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Two-dimensional (2D) metal oxide semiconductors offer a superlative combination of high electron mobility and visible-range transparency uniquely suitable for flexible transparent electronics. Synthesis of these ultrathin (<3 nm) semiconductors by Cabrera-Mott oxidation of liquid metals could enable emerging device applications but requires the precise design of their electrostatics at the nanoscale. This study demonstrates sub-nanometer-level control over the thickness of semiconducting 2D antimony-doped indium oxide (AIO) by manipulating the kinetics of Cabrera-Mott oxidation through variable-speed liquid metal printing at plastic-compatible temperatures (175°C). By modulating both the growth kinetics and doping, we engineer the conductivity and crystallinity of AIO for integration in ultrathin channel transistors exhibiting exceptional steep turn-on, on-off ratios > 106 and an outstanding average mobility of 34.7 ± 12.9 cm2/Vs. This result shows the potential for kinetically controlling 2D oxide synthesis for various high-performance optoelectronic device applications. 

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. We report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials. 

Risk-driven behaviour provides a feedback mechanism through which individuals both shape and are collectively affected by an epidemic. We introduce a general and flexible compartmental model to study the effect of heterogeneity in the population with regard to risk tolerance. The interplay between behaviour and epidemiology leads to a rich set of possible epidemic dynamics. Depending on the behavioural composition of the population, we find that increasing heterogeneity in risk tolerance can either increase or decrease the epidemic size. We find that multiple waves of infection can arise due to the interplay between transmission and behaviour, even without the replenishment of susceptibles. We find that increasing protective mechanisms such as the effectiveness of interventions, the fraction of risk-averse people in the population and the duration of intervention usage reduce the epidemic overshoot. When the protection is pushed past a critical threshold, the epidemic dynamics enter an underdamped regime where the epidemic size exactly equals the herd immunity threshold and overshoot is eliminated. Finally, we can find regimes where epidemic size does not monotonically decrease with a population that becomes increasingly risk-averse.