Characterization, modeling, and simulation of multiscale directed-assembly systems

Nanoscience is a rapidly developing field at the nexus of all physical sciences which holds the potential for mankind to gain a new level of control of matter over matter and energy altogether. Directed-assembly is an emerging field within nanoscience in which non-equilibrium system dynamics are controlled to produce scalable, arbitrarily complex and interconnected multi-layered structures with custom chemical, biologically or environmentally-responsive, electronic, or optical properties. We construct mathematical models and interpret data from direct-assembly experiments via application and augmentation of classical and contemporary physics, biology, and chemistry methods. Crystal growth, protein pathway mapping, LASER tweezers optical trapping, and colloid processing are areas of directed-assembly with established experimental techniques. We apply a custom set of characterization, modeling, and simulation techniques to experiments to each of these four areas. Many of these techniques can be applied across several experimental areas within directed-assembly and to systems featuring multiscale system dynamics in general. We pay special attention to mathematical methods for bridging models of system dynamics across scale regimes, as they are particularly applicable and relevant to directed-assembly. We employ massively parallel simulations, enabled by custom software, to establish underlying system dynamics and develop new device production methods

Advancing performance measurement theory by focusing on subjects : lessons from the measurement of social value

Performance measurement and management (PMM) researchers have recently called for a closer inspection of social controls – the cultural and behavioural aspects of PMM inside organisations – as a complement to longstanding inquiries into technical controls – the rational and structural processes that enable measurement. We address this call by first reviewing the principal findings obtained in the field of social value measurement (SVM), which focuses on the measurement of how and to what extent individuals and groups perceive and realise subjective changes (i.e., in knowledge, access, health, etc.) from interactions with organisations. Subsequently, we distil the main characteristics of SVM research (i.e., the basic conceptualisations, stated purposes and normative principles). We find that SVM tends to highlight the importance of individual and group wellbeing and welfare, aims to understand how organisational actions influence these conditions, and focuses upon individuals’ lived experiences of measuring or being measured. In comparison, PMM research concentrates on technical controls, mainly relies on notions of systems and structured processes, and assumes people’s behaviours are impacted by measures, but does not fully explore their responses. We argue that to properly acknowledge and integrate social aspects of PMM into research and practice, subjects – with their thoughts, emotions and experiences – should be included more explicitly in future studies and theorisations