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The assembly of peptide and peptide‐inspired building blocks into functional, well‐defined, multi‐length scale materials represents an exciting, rapidly expanding research field that bridges the principles of polymer science and engineering with a tremendous breadth of biomolecular interactions. The advantageous features of peptides, including their biocompatibility, functional diversity, and high purity, are complemented by the breadth of potential applications that may arise from their resultant structures and assemblies. Applications in biology (tissue scaffolding and drug conjugation), electronics (electron and/or ion‐conduction), and membranes (ion capture and ultrafiltration) represent a few of many examples where such biologically rich materials hold potential for enabling new routes to enhanced materials performance. Achieving successful solution and interfacial assembly techniques for peptides and other peptidomimetic materials requires obtaining a deep understanding of their design principles and limitations, as well as their amenability to structure formation when subjected to a variety of environmental conditions, such as pH, solvent, and temperature, to which such assembly methods may be exquisitely sensitive. This review especially focuses on mechanisms and the product of oligo‐ and polypeptide assembly, often resulting in the formation of extended, wire‐like structures obtained by solution methods, with inclusion of peptoid‐based structures and the complementary roles of polymerizations and step‐by‐step synthetic methods. Moreover, we describe relationships between naturally occurring peptide‐based structures, such asGeobacter pili, that in turn inspire self‐assembly of peptide‐based structures, composites with polymer materials, and assemblies therefrom.

 

Research involving polymer zwitterions typically involves the preparation of ammonium-based structures and their study as coatings or gels that impart hydrophilicity and/or antifouling properties to substrates and materials. More recent synthetic advances have produced a significant expansion in polymer zwitterion chemistry, especially with respect to the composition of the cationic moieties that open new possibilities to examine polymer zwitterions as amphiphiles, functional surfactants, and components of complex emulsions. This article describes the synthesis of new zwitterionic sulfonium sulfonate monomers and their use as starting materials in controlled free radical polymerization to yield the corresponding polymers. These novel polymer zwitterions bear sulfonium sulfonate groups, that possess an inverted dipole directionality relative to prior examples that yields different and unexpected physical and chemical properties. For example, the polymer zwitterions described here are soluble in a wide range of nonaqueous solvents and possess significantly greater stability against nucleophiles relative to their dipole-inverted counterparts. Additionally, the amphiphilic character of these sulfonium sulfonate polymers makes them amenable to use as surfactants for stabilizing oil-in-water emulsions, a feature that is not possible using conventional ultrahydrophilic polymer zwitterions. 

In the field of materials science, microscopy is the first and often only accessible method for structural characterization. There is a growing interest in the development of machine learning methods that can automate the analysis and interpretation of microscopy images. Typically training of machine learning models requires large numbers of images with associated structural labels, however, manual labeling of images requires domain knowledge and is prone to human error and subjectivity. To overcome these limitations, we present a semi-supervised transfer learning approach that uses a small number of labeled microscopy images for training and performs as effectively as methods trained on significantly larger image datasets. Specifically, we train an image encoder with unlabeled images using self-supervised learning methods and use that encoder for transfer learning of different downstream image tasks (classification and segmentation) with a minimal number of labeled images for training. We test the transfer learning ability of two self-supervised learning methods: SimCLR and Barlow-Twins on transmission electron microscopy (TEM) images. We demonstrate in detail how this machine learning workflow applied to TEM images of protein nanowires enables automated classification of nanowire morphologies ( e.g. , single nanowires, nanowire bundles, phase separated) as well as segmentation tasks that can serve as groundwork for quantification of nanowire domain sizes and shape analysis. We also extend the application of the machine learning workflow to classification of nanoparticle morphologies and identification of different type of viruses from TEM images. 

Filamentous bundles are ubiquitous in Nature, achieving highly adaptive functions and structural integrity from assembly of diverse mesoscale supramolecular elements. Engineering routes to synthetic, topologically integrated analogs demands precisely coordinated control of multiple filaments’ shapes and positions, a major challenge when performed without complex machinery or labor-intensive processing. Here, we demonstrate a photocreasing design that encodes local curvature and twist into mesoscale polymer filaments, enabling their programmed transformation into target 3-dimensional geometries. Importantly, patterned photocreasing of filament arrays drives autonomous spinning to form linked filament bundles that are highly entangled and structurally robust. In individual filaments, photocreases unlock paths to arbitrary, 3-dimensional curves in space. Collectively, photocrease-mediated bundling establishes a transformative paradigm enabling smart, self-assembled mesostructures that mimic performance-differentiating structures in Nature (e.g., tendon and muscle fiber) and the macro-engineered world (e.g., rope).

 

As a class of semiconductor nanocrystals that exhibit high photoluminescence quantum yield (PLQY) at tunable wavelengths, perovskite nanocrystals (PNCs) are attractive candidates for optoelectronic and light‐emitting devices. However, attempts to optimize PNC integration into such applications suffer from PNC instability and loss of PL over time. Here, we describe the impact of organic and polymeric N‐oxides when used in conjunction with PNCs, whereby a significant increase in PNC quantum yield is observed in solution, and stable PL emission is obtained in polymeric nanocomposites. Specifically, when using aliphatic N‐oxides in ligand exchange with CsPbBr₃PNCs in solution, a substantial boost in PNC brightness is observed (~40% or more PLQY increase), followed by an alteration of the perovskite chemistry. When N‐oxide substituents are positioned pendent to a poly(n‐butyl methacrylate) backbone, the optically clear flexible nanocomposite films obtained have bright PL emission and maintain optical clarity for months. X‐ray diffraction is useful for characterizing the PNC crystalline structure following exposure to aliphatic N‐oxides, while electron microscopy (EM) and small‐angle X‐ray scattering (SAXS) measurements of the PNC‐polymer nanocomposites show this polymeric N‐oxide platform to cleanly disperse PNCs in flexible polymer films.

 

Traditionally, complex coacervation is regarded as a process whereby two oppositely charged polyelectrolytes self-assemble into spherical droplets. Here, we introduce the polyzwitterionic complex, “pZC”, formed by the liquid-liquid phase separation of a polyzwitterion and a polyelectrolyte, and elucidate a mechanism by which such complexes can assemble using theory and experimental evidence. This system exhibits orthogonal phase behavior-it remains intact in acidic conditions, but disassembles as the pH increases, a process governed by the acid-base equilibria of the constituent chains. We relate the observed phase behavior to physiological conditions within the gastrointestinal tract with a simulation of the gastroduodenal junction, and demonstrate using video microscopy the viability of polyzwitterionic coacervates as technologies for the pH-triggered release of cargo. Such a system is envisaged to tackle imminent problems of drug transport via the oral route and serve as a packaging solution to increase uptake efficiency.

 

Porous carbon materials have increasingly drawn interest for applications ranging from supercapacitive energy storage to bioengineering. However, a simple and scalable fabrication process of such materials, employing low‐cost chemical compounds without sacrificing morphological and chemical control, remains lacking. Here, a novel, rapid, continuous bottom‐up strategy for synthesizing structurally tunable porous carbon network films on insulating and conductive substrates is reported. By employing rapid thermal annealing (RTA) of a commercial polyacrylonitrile‐based blend, simultaneous phase separation and thermal crosslinking are induced, effectively freezing the structure. Subsequent burning of degradable components generates a porous carbon framework ( ≈ 360 to 700 nm) doped with nitrogen and oxygen atoms. Introducing a boron‐containing reagent in the precursor solution enables boron doping and pore size reduction as small as 20 nm, enhancing materials' performance. The direct fabrication of micro‐supercapacitors on stainless steel substrates is demonstrated, achieving an areal capacitance of 12.7 mF cm⁻²at 50 mV s⁻¹, with ≈98% retention after 10 000 charge/discharge cycles. The benefit of boron doping is further highlighted for wound healing applications. Because RTA is already an established industrial method, this platform directly facilitates the synthesis of functional porous heteroatom‐doped carbon structures using commercial polymers and dopants for various applications.