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.

The nature of the silicaphilic fluorescence of PDMPO.

PDMPO (2-(4-pyridyl)-5-((4-(2-dimethylaminoethylaminocarbamoyl)methoxy)phenyl)oxazole), has unique silica specific fluorescence and is used in biology to understand biosilicification. This 'silicaphilic' fluorescence is not well understood nor is the response to local environmental variables like solvent and pH. We investigated PDMPO in a range of environments: using UV-vis and fluorescence spectroscopy supported by computational data, (SPARC, molecular dynamics simulations, density functional theory calculations), dynamic light scattering and zeta potential measurements to understand the PDMPO-silica interaction. From absorption data, PDMPO exhibited a pKa of 4.20 for PDMPOH2(2+) to PDMPOH(+). Fluorescence emission measurements revealed large shifts in excited state pKa* values with different behaviour when bound to silica (pKa* of 10.4). PDMPO bound to silica particles is located in the Stern layer with the dye exhibiting pH dependent depolarising motion. In aqueous solution, PDMPO showed strong chromaticity with correlation between the maximum emission wavelength for PDMPOH(+)* and dielectric constant (4.8-80). Additional chromatic effects were attributed to changes in solvent accessible surface area. Chromatic effects were also observed for silica bound dye which allow its use as a direct probe of bulk pH over a range far in excess of what is possible for the dye alone (3-5.2). The unique combination of chromaticity and excited state dynamics allows PDMPO to monitor pH from 3 to 13 while also reporting on surface environment opening a new frontier in the quantitative understanding of (bio)silicification.

Integrating 31P DOSY NMR spectroscopy and molecular mechanics as a powerful tool for unraveling the chemical structures of polyoxomolybdate-based amphiphilic nanohybrids in aqueous solution.

Novel organic-inorganic hybrids of various sizes were generated by reaction of 1,8-octanediphosphonic acid (ODP) and (NH4)6Mo7O24 in aqueous solution. The formation of rodlike hybrids with variable numbers of covalently bound ODP and polyoxomolybdate (POM) units can be tuned as a function of increasing (NH4)6Mo7O24 concentration at fixed ODP concentration. The chemical structure of the ODP/POM hybrids was characterized by (1)H, (31)P, and (95)Mo NMR spectroscopy. Heteronuclear (31)P DOSY (diffusion- ordered NMR spectroscopy) and molecular mechanics (MM) calculations were applied to determine the size and shape of the nanosized hybrids generated at various ODP/POM ratios. For this purpose, the structures of ODP/POM hybrids with variable numbers of ODP and POM units were optimized by MM and then approximated as cylinder-shaped objects by using a recently described mathematical algorithm. The thus-obtained cylinder length and diameter were further used to calculate the expected diffusion coefficients of the ODP/POM hybrids. Comparison of the calculated and experimentally determined diffusion coefficients led to the most probable ODP/POM hybrid length for each sample composition. The (31)P DOSY results show that the length of the hybrids increases with increasing POM concentration and reaches a maximum corresponding to an average of 8 ODP/7 POM units per chain at a sample composition of 20 mM ODP and 14 mM POM. With excess POM, above the latter concentration, the formation of shorter-chain hybrids terminated by Mo7 clusters at one or both ends was evidenced on further increasing the POM concentration. The results demonstrate that the combination of (31)P DOSY and MM, although virtually unexplored in POM chemistry, is a powerful innovative strategy for the detailed characterization of nanosized organic-inorganic POM-based hybrids in solution.

Understanding the fundamental role of π/π, σ/σ, and σ/π dispersion interactions in shaping carbon-based materials.

Noncovalent interactions involving aromatic rings, such as π-stacking and CH/π interactions, are central to many areas of modern chemistry. However, recent studies proved that aromaticity is not required for stacking interactions, since similar interaction energies were computed for several aromatic and aliphatic dimers. Herein, the nature and origin of π/π, σ/σ, and σ/π dispersion interactions has been investigated by using dispersion-corrected density functional theory, energy decomposition analysis, and the recently developed noncovalent interaction (NCI) method. Our analysis shows that π/π and σ/σ stacking interactions are equally important for the benzene and cyclohexane dimers, explaining why both compounds have similar boiling points. Also, similar dispersion forces are found in the benzene⋅⋅⋅methane and cyclohexane⋅⋅⋅methane complexes. However, for systems larger than naphthalene, there are enhanced stacking interactions in the aromatic dimers adopting a parallel-displaced configuration compared to the analogous saturated systems. Although dispersion plays a decisive role in stabilizing all the complexes, the origin of the π/π, σ/σ, and σ/π interactions is different. The NCI method reveals that the dispersion interactions between the hydrogen atoms are responsible for the surprisingly strong aliphatic interactions. Moreover, whereas σ/σ and σ/π interactions are local, the π/π stacking are inherently delocalized, which give rise to a non-additive effect. These new types of dispersion interactions between saturated groups can be exploited in the rational design of novel carbon materials.

Computationally-accelerated prediction of polyester-melamine coatings degradation to design sustainable organically-coated steels for outdoor applications.

This work implements computational chemistry as a screening tool to aid in the coating and resin formulation process. Conceptual Density Functional theory (DFT) reactivity descriptors like the global chemical hardness and the dual descriptor Fukui function identify the tendency of polyester-melamine coatings to undergo electrophilic and nucleophilic attack during weathering exposure. Coatings were subjected to natural and accelerated weathering tests, with periodic infrared spectroscopy, colour, and gloss measurements to assess for the degree of changes brought about through photodegradation. It was found that the number of attack sites in the atomistic models, when weighted as a function of the polyester : crosslinker ratio, effectively ranked the degradation of different coating systems upon weathering. This ranking matched the performance of the coatings subjected to both accelerated and natural weathering, showing affinity with naturally weathered samples, and matching in all areas. The results were shown to demonstrate significant correlation, being over R 2 = 0.8 for 7 of the 8 measured areas, and greater than R 2 = 0.9 for 6 compared areas. Comparison of computationally derived and experimentally acquired results showed that the performance of naturally weathered samples was matched across all areas by the computational rankings, showing superior correlation than that observed between natural and accelerated weathering tests. This indicates that the method utilised within this work provides a novel, cost-effective alternative to evaluate the projected performance of selected coatings, while enabling a computationally accelerated platform for more sustainable low-degradation coatings without the requirement of long-term weathering tests.

Tuning aromaticity patterns and electronic properties of armchair graphene nanoribbons with chemical edge functionalisation.

Tuning the band gap of graphene nanoribbons by chemical edge functionalisation is a promising approach towards future electronic devices based on graphene. The band gap is closely related to the aromaticity distribution and therefore tailoring the aromaticity patterns is a rational way for controlling the band gap. In the present work, it is shown how the three distinct classes of aromaticity patterns already found for armchair graphene nanoribbons can be rationally tuned by chemical edge functionalisation to modify their electronic arrangement and band gap. The electronic structure and the aromaticity distribution are studied using DFT calculations and through a series of delocalisation and geometry analysis methods, like the six-centre index (SCI) and the mean bond length (MBL) geometry descriptor. Novel aromaticity patterns are found for fluorine and nitrogen functionalisation characterised as inverted incomplete-Clar, and broken-Kekulé classes, while oxygen and nitrogen functionalisation is found to cut and extend the aromatic system, respectively. All these different arrangements of aromatic rings along the structure of graphene nanoribbons are explained using Clar's sextet theory, and a mesomeric effect mechanism for fluorine and nitrogen. In all cases, the changes in the aromaticity patterns are related to changes in the band gap. The energy and stability of the different edge functionalised graphene nanoribbons are also studied. An overall picture of edge effects, aromaticity patterns, and band gap tuning is provided.

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.

Electronic structure and aromaticity of graphene nanoribbons.

We analyse the electronic structure and aromaticity of graphene nanoribbons and carbon nanotubes through a series of delocalisation and geometry analysis methods. In particular, the six-centre index (SCI) is found to be in good agreement with the mean bond length (MBL) and ring bond dispersion (RBD) geometry descriptors. Based on DFT periodic calculations, three distinct classes of aromaticity patterns have been found for armchair graphene nanoribbons, appearing periodically as the width of the ribbon is increased. The periodicity in the band gap is found to be related to these aromaticity patterns. Also, the appearance of such distinct aromaticity distribution is explained within the framework of the Clar's sextet theory. Both delocalisation and geometry analysis methods are shown to be very fast and reliable tools for easily analysing the aromaticity in carbon nanosystems.

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.

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.

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.

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.

CoNTub v2.0--algorithms for constructing C3-symmetric models of three-nanotube junctions.

Here, a method is described for easily building three-carbon nanotube junctions. It allows the geometry to be found and bond connectivity of C(3) symmetric nanotube junctions to be established. Such junctions may present a variable degree of pyramidalization and are composed of three identical carbon nanotubes with arbitrary chirality. From the indices of the target nanotube, applying the formulas of strip algebra, the possible positions of the six defects (heptagonal rings) needed can be found. Given the multiple possibilities that arise for a specific pair of indices, the relation between the macroscopic geometry (interbranch angles, junction size, and pyramidalization) and each specific solution is found. To automate the construction of these structures, we implemented this algorithm with CoNTub software, version 2.0, which is available at ( http://www.ugr.es/local/gmdm/contub2 ). In addition, a classification of three-nanotube junctions, 3TJ, in seven types based on the location of defects has been proposed, i.e. 3TJ(0:0:6), 3TJ(0:1:5), 3TJ(0:2:4), 3TJ(0:3:3), 3TJ(1:1:4), 3TJ(1:2:3), and 3TJ(2:2:2) types.

Edge effects, electronic arrangement, and aromaticity patterns on finite-length carbon nanotubes.

Previous investigations have revealed that even long carbon nanotubes (CNTs) retain bond patterns that are characterized by the localization of Clar rings. Even for CNTs with 10 nm length, an alternated, oscillating structure of Clar and Kekulé patterning was also found, indicating that these arrangements may possibly persist for even longer nanotubes, given that they are finite. In the present work, we perform a detailed and comprehensive theoretical study of this phenomenon, in order to find the causes that give rise to these patterns. A complete set of CNTs with different chiralities, diameters (up to 2 nm), lengths (up to 10 nm) and endings (capped, uncapped, and tailored endings) was considered for such purposes. The results indicate that the Clar patterning appears not only on armchair CNTs, but also on those with chiral angle values close to 30°, and this results in a stabilization of the structure, when compared with the uniform, zigzag CNTs. This stabilizing effect points to the causes that underlie the three Nakamura CNT types, resulting as the superposition of structures with a maximal number of Clar rings. Although there is a strict dependence on the border shape, the main cause of the bond patterning in long tubes is to be found in the intrinsic wrapping of each CNT, because the type and number of oscillations present in the longest structures do not depend on the particular length. Nevertheless, the three Nakamura types of armchair tubes appear to subsist beyond the appearance of oscillations, because each of these sets evolves in a different manner, and energy properties that link them together. Apart from the geometry, Clar patterning was investigated through NICS (Nucleus Independent Chemical Shifts) measures, which reveal a connection between the Clar rings and a local concentration of aromaticity.

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.

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.

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.

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.

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.