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Classical nucleation theory predicts that two-dimensional islands on a surface must reach a critical size before they continue to grow; below that size, they dissolve. Chen et al. used phage display to select for short peptides that would bind to molybdenum disulfide (MoS 2 ) (see the Perspective by Kahr and Ward). Hexagonal arrays of these peptides grew epitaxially as dimers but without a size barrier—the critical nuclei size was zero. Although two-dimensional arrays formed, growth occurred one row at time. Classical nucleation theory indeed predicts the absence of a barrier for such one-dimensional growth. Science , this issue p. 1135 ; see also p. 1111 The barrier-free, row-by-row assembly of peptides on a MoS 2 surface confirms a prediction of classical nucleation theory. Assembly of two-dimensional (2D) molecular arrays on surfaces produces a wide range of architectural motifs exhibiting unique properties, but little attention has been given to the mechanism by which they nucleate. Using peptides selected for their binding affinity to molybdenum disulfide, we investigated nucleation of 2D arrays by molecularly resolved in situ atomic force microscopy and compared our results to molecular dynamics simulations. The arrays assembled one row at a time, and the nuclei were ordered from the earliest stages and formed without a free energy barrier or a critical size. The results verify long-standing but unproven predictions of classical nucleation theory in one dimension while revealing key interactions underlying 2D assembly.

Metallic nanostructures have become popular for applications in therapeutics, catalysts, imaging, and gene delivery. Molecular dynamics simulations are gaining influence to predict nanostructure assembly and performance; however, instantaneous polarization effects due to induced charges in the free electron gas are not routinely included. Here we present a simple, compatible, and accurate polarizable potential for gold that consists of a Lennard–Jones potential and a harmonically coupled core-shell charge pair for every metal atom. The model reproduces the classical image potential of adsorbed ions as well as surface, bulk, and aqueous interfacial properties in excellent agreement with experiment. Induced charges affect the adsorption of ions onto gold surfaces in the gas phase at a strength similar to chemical bonds while ions and charged peptides in solution are influenced at a strength similar to intermolecular bonds. The proposed model can be applied to complex gold interfaces, electrode processes, and extended to other metals. Molecular dynamics models for predicting the behavior of metallic nanostructures typically do not take into account polarization effects in metals. Here, the authors introduce a polarizable Lennard–Jones potential that provides quantitative insight into the role of induced charges at metal surfaces and related complex material interfaces.

The earlier integration of validated Lennard–Jones (LJ) potentials for 8 fcc metals into materials and biomolecular force fields has advanced multiple research fields, for example, metal–electrolyte interfaces, recognition of biomolecules, colloidal assembly of metal nanostructures, alloys, and catalysis. Here we introduce 12-6 and 9-6 LJ parameters for classical all-atom simulations of 10 further fcc metals (Ac, Ca (α), Ce (γ), Es (β), Fe (γ), Ir, Rh, Sr (α), Th (α), Yb (β)) and stainless steel. The parameters reproduce lattice constants, surface energies, water interfacial energies, and interactions with (bio)organic molecules in 0.1 to 5% agreement with experiment, as well as qualitative mechanical properties under standard conditions. Deviations are reduced up to a factor of one hundred in comparison to earlier Lennard–Jones parameters, embedded atom models, and density functional theory. We also explain a quantitative correlation between atomization energies from experiments and surface energies that supports parameter development. The models are computationally very efficient and applicable to an exponential space of alloys. Compatibility with a wide range of force fields such as the Interface force field (IFF), AMBER, CHARMM, COMPASS, CVFF, DREIDING, OPLS-AA, and PCFF enables reliable simulations of nanostructures up to millions of atoms and microsecond time scales. User-friendly model building and input generation are available in the CHARMM-GUI Nanomaterial Modeler. As a limitation, deviations in mechanical properties vary and are comparable to DFT methods. We discuss the incorporation of reactivity and features of the electronic structure to expand the range of applications and further increase the accuracy.

Next-generation structural materials are expected to be lightweight, high-strength and tough composites with embedded functionalities to sense, adapt, self-repair, morph and restore. This Review highlights recent developments and concepts in bioinspired nanocomposites, emphasizing tailoring of the architecture, interphases and confinement to achieve dynamic and synergetic responses. We highlight cornerstone examples from natural materials with unique mechanical property combinations based on relatively simple building blocks produced in aqueous environments under ambient conditions. A particular focus is on structural hierarchies across multiple length scales to achieve multifunctionality and robustness. We further discuss recent advances, trends and emerging opportunities for combining biological and synthetic components, state-of-the-art characterization and modelling approaches to assess the physical principles underlying nature-inspired design and mechanical responses at multiple length scales. These multidisciplinary approaches promote the synergetic enhancement of individual materials properties and an improved predictive and prescriptive design of the next era of structural materials at multilength scales for a wide range of applications.This Review discusses recent progress in bioinspired nanocomposite design, emphasizing the role of hierarchical structuring at distinct length scales to create multifunctional, lightweight and robust structural materials for diverse technological applications.

Nanoscale biological assemblies exemplified by exosomes, endosomes and capsids, play crucial roles in all living systems. Supraparticles (SP) from inorganic nanoparticles (NPs) replicate structural characteristics of these bioassemblies, but it is unknown whether they can mimic their biochemical functions. Here, we show that chiral ZnS NPs self-assemble into 70–100 nm SPs that display sub-nanoscale porosity associated with interstitial spaces between constituent NPs. Similarly to photosynthetic bacterial organelles, these SPs can serve as photocatalysts, enantioselectively converting L- or D- tyrosine (Tyr) into dityrosine (diTyr). Experimental data and molecular dynamic simulations indicate that the chiral bias of the photocatalytic reaction is associated with the chiral environment of interstitial spaces and preferential partitioning of enantiomers into SPs, which can be further enhanced by co-assembling ZnS with Au NPs. Besides replicating a specific function of biological nanoassemblies, these findings establish a path to enantioselective oxidative coupling of phenols for biomedical and other needs. Nanoscale biological assemblies play crucial roles in all living systems and display a variety of chemical functionalities. Here the authors show that it is possible to replicate some of the biochemical functions in similarly-sized assemblies made from inorganic nanoparticles.

Nucleation plays a critical role in many physical and biological phenomena that range from crystallization, melting and evaporation to the formation of clouds and the initiation of neurodegenerative diseases 1 – 3 . However, nucleation is a challenging process to study experimentally, especially in its early stages, when several atoms or molecules start to form a new phase from a parent phase. A number of experimental and computational methods have been used to investigate nucleation processes 4 – 17 , but experimental determination of the three-dimensional atomic structure and the dynamics of early-stage nuclei has been unachievable. Here we use atomic electron tomography to study early-stage nucleation in four dimensions (that is, including time) at atomic resolution. Using FePt nanoparticles as a model system, we find that early-stage nuclei are irregularly shaped, each has a core of one to a few atoms with the maximum order parameter, and the order parameter gradient points from the core to the boundary of the nucleus. We capture the structure and dynamics of the same nuclei undergoing growth, fluctuation, dissolution, merging and/or division, which are regulated by the order parameter distribution and its gradient. These experimental observations are corroborated by molecular dynamics simulations of heterogeneous and homogeneous nucleation in liquid–solid phase transitions of Pt. Our experimental and molecular dynamics results indicate that a theory beyond classical nucleation theory 1 , 2 , 18 is needed to describe early-stage nucleation at the atomic scale. We anticipate that the reported approach will open the door to the study of many fundamental problems in materials science, nanoscience, condensed matter physics and chemistry, such as phase transition, atomic diffusion, grain boundary dynamics, interface motion, defect dynamics and surface reconstruction with four-dimensional atomic resolution. Atomic electron tomography captures crystal nucleation in four dimensions in FePt nanoparticles, with the observed early-stage nucleation not consistent with classical nucleation theory.

Electron tomography is used to create a 3D reconstruction of a tungsten needle that allows the positions of individual atoms to be localized with a precision of 19 picometres, without using averaging or assuming the sample crystallinity. Crystallography, the primary method for determining the 3D atomic positions in crystals, has been fundamental to the development of many fields of science 1 . However, the atomic positions obtained from crystallography represent a global average of many unit cells in a crystal 1 , 2 . Here, we report, for the first time, the determination of the 3D coordinates of thousands of individual atoms and a point defect in a material by electron tomography with a precision of ∼19 pm, where the crystallinity of the material is not assumed. From the coordinates of these individual atoms, we measure the atomic displacement field and the full strain tensor with a 3D resolution of ∼1 nm 3 and a precision of ∼10 −3 , which are further verified by density functional theory calculations and molecular dynamics simulations. The ability to precisely localize the 3D coordinates of individual atoms in materials without assuming crystallinity is expected to find important applications in materials science, nanoscience, physics, chemistry and biology.

The simulation of chemical reactions and mechanical properties including failure from atoms to the micrometer scale remains a longstanding challenge in chemistry and materials science. Bottlenecks include computational feasibility, reliability, and cost. We introduce a method for reactive molecular dynamics simulations using a clean replacement of non-reactive classical harmonic bond potentials with reactive, energy-conserving Morse potentials, called the Reactive INTERFACE Force Field (IFF-R). IFF-R is compatible with force fields for organic and inorganic compounds such as IFF, CHARMM, PCFF, OPLS-AA, and AMBER. Bond dissociation is enabled by three interpretable Morse parameters per bond type and zero energy upon disconnect. Use cases for bond breaking in molecules, failure of polymers, carbon nanostructures, proteins, composite materials, and metals are shown. The simulation of bond forming reactions is included via template-based methods. IFF-R maintains the accuracy of the corresponding non-reactive force fields and is about 30 times faster than prior reactive simulation methods. Molecular dynamics is a common tool to study microscopic physicochemical systems, however, it is limited by the inhability to form and break chemical bonds. Here the authors present a method to modify traditional force-fields implementing bond dissociation and bond forming.

Systematic control of grain boundary densities in various platinum (Pt) nanostructures was achieved by specific peptide-assisted assembly and coagulation of nanocrystals. A positive quadratic correlation was observed between the oxygen reduction reaction (ORR) specific activities of the Pt nanostructures and the grain boundary densities on their surfaces. Compared to commercial Pt/C, the grain-boundary-rich strain-free Pt ultrathin nanoplates demonstrated a 15.5 times higher specific activity and a 13.7 times higher mass activity. Simulation studies suggested that the specific activity of ORR was proportional to the resident number and the resident time of oxygen on the catalyst surface, both of which correlate positively with grain boundary density, leading to improved ORR activities.

Heterogeneous nanocatalysts play a crucial role in both the chemical and energy industries. Despite substantial advancements in theoretical, computational and experimental studies, identifying their active sites remains a major challenge. Here we utilize atomic electron tomography to determine the three-dimensional atomic structure of PtNi and Mo-doped PtNi nanocatalysts for the electrochemical oxygen reduction reaction. We then employ the experimental atomic structures as input to first-principles-trained machine learning to identify the active sites of the nanocatalysts. Through the analysis of the structure–activity relationships, we formulate an equation termed the local environment descriptor, which balances the strain and ligand effects to provide physical and chemical insights into active sites in the oxygen reduction reaction. The ability to determine the three-dimensional atomic structure and chemical composition of realistic nanoparticles, combined with machine learning, could transform our fundamental understanding of the active sites of catalysts and guide the rational design of optimal nanocatalysts. Pt-based catalysts are the state of the art for the oxygen reduction reaction. Now the three-dimensional local atomic structure of PtNi and Mo-doped PtNi nanoparticles is revealed via atomic electron tomography, and a local environment descriptor of catalytic activity is put forwards.