ABSTRACT
In the realm of particle self-assembly, it is possible to reliably construct nearly arbitrary structures if all the pieces are distinct1-3, but systems with fewer flavours of building blocks have so far been limited to the assembly of exotic crystals4-6. Here we introduce a minimal model system of colloidal droplet chains7, with programmable DNA interactions that guide their downhill folding into specific geometries. Droplets are observed in real space and time, unravelling the rules of folding. Combining experiments, simulations and theory, we show that controlling the order in which interactions are switched on directs folding into unique structures, which we call colloidal foldamers8. The simplest alternating sequences (ABAB...) of up to 13 droplets yield 11 foldamers in two dimensions and one in three dimensions. Optimizing the droplet sequence and adding an extra flavour uniquely encodes more than half of the 619 possible two-dimensional geometries. Foldamers consisting of at least 13 droplets exhibit open structures with holes, offering porous design. Numerical simulations show that foldamers can further interact to make complex supracolloidal architectures, such as dimers, ribbons and mosaics. Our results are independent of the dynamics and therefore apply to polymeric materials with hierarchical interactions on all length scales, from organic molecules all the way to Rubik's Snakes. This toolbox enables the encoding of large-scale design into sequences of short polymers, placing folding at the forefront of materials self-assembly.
Subject(s)
Materials Science , Polymers , DNA/chemistry , Emulsions/chemical synthesis , Emulsions/chemistry , Polymers/chemical synthesis , Polymers/chemistry , Materials Science/methods , Colloids/chemical synthesis , Colloids/chemistryABSTRACT
Self-assembly of complex and functional materials remains a grand challenge in soft material science. Efficient assembly depends on a delicate balance between thermodynamic and kinetic effects, requiring fine-tuning affinities and concentrations of subunits. By contrast, we introduce an assembly paradigm that allows large error-tolerance in the subunit affinity and helps avoid kinetic traps. Our combined experimental and computational approach uses a model system of triangular subunits programmed to assemble into T = 3 icosahedral capsids comprising 60 units. The experimental platform uses DNA origami to create monodisperse colloids whose three-dimensional geometry is controlled to nanometer precision, with two distinct bonds whose affinities are controlled to kBT precision, quantified in situ by static light scattering. The computational model uses a coarse-grained representation of subunits, short-ranged potentials, and Langevin dynamics. Experimental observations and modeling reveal that when the bond affinities are unequal, two distinct hierarchical assembly pathways occur, in which the subunits first form dimers in one case and pentamers in another. These hierarchical pathways produce complete capsids faster and are more robust against affinity variation than egalitarian pathways, in which all binding sites have equal strengths. This finding suggests that hierarchical assembly may be a general engineering principle for optimizing self-assembly of complex target structures.
Subject(s)
Capsid , Materials Science , Capsid/metabolism , Capsid Proteins/chemistry , DNA/chemistry , Kinetics , Thermodynamics , Virus Assembly , Materials Science/methodsABSTRACT
Inorganic materials have essential roles in society, including in building construction, optical devices, mechanical engineering and as biomaterials1-4. However, the manufacture of inorganic materials is limited by classical crystallization5, which often produces powders rather than monoliths with continuous structures. Several precursors that enable non-classical crystallization-such as pre-nucleation clusters6-8, dense liquid droplets9,10, polymer-induced liquid precursor phases11-13 and nanoparticles14-have been proposed to improve the construction of inorganic materials, but the large-scale application of these precursors in monolith preparations is limited by availability and by practical considerations. Inspired by the processability of polymeric materials that can be manufactured by crosslinking monomers or oligomers15, here we demonstrate the construction of continuously structured inorganic materials by crosslinking ionic oligomers. Using calcium carbonate as a model, we obtain a large quantity of its oligomers (CaCO3)n with controllable molecular weights, in which triethylamine acts as a capping agent to stabilize the oligomers. The removal of triethylamine initiates crosslinking of the (CaCO3)n oligomers, and thus the rapid construction of pure monolithic calcium carbonate and even single crystals with a continuous internal structure. The fluid-like behaviour of the oligomer precursor enables it to be readily processed or moulded into shapes, even for materials with structural complexity and variable morphologies. The material construction strategy that we introduce here arises from a fusion of classic inorganic and polymer chemistry, and uses the same cross-linking process for the manufacture the materials.
Subject(s)
Calcium Carbonate/chemistry , Chemistry, Inorganic , Materials Science/methods , Polymers/chemistryABSTRACT
The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.
Subject(s)
Biocompatible Materials/chemistry , High-Throughput Screening Assays/methods , Animals , Humans , Materials Science/methodsABSTRACT
Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of "bio-integrated" technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in following sections. The subsequent content highlights the most advanced biosensors, classified according to their ability to capture biophysical, biochemical, and environmental information. Additional sections feature schemes for electrically powering these sensors and strategies for achieving fully integrated, wireless systems. The review concludes with an overview of key remaining challenges and a summary of opportunities where advances in materials chemistry will be critically important for continued progress.
Subject(s)
Biosensing Techniques/instrumentation , Wearable Electronic Devices , Biosensing Techniques/methods , Humans , Materials Science/methodsABSTRACT
Large-size ultrathin 2D materials, with extensive applications in optics, medicine, biology, and semiconductor fields, can be prepared through an existing common physical and chemical process. However, the current exfoliation technologies still need to be improved upon with urgency. Herein, a novel and simple "ultrasonic-ball milling" strategy is reported to effectively obtain high quality and large size ultrathin 2D materials with complete lattice structure through the introduction of moderate sapphire (Al2 O3 ) abrasives in a liquid phase system. Ultimately numerous high-quality ultrathin h-BN, graphene, MoS2 , WS2 , and BCN nanosheets are obtained with large sizes ranging from 1-20 µm, small thickness of ≈1-3 nm and a high yield of over 20%. Utilizing shear and friction force synergistically, this strategy provides a new method and alternative for preparing and optimizing large size ultrathin 2D materials.
Subject(s)
Materials Science , Nanostructures , Ultrasonics , Friction , Graphite , Materials Science/methods , Nanostructures/chemistry , Shear StrengthABSTRACT
Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high-throughput and high-content screening assays, dose-response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer-by-design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation.
Subject(s)
Materials Science , Nanostructures , Safety , Toxicity Tests , Computer Simulation , Humans , Materials Science/methods , Materials Science/trends , Nanostructures/standards , Risk AssessmentABSTRACT
Recent advances in materials chemistry and composite materials design establish the foundations for classes of electronics with physical form factors that bridge the gap between soft biological organisms and rigid microsystems technologies. Skin-interfaced platforms of this type have broad utility in continuous clinical-grade monitoring of physiological status, with the potential to significantly lower the cost and increase the efficacy of modern health care. Development of materials and device designs for power supply systems in this context is critically important, and it represents a rapidly expanding focus of research in the chemical sciences. Reformulating conventional technologies into biocompatible platforms and co-integrating them into skin-interfaced systems demand innovative approaches in materials chemistry and engineering. In terms of physical properties, the resulting devices must offer levels of flexibility, stretchability, thickness, and mass density that approach those of the epidermis itself, while maintaining operational characteristics and mechanical durability for practical use outside of a laboratory or hospital. While nearly all commercially available components for energy storage and harvesting are rigid and planar, recent research provides options in devices that are biocompatible not only at the level of the constituent materials but also in terms of the mechanics and geometrical forms, with resulting capabilities for establishing stable, nonirritating, intimate interfaces to the skin for extended periods of time. This Account highlights the range of materials choices and associated device architectures for skin-interfaced power supply systems. The Account begins with an overview of the main design strategies, ranging from one-, two-, and three-dimensional engineered composite structures to active materials that are intrinsically stretchable. The following sections describe a broad collection of devices based on these concepts, starting with batteries and supercapacitors for storage and then photovoltaic, piezoelectric, triboelectric, and thermoelectric devices for harvesting. Representative examples highlight recent advances, with a focus on the relationship between the materials and the performance during deformation. A final section discusses the challenges and opportunities in this area. Continued efforts in fundamental chemical research will be critically important to progress in this emerging field of technology. For example, understanding the mechanisms by which physical deformations affect the intrinsic materials properties and the system-level performance requires further study. The development of stretchable and biocompatible solid electrolytes with high ionic conductivity is an example of a specific area of interest for energy storage devices. Here and in other storage and harvesting systems advanced materials are needed to provide robust barriers to environmental factors. Work to address these and other interesting challenges will demand multidisciplinary collaborations between chemists, materials scientists, bioengineers, and clinicians, all oriented toward establishing the foundations for technologies that could help to address global grand challenges in human health care.
Subject(s)
Electric Power Supplies , Equipment Design , Wearable Electronic Devices , Humans , Inorganic Chemicals/chemistry , Materials Science/methods , Organic Chemicals/chemistryABSTRACT
Proteins are a class of nanoscale building block with remarkable chemical complexity and sophistication: their diverse functions, shapes, and symmetry as well as atomically monodisperse structures far surpass the range of conventional nanoparticles that can be accessed synthetically. The chemical topologies of proteins that drive their assembly into materials are central to their functions in nature. However, despite the importance of protein materials in biology, efforts to harness these building blocks synthetically to engineer new materials have been impeded by the chemical complexity of protein surfaces, making it difficult to reliably design protein building blocks that can be robustly transformed into targeted materials. Here we describe our work aimed at exploiting a simple but important concept: if one could exchange complex protein-protein interactions with well-defined and programmable DNA-DNA interactions, one could control the assembly of proteins into structurally well-defined oligomeric and polymeric materials and three-dimensional crystals. As a class of nanoscale building block, proteins with surface DNA modifications have a vast design space that exceeds what is practically and conceptually possible with their inorganic counterparts: the sequences of the DNA and protein and the chemical nature and position of DNA attachment all play roles in dictating the assembly behavior of protein-DNA conjugates. We summarize how each of these design parameters can influence structural outcome, beginning with proteins with a single surface DNA modification, where energy barriers between protein monomers can be tuned through the sequence and secondary structure of the oligonucleotide. We then explore challenges and progress in designing directional interactions and valency on protein surfaces. The directional binding properties of protein-DNA conjugates are ultimately imposed by the amino acid sequence of the protein, which defines the spatial distribution of DNA modification sites on the protein. Through careful design and mutagenesis, bivalent building blocks that bind directionally to form one-dimensional assemblies can be realized. Finally, we discuss the assembly of proteins densely modified with DNA into crystalline superlattices. At first glance, these protein building blocks display crystallization behavior remarkably similar to that of their DNA-functionalized inorganic nanoparticle counterparts, which allows design principles elucidated for DNA-guided nanoparticle crystallization to be used as predictive tools in determining structural outcomes in protein systems. Proteins additionally offer design handles that nanoparticles do not: unlike nanoparticles, the number and spatial distribution of DNA can be controlled through the protein sequence and DNA modification chemistry. Changing the spatial distributions of DNA can drive otherwise identical proteins down distinct crystallization pathways and yield building blocks with exotic distributions of DNA that crystallize into structures that are not yet attainable using isotropically functionalized particles. We highlight challenges in accessing other classes of architectures and establishing general design rules for DNA-mediated protein assembly. Harnessing surface DNA modifications to build protein materials creates many opportunities to realize new architectures and answer fundamental questions about DNA-modified nanostructures in both materials and biological contexts. Proteins with surface DNA modifications are a powerful class of nanomaterial building blocks for which the DNA and protein sequences and the nature of their conjugation dictate the material structure.
Subject(s)
Catalase/chemistry , Chaperonin 60/chemistry , DNA/chemistry , beta-Galactosidase/chemistry , Engineering/methods , Gold/chemistry , Materials Science/methods , Metal Nanoparticles/chemistry , Oligodeoxyribonucleotides/chemistryABSTRACT
The influence of the amorphization technique on the physicochemical properties of amorphous lactulose was investigated. Four different amorphization techniques were used: quenching of the melt, milling, spray-drying, and freeze-drying, and amorphous samples were analyzed by differential scanning calorimetry, NMR spectroscopy, and powder X-ray diffraction analysis. Special attention was paid to the tautomeric composition and to the glass transition of amorphized materials. It was found that the tautomeric composition of the starting physical state (crystal, liquid, or solution) is preserved during the amorphization process and has a strong repercussion on the glass transition of the material. The correlation between these two properties as well as the plasticizing effect of the different tautomers was clarified by molecular dynamics simulations.
Subject(s)
Desiccation/methods , Lactulose/chemistry , Materials Science/methods , Calorimetry, Differential Scanning , Diffusion , Freeze Drying/methods , Isomerism , Lactulose/chemical synthesis , Magnetic Resonance Spectroscopy , Molecular Dynamics Simulation , Powders , Solubility , Vitrification , X-Ray DiffractionSubject(s)
Programming Languages , Algorithms , Genomics/methods , Materials Science/methods , Research , Systems Biology/methods , Time FactorsABSTRACT
Materials chemistry has been one of the most talked-about areas of materials research over the past decades [...].
Subject(s)
Chemistry , Materials Science , Chemistry/methods , Materials Science/methodsABSTRACT
The exceptional reactivity of the azide group makes organic azides a highly versatile family of compounds in chemistry and the material sciences. One of the most prominent reactions employing organic azides is the regioselective copper(I)-catalyzed Huisgen 1,3-dipolar cycloaddition with alkynes yielding 1,2,3-triazoles. Other named reactions include the Staudinger reduction, the aza-Wittig reaction, and the Curtius rearrangement. The popularity of organic azides in material sciences is mostly based on their propensity to release nitrogen by thermal activation or photolysis. On the one hand, this scission reaction is accompanied with a considerable output of energy, making them interesting as highly energetic materials. On the other hand, it produces highly reactive nitrenes that show extraordinary efficiency in polymer crosslinking, a process used to alter the physical properties of polymers and to boost efficiencies of polymer-based devices such as membrane fuel cells, organic solar cells (OSCs), light-emitting diodes (LEDs), and organic field-effect transistors (OFETs). Thermosets are also suitable application areas. In most cases, organic azides with multiple azide functions are employed which can either be small molecules or oligo- and polymers. This review focuses on nitrene-based applications of multivalent organic azides in the material and life sciences.
Subject(s)
Alkynes/chemistry , Azides/chemistry , Cross-Linking Reagents/chemistry , Nitrogen/chemistry , Triazoles/chemical synthesis , Catalysis , Cycloaddition Reaction , Humans , Materials Science/methods , Molecular Structure , Photochemical Processes , PhotolysisABSTRACT
Greener processes have emerged as serious and competitive routes to produce various nanomaterials [...].
Subject(s)
Bacteria/metabolism , Materials Science/methods , Nanostructures/chemistry , Nanotechnology/methods , Biocompatible Materials/chemistry , Drug Delivery Systems/methods , Nanostructures/microbiology , Nanostructures/virology , Plant Viruses/metabolismABSTRACT
Flame-retardant polyurethane foams are potential packing materials for the transport casks of highly active nuclear materials for shock absorption and insulation purposes. Exposure of high doses of gamma radiation causes cross-linking and chain sectioning of macromolecules in this polymer foam, which leads to reorganization of their cellular microstructure and thereby variations in physico-mechanical properties. In this study, in-house-developed flame-retardant rigid polyurethane foam samples were exposed to gamma irradiation doses in the 0-20â kGy range and synchrotron radiation X-ray micro-computed tomography (SR-µCT) imaging was employed for the analysis of radiation-induced morphological variations in their cellular microstructure. Qualitative and quantitative analysis of SR-µCT images has revealed significant variations in the average cell size, shape, wall thickness, orientations and spatial anisotropy of the cellular microstructure in polyurethane foam.
Subject(s)
Flame Retardants/radiation effects , Polyurethanes/radiation effects , X-Ray Microtomography/methods , Gamma Rays , Materials Science/methods , Radiation Dosage , SynchrotronsABSTRACT
The number of published materials science articles has increased manyfold over the past few decades. Now, a major bottleneck in the materials discovery pipeline arises in connecting new results with the previously established literature. A potential solution to this problem is to map the unstructured raw text of published articles onto structured database entries that allow for programmatic querying. To this end, we apply text mining with named entity recognition (NER) for large-scale information extraction from the published materials science literature. The NER model is trained to extract summary-level information from materials science documents, including inorganic material mentions, sample descriptors, phase labels, material properties and applications, as well as any synthesis and characterization methods used. Our classifier achieves an accuracy (f1) of 87%, and is applied to information extraction from 3.27 million materials science abstracts. We extract more than 80 million materials-science-related named entities, and the content of each abstract is represented as a database entry in a structured format. We demonstrate that simple database queries can be used to answer complex "meta-questions" of the published literature that would have previously required laborious, manual literature searches to answer. All of our data and functionality has been made freely available on our Github ( https://github.com/materialsintelligence/matscholar ) and website ( http://matscholar.com ), and we expect these results to accelerate the pace of future materials science discovery.
Subject(s)
Cheminformatics/methods , Data Mining/methods , Databases, Factual , Materials Science/methods , Neural Networks, Computer , SoftwareABSTRACT
The material-air partition coefficient (Kma ) is a key parameter to estimate the release of chemicals incorporated in solid materials and resulting human exposures. Existing correlations to estimate Kma are applicable for a limited number of chemical-material combinations without considering the effect of temperature. The present study develops a quantitative structure-property relationship (QSPR) to predict Kma for a large number of chemical-material combinations. We compiled a dataset of 991 measured Kma for 179 chemicals in 22 consolidated material types. A multiple linear regression model predicts Kma as a function of chemical's Koa , enthalpy of vaporization (∆Hv ), temperature, and material type. The model shows good fitting of the experimental dataset with adjusted R2 of 0.93 and has been verified by internal and external validations to be robust, stable and has good predicting ability ( Rext2 > 0.78). A generic QSPR is also developed to predict Kma from chemical properties and temperature only (adjusted R2 = 0.84), without the need to assign a specific material type. These QSPRs provide correlation methods to estimate Kma for a wide range of organic chemicals and materials, which will facilitate high-throughput estimates of human exposures for chemicals in solid materials, particularly building materials and furniture.
Subject(s)
Air Pollution, Indoor/analysis , Models, Chemical , Organic Chemicals/analysis , Organic Chemicals/chemistry , Quantitative Structure-Activity Relationship , Air Pollutants/analysis , Humans , Linear Models , Materials Science/methodsABSTRACT
Researchers striving to convert biology into an exact science foremost rely on structural biology and biochemical reconstitution approaches to obtain quantitative data. However, cell biological research is moving at an ever-accelerating speed into areas where these approaches lose much of their edge. Intrinsically unstructured proteins and biochemical interaction networks composed of interchangeable, multivalent, and unspecific interactions pose unique challenges to quantitative biology, as do processes that occur in discrete cellular microenvironments. Here we argue that a conceptual change in our way of conducting biochemical experiments is required to take on these new challenges. We propose that reconstitution of cellular processes in vitro should be much more focused on mimicking the cellular environment in vivo, an approach that requires detailed knowledge of the material properties of cellular compartments, essentially requiring a material science of the cell. In a similar vein, we suggest that quantitative biochemical experiments in vitro should be accompanied by corresponding experiments in vivo, as many newly relevant cellular processes are highly context-dependent. In essence, this constitutes a call for chemical biologists to convert their discipline from a proof-of-principle science to an area that could rightfully be called quantitative biochemistry in living cells. In this essay, we discuss novel techniques and experimental strategies with regard to their potential to fulfill such ambitious aims.
Subject(s)
Biochemistry/methods , Cytological Techniques , Models, Biological , Animals , Biochemistry/trends , Biomedical Research/methods , Biomedical Research/trends , Cellular Microenvironment , Cytological Techniques/trends , Humans , In Vitro Techniques/trends , Materials Science/methods , Materials Science/trendsABSTRACT
One unusual and challenging scientific field that has received only cursory attention to date is the three-dimensional (3D) microstructure and spatial distribution of drug(s) and formulation materials in solid dosage forms. This study aims to provide deeper insight into the relationships between the microstructure of multiple-unit pellet system (MUPS) tablets and the spatial distribution of the active pharmaceutical ingredient (API) and excipients to facilitate the design of quantitative models for drug delivery systems. Synchrotron radiation X-ray microcomputed tomography (SR-µCT) was established as a 3D structure elucidation technique, which, in conjunction with liquid chromatography coupled to mass spectrometry (LC-MS) or liquid chromatography with evaporative light-scattering detector (LC-ELSD) enables chemical analysis of tablets. On the basis of the specific interior construction of theophylline MUPS tablets, the spatial distribution of materials was acquired by quantifying microregion samples that had been validated by SR-µCT for their locations in the MUPS tablets. The 3D structure of the MUPS tablets was catalogued as three structural domains: a matrix layer (ML), a protective cushion layer (PCL), and pellets (PL). Compared with the components in the ML, components in the PL had a larger proportion of theophylline, sucrose, and diethyl phthalate and a smaller proportion of lactose and sodium lauryl sulfate, whereas glyceryl monostearate was found to account for a large portion of the PCL. Microstructural characterization-guided zonal chemical determination represents a new approach for quality assessment and the development of drug delivery systems with in-depth insight into their constituent layers on a new scale.
Subject(s)
Chromatography, High Pressure Liquid/methods , Materials Science/methods , Tablets/chemistry , Theophylline/chemistry , X-Ray Microtomography/methodsABSTRACT
Structural analysis of molecular pores can yield important information on their behavior in solution and in the solid state. We developed pywindow, a python package that enables the automated analysis of structural features of porous molecular materials, such as molecular cages. Our analysis includes the cavity diameter, number of windows, window diameters, and average molecular diameter. Molecular dynamics trajectories of molecular pores can also be analyzed to explore the influence of flexibility. We present the methodology, validation, and application of pywindow for the analysis of molecular pores, metal-organic polyhedra, and some instances of framework materials. pywindow is freely available from github.com/JelfsMaterialsGroup/pywindow .