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A facile route to generate cyclic peptide nanotubes with tunable interiors is presented. By incorporating 3-amino-2-methylbenzoic acid in the D,L-alternating primary sequence of a cyclic peptide, a functional group can be presented in the interior of the nanotubes without compromising the formation of high aspect ratio nanotubes. The new design of such a cyclic peptide also enables one to modulate the nanotube growth process to be compatible with the polymer processing window without compromising the formation of high aspect ratio nanotubes, thus opening a viable approach toward molecularly defined porous membranes.

Decay properties and stability of heaviest nuclei with Z≤132 are studied within the macro-microscopical approach for nuclear ground state masses and phenomenological relations for the half-lives with respect to α-decay, β-decay and spontaneous fission. We found that at existing experimental facilities the synthesis and detection of nuclei with Z>120 produced in fusion reactions may be difficult due to their short half-lives (shorter than 1 μs). The nearest (more neutron-rich) isotopes of superheavy elements with 111≤Z≤115 to those synthesized recently in Dubna in 48 Ca -induced fusion reactions are found to be β+-decaying. This fact may significantly complicate their experimental identification. However it gives a chance to synthesize in fusion reactions the most stable superheavy nuclei located at the center of the island of stability. Our calculations yield that the β-stable isotopes 291 Cn and 293 Cn with a half-life of about 100 years are the longest-living superheavy nuclei located at the island of stability.

Understanding the deformation mechanisms in multilayer graphene (MLG), an attractive material used in nanodevices as well as in the reinforcement of nanocomposites, is critical yet challenging due to difficulties in experimental characterization and the spatiotemporal limitations of atomistic modeling. In this study, we combine nanomechanical experiments with coarse-grained molecular dynamics (CG-MD) simulations to elucidate the mechanisms of deformation and failure of MLG sheets. Elastic properties of graphene sheets with one to three layers are measured using film deflection tests. A nonlinear behavior in the force vs deflection curves for MLGs is observed in both experiments and simulations: during loading/unloading cycles, MLGs dissipate energy through a "recoverable slippage" mechanism. The CG-MD simulations further reveal an atomic level interlayer slippage process and suggest that the dissipated energy scales with film perimeter. Moreover, our study demonstrates that the finite shear strength between individual layers could explain the experimentally measured size-dependent strength with thickness scaling in MLG sheets.

Cellulose nanocrystals (CNCs) exhibit outstanding mechanical properties exceeding that of Kevlar, serving as reinforcing domains in nature’s toughest biological nanocomposites such as wood. To establish a molecular-level understanding of how CNCs develop high resistance to failure, here we present new analyses based on atomistic simulations on the fracture energy of Iβ CNCs. We show that the fracture energy depends on the crystal width, due to edge defects that significantly reduce the fracture energy of small crystals but have a negligible effect beyond a critical width. Additionally, collective effects of sheet stacking and stabilization by van der Waals interactions saturate at a critical crystal thickness that we predict with an analytical relationship based on a physical model. Remarkably, ideal dimensions optimizing fracture energy are found to be 4.8–5.6 nm in thickness (approximately 6–7 layers) and 6.2–7.3 nm in width (approximately 6–7 cellulose chains), which correspond to the common dimensions of CNCs found in nature. Our studies shed light on evolutionary principles that provide guidance toward high mechanical performance in natural and synthetic nanobiocomposites.

Self-assembly of cyclic peptide nanotubes (CPNs) in polymer thin films has opened up the possibility of creating separation membranes with tunable nanopores that can differentiate molecules at the sub-nanometer level. While it has been demonstrated that the interior chemistry of the CPNs can be tailored by inserting functional groups in the nanopore lumen (mCPNs), a design strategy for picking the chemical modifications that lead to particular transport properties has not been established. Drawing from the knowledgebase of functional groups in natural amino acids, here we use molecular dynamics simulations to elucidate how bioinspired mutations influence the transport of water through mCPNs. We show that, at the nanoscale, factors besides the pore size, such as electrostatic interactions and steric effects, can dramatically change the transport properties. We recognize a novel asymmetric structure of water under nanoconfinement inside the chemically functionalized nanotubes and identify that the small non-polar glycine-mimic groups that minimize the steric constraints and confer a hydrophobic character to the nanotube interior are the fastest transporters of water. Our computationally developed experiments on a realistic material system circumvent synthetic challenges, and lay the foundation for bioinspired principles to tailor artificial nanochannels for separation applications such as desalination, ion-exchange and carbon capture.

Multi-layer graphene assemblies (MLGs) or fibers with a staggered architecture exhibit high toughness and failure strain that surpass those of the constituent single sheets. However, how the architectural parameters such as the sheet overlap length affect these mechanical properties remains unknown due in part to the limitations of mechanical continuum models. By exploring the mechanics of MLG assemblies under tensile deformation using our established coarse-grained molecular modeling framework, we have identified three different critical interlayer overlap lengths controlling the strength, plastic stress, and toughness of MLGs, respectively. The shortest critical length scale L(C)(S) governs the strength of the assembly as predicted by the shear-lag model. The intermediate critical length L(C)(P) is associated with a dynamic frictional process that governs the strain localization propensity of the assembly, and hence the failure strain. The largest critical length scale L(C)(T) corresponds to the overlap length necessary to achieve 90% of the maximum theoretical toughness of the material. Our analyses provide the general guidelines for tuning the constitutive properties and toughness of multilayer 2D nanomaterials using elasticity, interlayer adhesion energy and geometry as molecular design parameters.

Graphene oxide (GO) shows promise as a nanocomposite building block due to its exceptional mechanical properties. While atomistic simulations have become central to investigating its mechanical properties, the method remains prohibitively expensive for large deformations and mesoscale failure mechanisms. To overcome this, we establish a coarse-grained (CG) model that captures key mechanical and interfacial properties, and the non-homogeneous effect of oxidation in GO sheets. The CG model consists of three types of CG beads, representing groups of pristine sp 2 carbon atoms, and hydroxyl and epoxide functionalized regions. The CG force field is parameterized based on density functional-based tight binding simulations on three extreme cases. It accurately quantifies deterioration of tensile modulus and strength at the expense of improving interlayer adhesion with increasing oxidation of varying chemical compositions. We demonstrate the applicability of the model to study mesoscale phenomena by reproducing different force vs. indentation curves in silico, corroborating recent experimental observations on how chemistry near contact point influences properties. Finally, we apply the model to measure the fracture toughness of pristine graphene and GO. The critical stress intensity factor ( ) of graphene is found to be the highest, and epoxide-rich GO also possess higher compared to hydroxyl-rich GO.