Biomass carbon mining to develop nature-inspired materials for a circular economy.

A transition from a linear to a circular economy is the only alternative to reduce current pressures in natural resources. Our society must redefine our material sources, rethink our supply chains, improve our waste management, and redesign materials and products. Valorizing extensively available biomass wastes, as new carbon mines, and developing biobased materials that mimic nature's efficiency and wasteless procedures are the most promising avenues to achieve technical solutions for the global challenges ahead. Advances in materials processing, and characterization, as well as the rise of artificial intelligence, and machine learning, are supporting this transition to a new materials' mining. Location, cultural, and social aspects are also factors to consider. This perspective discusses new alternatives for carbon mining in biomass wastes, the valorization of biomass using available processing techniques, and the implementation of computational modeling, artificial intelligence, and machine learning to accelerate material's development and process engineering.

Biorefineries: Achievements and challenges for a bio-based economy.

Climate change, socioeconomical pressures, and new policy and legislation are driving a decarbonization process across industries, with a critical shift from a fossil-based economy toward a biomass-based one. This new paradigm implies not only a gradual phasing out of fossil fuels as a source of energy but also a move away from crude oil as a source of platform chemicals, polymers, drugs, solvents and many other critical materials, and consumer goods that are ubiquitous in our everyday life. If we are to achieve the United Nations' Sustainable Development Goals, crude oil must be substituted by renewable sources, and in this evolution, biorefineries arise as the critical alternative to traditional refineries for producing fuels, chemical building blocks, and materials out of non-edible biomass and biomass waste. State-of-the-art biorefineries already produce cost-competitive chemicals and materials, but other products remain challenging from the economic point of view, or their scaled-up production processes are still not sufficiently developed. In particular, lignin's depolymerization is a required milestone for the success of integrated biorefineries, and better catalysts and processes must be improved to prepare bio-based aromatic simple molecules. This review summarizes current challenges in biorefinery systems, while it suggests possible directions and goals for sustainable development in the years to come.

Biobased Spore Microcapsules for Asphalt Self-Healing.

Asphalt pavements and bituminous composites are majorly damaged by bitumen aging and fatigue cracking by traffic load. To add, maintenance and reparation of asphalt pavements is expensive and also releases significant amounts of greenhouse gases. These issues can be mitigated by promoting asphalt self-healing mechanisms with encapsulated rejuvenators. The ability of the required microcapsules to be resilient against high temperatures, oxidation, and mechanical stress is essential to promote such self-healing behavior without compromising the field performance of the asphalt pavement. This work proposes, for the first time, the use of extremely resistant biobased spores for the encapsulation of recycled oil-based rejuvenators to produce more resilient self-healing pavements. Spore encapsulants were obtained from natural spores (Lycopodium clavatum) by applying different chemical treatments, which enabled the selection of the best morphologically intact and clean spore encapsulant. The physical, morphological, and physicochemical changes were examined using fluorescence images, ATR-FTIR, SEM, size distribution, XRD, TGA and DSC analyses. Sunflower oil was used as the encapsulated rejuvenator with an optimal sol colloidal mixture for sporopollenin-oil of 1:5 (gram-to-gram). Vacuum, passive, and centrifugal encapsulation techniques were tested for loading the rejuvenator inside the clean spores and for selecting the best encapsulation technology. The encapsulation efficiency and the profiles of the accelerated release of the rejuvenator from the loaded spores over time were studied, and these processes were visualized with optical and inverted fluorescence microscopy. Vacuum encapsulation was identified as the best loading technique with an encapsulation efficiency of 93.02 ± 3.71%. The rejuvenator was successfully encapsulated into the clean spores, as observed by optical and SEM morphologies. In agreement with the TGA and DSC, the microcapsules were stable up to 204 °C. Finally, a self-healing test was conducted through fluorescence tests to demonstrate how these biobased spore microcapsules completely heal a crack into an aged bitumen sample in 50 min.

Socially-Directed Development of Materials for Structural Color.

Advancing a socially-directed approach to materials research and development is an imperative to address contemporary challenges and mitigate future detrimental environmental and social impacts. This paper reviews, synergizes, and identifies cross-disciplinary opportunities at the intersection of materials science and engineering with humanistic social sciences fields. Such integrated knowledge and methodologies foster a contextual understanding of materials technologies embedded within, and impacting broader societal systems, thus informing decision making upstream and throughout the entire research and development process toward more socially responsible outcomes. Technological advances in the development of structural color, which arises due to the incoherent and coherent scattering of micro-and nanoscale features and possesses a vast design space, are considered in this context. Specific areas of discussion include material culture, narratives, and visual perception, material waste and use, environmental and social life cycle assessment, and stakeholder and community engagement. A case study of the technical and social implications of bio-based cellulose (as a source for structurally colored products) is provided. Socially-directed research and development of materials for structural color hold significant capacity for improved planetary and societal impact across industries such as aerospace, consumer products, displays and sensors, paints and dyes, and food and agriculture.

Wearable Light Sensors Based on Unique Features of a Natural Biochrome.

Overexposure to complete solar radiation (combined ultraviolet, visible, and infrared) is correlated with several harmful biological consequences including hyperpigmentation, skin cancer, eye damage, and immune suppression. With limited effective therapeutic options available for these conditions, significant efforts have been directed toward promoting preventative habits. Recently, wearable solar radiometers have emerged as practical tools for managing personal exposure to sunlight. However, designing simple and inexpensive sensors that can measure energy across multiple spectral regions without incorporating electronic components remains challenging, largely due to inherent spectral limitations of photoresponsive indicators. In this work, we report the design, fabrication, and characterization of wearable radiation sensors that leverage an unexpected feature of a natural biochrome, xanthommatin-its innate sensitivity to both ultraviolet and visible through near-infrared radiation. We found that xanthommatin-based sensors undergo a visible shift from yellow to red in the presence of complete sunlight. This color change is driven by intrinsic photoreduction of the molecule, which we investigated using computational modeling and supplemented by radiation-driven formation of complementary reducing agents. These sensors are responsive to dermatologically relevant doses of erythemally weighted radiation, as well as cumulative doses of high-energy ultraviolet radiation used for germicidal sterilization. We incorporated these miniature sensors into pressure-activated microfluidic systems to illustrate on-demand activation of a wearable and mountable form factor. When taken together, our findings encompass an important advancement toward accessible, quantitative measurements of UVC and complete solar radiation for a variety of use cases.

Conductive Silk-Based Composites Using Biobased Carbon Materials.

There is great interest in developing conductive biomaterials for the manufacturing of sensors or flexible electronics with applications in healthcare, tracking human motion, or in situ strain measurements. These biomaterials aim to overcome the mismatch in mechanical properties at the interface between typical rigid semiconductor sensors and soft, often uneven biological surfaces or tissues for in vivo and ex vivo applications. Here, the use of biobased carbons to fabricate conductive, highly stretchable, flexible, and biocompatible silk-based composite biomaterials is demonstrated. Biobased carbons are synthesized via hydrothermal processing, an aqueous thermochemical method that converts biomass into a carbonaceous material that can be applied upon activation as conductive filler in composite biomaterials. Experimental synthesis and full-atomistic molecular dynamics modeling are combined to synthesize and characterize these conductive composite biomaterials, made entirely from renewable sources and with promising applications in fields like biomedicine, energy, and electronics.

A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence.

We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The sonification method proposed here uses the normal mode vibrations of the amino acid building blocks of proteins to compute an audible representation of each of the 20 natural amino acids, which is fully defined by the overlay of its respective natural vibrations. The vibrational frequencies are transposed to the audible spectrum following the musical concept of transpositional equivalence, playing or writing music in a way that makes it sound higher or lower in pitch while retaining the relationships between tones or chords played. This transposition method ensures that the relative values of the vibrational frequencies within each amino acid and among different amino acids are retained. The characteristic frequency spectrum and sound associated with each of the amino acids represents a type of musical scale that consists of 20 tones, the "amino acid scale". To create a playable instrument, each tone associated with the amino acids is assigned to a specific key on a piano roll, which allows us to map the sequence of amino acids in proteins into a musical score. To reflect higher-order structural details of proteins, the volume and duration of the notes associated with each amino acid are defined by the secondary structure of proteins, computed using DSSP and thereby introducing musical rhythm. We then train a recurrent neural network based on a large set of musical scores generated by this sonification method and use AI to generate musical compositions, capturing the innate relationships between amino acid sequence and protein structure. We then translate the de novo musical data generated by AI into protein sequences, thereby obtaining de novo protein designs that feature specific design characteristics. We illustrate the approach in several examples that reflect the sonification of protein sequences, including multihour audible representations of natural proteins and protein-based musical compositions solely generated by AI. The approach proposed here may provide an avenue for understanding sequence patterns, variations, and mutations and offers an outreach mechanism to explain the significance of protein sequences. The method may also offer insight into protein folding and understanding the context of the amino acid sequence in defining the secondary and higher-order folded structure of proteins and could hence be used to detect the effects of mutations through sound.

Dynamic pigmentary and structural coloration within cephalopod chromatophore organs.

Chromatophore organs in cephalopod skin are known to produce ultra-fast changes in appearance for camouflage and communication. Light-scattering pigment granules within chromatocytes have been presumed to be the sole source of coloration in these complex organs. We report the discovery of structural coloration emanating in precise register with expanded pigmented chromatocytes. Concurrently, using an annotated squid chromatophore proteome together with microscopy, we identify a likely biochemical component of this reflective coloration as reflectin proteins distributed in sheath cells that envelop each chromatocyte. Additionally, within the chromatocytes, where the pigment resides in nanostructured granules, we find the lens protein Ω- crystallin interfacing tightly with pigment molecules. These findings offer fresh perspectives on the intricate biophotonic interplay between pigmentary and structural coloration elements tightly co-located within the same dynamic flexible organ - a feature that may help inspire the development of new classes of engineered materials that change color and pattern.

Paraffin-enabled graphene transfer.

The performance and reliability of large-area graphene grown by chemical vapor deposition are often limited by the presence of wrinkles and the transfer-process-induced polymer residue. Here, we report a transfer approach using paraffin as a support layer, whose thermal properties, low chemical reactivity and non-covalent affinity to graphene enable transfer of wrinkle-reduced and clean large-area graphene. The paraffin-transferred graphene has smooth morphology and high electrical reliability with uniform sheet resistance with ~1% deviation over a centimeter-scale area. Electronic devices fabricated on such smooth graphene exhibit electrical performance approaching that of intrinsic graphene with small Dirac points and high carrier mobility (hole mobility = 14,215 cm2 V-1 s-1; electron mobility = 7438 cm2 V-1 s-1), without the need of further annealing treatment. The paraffin-enabled transfer process could open realms for the development of high-performance ubiquitous electronics based on large-area two-dimensional materials.

Multiscale Design of Graphyne-Based Materials for High-Performance Separation Membranes.

By varying the number of acetylenic linkages connecting aromatic rings, a new family of atomically thin graph-n-yne materials can be designed and synthesized. Generating immense scientific interest due to its structural diversity and excellent physical properties, graph-n-yne has opened new avenues toward numerous promising engineering applications, especially for separation membranes with precise pore sizes. Having these tunable pore sizes in combination with their excellent mechanical strength to withstand high pressures, free-standing graph-n-yne is theoretically posited to be an outstanding membrane material for separating or purifying mixtures of either gases or liquids, rivaling or even dramatically exceeding the capabilities of current, state-of-art separation membranes. Computational modeling and simulations play an integral role in the bottom-up design and characterization of these graph-n-yne materials. Thus, here, the state of the art in modeling α-, ß-, γ-, δ-, and 6,6,12-graphyne nanosheets for synthesizing graph-2-yne materials and 3D architectures thereof is discussed. Different synthesis methods are described and a broad overview of computational characterizations of graph-n-yne's electrical, chemical, and thermal properties is provided. Furthermore, a series of in-depth computational studies that delve into the specifics of graph-n-yne's mechanical strength and porosity, which confer superior performance for separation and desalination membranes, are reviewed.

Multiscale Modeling of Silk and Silk-Based Biomaterials-A Review.

Silk embodies outstanding material properties and biologically relevant functions achieved through a delicate hierarchical structure. It can be used to create high-performance, multifunctional, and biocompatible materials through mild processes and careful rational material designs. To achieve this goal, computational modeling has proven to be a powerful platform to unravel the causes of the excellent mechanical properties of silk, to predict the properties of the biomaterials derived thereof, and to assist in devising new manufacturing strategies. Fine-scale modeling has been done mainly through all-atom and coarse-grained molecular dynamics simulations, which offer a bottom-up description of silk. In this work, a selection of relevant contributions of computational modeling is reviewed to understand the properties of natural silk, and to the design of silk-based materials, especially combined with experimental methods. Future research directions are also pointed out, including approaches such as 3D printing and machine learning, that may enable a high throughput design and manufacturing of silk-based biomaterials.

The Rise of Hierarchical Nanostructured Materials from Renewable Sources: Learning from Nature.

Mimicking Nature implies the use of bio-inspired hierarchical designs to manufacture nanostructured materials. Such materials should be produced from sustainable sources ( e.g., biomass) and through simple processes that use mild conditions, enabling sustainable solutions. The combination of different types of nanomaterials and the implementation of different features at different length scales can provide synthetic hierarchical nanostructures that mimic natural materials, outperforming the properties of their constitutive building blocks. Taking recent developments in flow-assisted assembly of nanocellulose crystals as a starting point, we review the state of the art and provide future perspectives on the manufacture of hierarchical nanostructured materials from sustainable sources, assembly techniques, and potential applications.

Interlocking Friction Governs the Mechanical Fracture of Bilayer MoS2.

A molybdenum disulfide (MoS2) layered system is a two-dimensional (2D) material, which is expected to provide the next generation of electronic devices together with graphene and other 2D materials. Due to its significance for future electronics applications, gaining a deep insight into the fundamental mechanisms upon MoS2 fracture is crucial to prevent mechanical failure toward reliable applications. Here, we report direct experimental observation and atomic modeling of the complex failure behaviors of bilayer MoS2 originating from highly variable interlayer frictions, elucidated with in situ transmission electron microscopy and large-scale reactive molecular dynamics simulations. Our results provide a systematic understanding of the effects that different stacking and loading conditions have on the failure mechanisms and crack-tip behaviors in the bilayer MoS2 systems. Our findings unveil essential properties in fracture of this 2D material and provide mechanistic insight into its mechanical failure.

Multiscale modeling of keratin, collagen, elastin and related human diseases: Perspectives from atomistic to coarse-grained molecular dynamics simulations.

Scleroproteins are an important category of proteins within the human body that adopt filamentous, elongated conformations in contrast with typical globular proteins. These include keratin, collagen, and elastin, which often serve a common mechanical function in structural support of cells and tissues. Genetic mutations alter these proteins, disrupting their functions and causing diseases. Computational characterization of these mutations has proven to be extremely valuable in identifying the intricate structure-function relationships of scleroproteins from the molecular scale up, especially if combined with multiscale experimental analysis and the synthesis of model proteins to test specific structure-function relationships. In this work, we review numerous critical diseases that are related to keratin, collagen, and elastin, and through several case studies, we propose ways of extensively utilizing multiscale modeling, from atomistic to coarse-grained molecular dynamics simulations, to uncover the molecular origins for some of these diseases and to aid in the development of novel cures and therapies. As case studies, we examine the effects of the genetic disease Epidermolytic Hyperkeratosis (EHK) on the structure and aggregation of keratins 1 and 10; we propose models to understand the diseases of Osteogenesis Imperfecta (OI) and Alport syndrome (AS) that affect the mechanical and aggregation properties of collagen; and we develop atomistic molecular dynamics and elastic network models of elastin to determine the role of mutations in diseases such as Cutis Laxa and Supravalvular Aortic Stenosis on elastin's structure and molecular conformational motions and implications for assembly.

Materials-by-Design: Computation, Synthesis, and Characterization from Atoms to Structures.

In the 50 years that succeeded Richard Feynman's exposition of the idea that there is "plenty of room at the bottom" for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Polydopamine and eumelanin molecular structures investigated with ab initio calculations.

A set of computational methods that contains a brute-force algorithmic generation of chemical isomers, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations is reported and applied to investigate nearly 3000 probable molecular structures of polydopamine (PDA) and eumelanin. All probable early-polymerized 5,6-dihydroxyindole (DHI) oligomers, ranging from dimers to tetramers, have been systematically analyzed to find the most stable geometry connections as well as to propose a set of molecular models that represents the chemically diverse nature of PDA and eumelanin. Our results indicate that more planar oligomers have a tendency to be more stable. This finding is in good agreement with recent experimental observations, which suggested that PDA and eumelanin are composed of nearly planar oligomers that appear to be stacked together via π-π interactions to form graphite-like layered aggregates. We also show that there is a group of tetramers notably more stable than the others, implying that even though there is an inherent chemical diversity in PDA and eumelanin, the molecular structures of the majority of the species are quite repetitive. Our results also suggest that larger oligomers are less likely to form. This observation is also consistent with experimental measurements, supporting the existence of small oligomers instead of large polymers as main components of PDA and eumelanin. In summary, this work brings an insight into the controversial structure of PDA and eumelanin, explaining some of the most important structural features, and providing a set of molecular models for more accurate modeling of eumelanin-like materials.

The role of weak interactions in lignin polymerization.

Lignin is the most abundant natural polymer composed by aromatic moieties. Its chemical composition and its abundance have focused efforts to unlock its potential as a source of aromatic compounds for many years. The lack of a proper way for lignin de-polymerization has hampered its success as a natural solution for commodity aromatic chemicals, which is also due to the lack of understanding of the underlying mechanisms of lignin polymerization. A fuller fundamental understanding of polymerization mechanisms could lead to improvements in de-polymerization strategies, and therefore a proper methodology and a predictive theoretical framework are required for such purpose. This work presents a complete computational study on some of the key steps of lignin polymerization mechanisms. Density functional theory (DFT) calculations have been performed to evaluate the most appropriate methodology and to compute the chemical structures and reaction enthalpies for the monolignol dimerization, the simplest key step that controls the polymerization. Quantum theory of atoms in molecules (QTAIM) has been applied to understand the coupling reaction mechanisms, for which the radical species and transition states (TSs) involved have been characterized. The coupling that leads to the formation of the ß-O-4 linkage has been theoretically reproduced according to proposed mechanisms, for which weak interactions have been found to play a key role in the arrangement of reactants. The hydrogen bond formed between the oxygen of the phenoxy radical, and the alcohol of the aliphatic chain, together with the interaction between aromatic rings, locates the reactants in a position that favors such ß-O-4 linkage. Graphical Abstract QTAIM analysis of the complex between coumaryl and coniferyl alcohols. It emphasizes the importance of weak interactions during the formation of beta-O-4 linkages in the polymerization of lignin.

Ion Effect and Metal-Coordinated Cross-Linking for Multiscale Design of Nereis Jaw Inspired Mechanomutable Materials.

The Nvjp-1 protein is a key component in the jaws of Nereis virens, a species of marine worm. It contains over 25 mol % of histidine, which is believed to play a key role in the metal-coordinated cross-linking responsible for the structural stability and exceptional mechanical performance of the worm jaw. Understanding the nanoscale mechanism behind this cross-linking and its pathway in affecting the macroscopic mechanical behavior of the material is crucial to develop bioinspired mechanomutable materials based on Nvjp-1. Here, we use a combination of multiscale modeling and experimental synthesis to understand the behavior of this heterologous-expressed protein from the nano- to the macroscale. We have built a bottom-up molecular-based model, which includes electronic-based density functional theory calculations, atomistic simulation of the nanoscale properties with replica exchange molecular dynamics, and an elastic network model for describing the macroscale behavior at different pHs. This multiscale modeling supports the experimental synthesis of a photo-cross-linked Nvjp-1 hydrogel by proving both the nanoscale mechanisms and mechanical behavior predictions. Our theoretical results agree well with the experimental observations, showing that Nvjp-1 forms a more compact structure in the presence of Zn2+ ions with a suitable pH environment, leading to the formation of more stable intramolecular metal-coordinated cross-links. These metal-coordinated cross-links induce nanoscale aggregation of Nvjp-1, which is responsible for the hydrogel contraction observed in experiments and predicted by the model.