Professor Stephen Blundell

Abstract:

The technique of muon spin rotation (μSR) has emerged in the last few decades as one of the most powerful methods of obtaining local magnetic information. To make the technique fully quantitative, it is necessary to have an accurate estimate of where inside the crystal structure the muon implants. This can be provided by density functional theory calculations using an approach that is termed as DFT + μ, density functional theory with the implanted muon included. This article reviews this approach, describes some recent successes in particular μSR experiments, and suggests some avenues for future exploration.

Abstract:

Recently, a new class of quantum magnets, the so-called breathing pyrochlore spin systems, have attracted much attention due to their potential to host exotic emergent phenomena. Here, we present magnetometry, heat capacity, thermal conductivity, muon-spin relaxation, and polarized inelastic neutron scattering measurements performed on high-quality single crystal samples of the breathing pyrochlore compound Ba3Yb2Zn5O11. We interpret these results using a simplified toy model and provide insight into the low-energy physics of this system beyond the single tetrahedron physics proposed previously.

Abstract:

KAgF₃ is a quasi-one-dimensional quantum antiferromagnet hosting a series of intriguing structural and magnetic transitions. Here we use powder neutron diffraction, μSR spectroscopy, and density functional theory calculations to elucidate the low-temperature magnetic phases. Below T_N1 = 29 K we find that the material orders as an A-type antiferromagnet with an ordered moment of 0.52 μ B . Both neutrons and muons provide evidence for an intermediate phase at temperatures T_N1 < T < T_N2 with T_N2 ≈ 66 K from a previous magnetometry study. However, the evidence is at the limit of detection and its nature remains an open problem.

Abstract:

A software extension to the Windows Muon Data Analysis software package WiMDA has been developed for the analysis of µ⁻SR data, which has been dubbed Negative-WiMDA. In designing Negative-WiMDA, some key features were considered: it should be easily accessed from the main analysis window of WiMDA; it should be able to account for multiple elements in a sample; it should be able to subtract signals treated as unwanted background, allowing the user to focus on a particular element of interest; it should be able to handle transverse-field (TF) data, and perhaps most importantly, it should be intuitive to use. The main features of Negative-WiMDA are presented here with a few examples of their use.