with ethyl, butyl, and hexyl groups confirmed simulation predictions, wherein the increasing size of the alkyl chain increased CNC dispersibility. CNC-COOH-hexyl dispersed well in ethanol and remained stable for 1 day. The findings of this research enhanced our understanding of how functionalization of the CNCs improves their stability in biosourced nonaqueous solvents such as ethanol and opens the avenue for their integration in biosourced solvent-based technologies.

Real-Time Phosphate Monitoring via Plant-derived Graphene Ink FET Sensors Integrated with Deep Learning

2025-03-27

Real-time monitoring of plant nutrient levels, particularly phosphate, is essential for optimizing plant growth and addressing nutrient imbalances in precision agriculture. Conventional sensors mostly suffer from poor stability, reproducibility, matrix effects, and high costs, limiting their scalability and practical application. To overcome these challenges, a deep learning (DL)-integrated remote-gate field-effect transistor (FET) sensor utilizing a plant-derived graphene electrode is introduced for enhanced performance and reliability. These solution-processed graphene electrodes composed of cellulose nanocrystals (CNCs) from plant fibers are functionalized with phosphate-capturing ferritin and serve as the sensing surface, capacitively coupled to a commercial n-type FET, addressing device variability issues. DL integration significantly improved accuracy, enabling robust and precise phosphate detection. The sensor demonstrates a sensitivity of 14.1 mV/dec after the pH correction, a coefficient of variation (CV) of responses below 5%, and a 1 ng/mL detection limit. As a proof-of-concept, phosphate levels in Hoagland solution, a standard plant nutrient medium, were monitored, achieving an r2 of 0.951 and a CV of 5.39%. A handheld prototype system further demonstrates its potential for on-site continuous monitoring. This sustainable and cost-effective approach provides a scalable solution for real-time phosphate detection with high sensitivity and reproducibility, meeting agricultural demands.