Programming twist angle and strain profiles in 2D materials.

Moiré superlattices in twisted two-dimensional materials have generated tremendous excitement as a platform for achieving quantum properties on demand. However, the moiré pattern is highly sensitive to the interlayer atomic registry, and current assembly techniques suffer from imprecise control of the average twist angle, spatial inhomogeneity in the local twist angle, and distortions caused by random strain. We manipulated the moiré patterns in hetero- and homobilayers through in-plane bending of monolayer ribbons, using the tip of an atomic force microscope.

Two-particle time-domain interferometry in the fractional quantum Hall effect regime.

Quasi-particles are elementary excitations of condensed matter quantum phases. Demonstrating that they keep quantum coherence while propagating is a fundamental issue for their manipulation for quantum information tasks. Here, we consider anyons, the fractionally charged quasi-particles of the Fractional Quantum Hall Effect occurring in two-dimensional electronic conductors in high magnetic fields.

Wavelength weightings in machine learning for ovine joint tissue differentiation using diffuse reflectance spectroscopy (DRS).

To investigate the DRS of ovine joint tissue to determine the optimal optical wavelengths for tissue differentiation and relate these wavelengths to the biomolecular composition of tissues. In this study, we combine machine learning with DRS for tissue classification and then look further at the weighting matrix of the classifier to further understand the key differentiating features. Supervised machine learning was used to analyse DRS data.

Do improved pollination services outweigh farm-economic disadvantages of working in small-structured agricultural landscapes? - Development and application of a bio-economic model.

Increases in the size of agricultural fields, the loss of permanent green field edges and other semi-natural habitats have accompanied the intensification of agriculture, and are still ongoing. From a farm economic perspective, an increase in field size increases efficiency mainly due to cost savings. However, recent evidence suggests that increases in field size might lead to the loss of ecosystem services provided by farmland biodiversity, but this trade-off is rarely considered.

Machine learning classification of human joint tissue from diffuse reflectance spectroscopy data.

To assess if incorporation of DRS sensing into real-time robotic surgery systems has merit. DRS as a technology is relatively simple, cost-effective and provides a non-contact approach to tissue differentiation. Supervised machine learning analysis of diffuse reflectance spectra was performed to classify human joint tissue that was collected from surgical procedures.