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Abstract Designing high-performance composites requires exploring vast microstructural design spaces, which is computationally expensive for bicontinuous architecture using traditional simulations. We present an end-to-end artificial intelligence framework combining a denoising diffusion probabilistic model (DDPM) and a multimodal surrogate predictor to jointly generate and evaluate composite microstructures. Trained on 2000 phase-field-generated binary composites (0.55:0.45 stiff-to-soft ratio) with simulated stress fields, the DDPM co-generates realistic configurations and von Mises responses. From each stress map, 28 features and image embeddings feed a multimodal neural network that predicts Young’s modulus and ultimate tensile strength (R² = 0.95 and 0.75). This generative–predictive pipeline accelerates composite design and inverse discovery. Graphical abstract 

Abstract Bamboo culm has been widely used in engineering for its high strength, lightweight, and low cost. Its outermost epidermis is a smooth and dense layer that contains cellulose, silica particles, and stomata and acts as a water and mechanical barrier. Recent experimental studies have shown that the layer has a higher mechanical strength than other inside regions. Still, the mechanism is unclear, especially for how the low silica concentration (<10%) can effectively reinforce the layer and prevent the inner fibers from splitting. Here, theoretical analysis is combined with experimental imaging and 3D printing to investigate the effect of the distribution of silica particles on composite mechanics. The anisotropic partial distribution function of silica particles in bamboo skin yields higher toughness (>10%) than randomly distributed particles. A generative artificial intelligence (AI) model inspired by bamboo epidermis is developed to generate particle‐reinforced composites. Besides the visual similarity, it is found that the samples by the generative model show failure processes and fracture toughness identical to the actual bamboo epidermis. This work reveals the micromechanics of the bamboo epidermis. It illustrates that generative AI can help design bio‐inspired composites of a complex structure that cannot be uniformly represented by a simple building block or optimized around local boundaries. It expands the design space of particle‐reinforced composites for enhanced toughness modulus, offering advantages in industries where mechanical reliability is critical. 

AbstractMycelium is crucial in decomposing biomass and cycling nutrients in nature. While various environmental factors can influence mycelium growth, the role of substrate mechanics is not yet clear. In this study, we investigate the effect of substrate stiffness on mycelium growth. We prepared agar substrates of different concentrations to grow the mycelium, but kept other environmental and chemical conditions consistent. We made a time-lapse recording of the growing history with minimum interruption. We repeated our tests for different species. Our results generally support that mycelium grows faster on a stiffer substrate,Ganoderma lucidumgives the highest growth rate andPleurotus eryngiiis most sensitive to substrate stiffness. We combined experimental characterization and computational simulation to investigate the mechanism and discovered that mycelium concentrates on the surface of a rigid substrate, but penetrates the soft one. Our Monte Carlo simulations illustrate that such a penetration allows mycelium to grow in the three-dimensional space, but effectively slows down the surface occupation speed. Our study provides insights into fungal growth and reveals that the mycelium growth rate can be tuned through substrate stiffness, thus reducing the time for producing mycelium-based composites. Impact statementWe used agar substrates and tuned its stiffness to culture mycelium and compared tune its stiffness to culture mycelium and compare its growth in a well-controlled condition. Our results revealed that mycelium grows faster on stiffer substrates, thus fully occupying the petri dish surface more quickly. We repeated our study several times by testing four species,P. eryngii,G. lucidum,Trametes versicolor,and Flammulina velutipes,and the stiffest substrate always gives the highest mean growing rate than others. TheG. lucidumshows the highest spreading rate that is obtained on the stiffest substrate as 39.1 ± 2.0 mm²/h. We found that the mycelium on a soft substrate will grow into the substrate instead of spreading on the stiffer surface. Our Monte Carlo simulations further show that once the fibers grow into a three-dimensional substrate, its growth is slower than growing on a two-dimensional surface, providing a microscopic mechanism of the substrate stiffness effect. This study’s analysis of how substrate stiffness impacts mycelium growth is new, bridging a critical knowledge gap in understanding the relationship between substrate mechanics and fungal ecology. The knowledge from this study has a potential in accelerating sustainable manufacturing of mycelium-based composite by adjusting substrate mechanics. Graphical Abstract 

Abstract Cis-peptide bonds are rare in proteins, and building blocks less favorable to the trans-conformer have been considered destabilizing. Although proline tolerates the cis-conformer modestly among all amino acids, for collagen, the most prevalent proline-abundant protein, all peptide bonds must be trans to form its hallmark triple-helix structure. Here, using host-guest collagen mimetic peptides (CMPs), we discover that surprisingly, even the cis-enforcing peptoid residues (N-substituted glycines) form stable triple-helices. Our interrogations establish that these peptoid residues entropically stabilize the triple-helix by pre-organizing individual peptides into a polyproline-II helix. Moreover, noting that the cis-demanding peptoid residues drastically reduce the folding rate, we design a CMP whose triple-helix formation can be controlled by peptoid cis-trans isomerization, enabling direct targeting of fibrotic remodeling in myocardial infarction in vivo. These findings elucidate the principles of peptoid cis-trans isomerization in protein folding and showcase the exploitation of cis-amide-favoring residues in building programmable and functional peptidomimetics. 

In response to the urgent need for low‐carbon and energy‐efficient materials in the built environment, mycelium‐bound composites (MBCs), produced through fungal mycelium growth on organic waste, have emerged in the building market as sustainable alternatives to petroleum‐derived insulation and particleboards. However, the rough, hydrophobic mycelium surfaces of MBCs may pose practical challenges for installation, such as heat loss at panel–panel interfacial joints and limited compatibility with conventional fastening and adhesives. A biocompatible adhesive is therefore needed for seamless assemblies. Fungal biowelding, the innate ability of mycelium to grow across interfaces and bond materials together, holds promise as a biological interfacial adhesive. This review elucidates the interfacial bonding mechanisms of mycelium and examines how biowelding behaviors govern the fabrication of sustainable materials and engineered living composite systems. Future strategies for optimizing mycelium‐mediated adhesion and the potential use of biowelding as a bioadhesive are further discussed in the building and wood industries. By leveraging the adaptive growth, interfacial bonding, and biodegradability of mycelium, biowelding offers a regenerative adhesive solution toward circular construction systems. 

Frontspiece Cover, Adv. Mater. 22/2025 

We synthesized and characterized the advanced multifunctional features of mycelium–coir-based composites as a replacement for fossil-based foams used in building insulation.