Layered graphitic carbon host formation during liquid-free solid state growth of metal pyrophosphates

We report a successful ligand- and liquid-free solid state route to form metal pyrophosphates within a layered graphitic carbon matrix through a single step approach involving pyrolysis of previously synthesized organometallic derivatives of a cyclotriphosphazene. In this case, we show how single crystal Mn2P2O7 can be formed on either the micro- or the nanoscale in the complete absence of solvents or solutions by an efficient combustion process using rationally designed macromolecular trimer precursors, and present evidence and a mechanism for layered graphite host formation. Using in situ Raman spectroscopy, infrared spectroscopy, X-ray diffraction, high resolution electron microscopy, thermogravimetric and differential scanning calorimetric analysis, and near-edge X-ray absorption fine structure examination, we monitor the formation process of a layered, graphitic carbon in the matrix. The identification of thermally and electrically conductive graphitic carbon host formation is important for the further development of this general ligand-free synthetic approach for inorganic nanocrystal growth in the solid state, and can be extended to form a range of transition metals pyrophosphates. For important energy storage applications, the method gives the ability to form oxide and (pyro)phosphates within a conductive, intercalation possible, graphitic carbon as host–guest composites directly on substrates for high rate Li-ion battery and emerging alternative positive electrode materials

Modelling and predictive control techniques for building heating systems

Model predictive control (MPC) has often been referred to in literature as a potential method for more efficient control of building heating systems. Though a significant performance improvement can be achieved with an MPC strategy, the complexity introduced to the commissioning of the system is often prohibitive. Models are required which can capture the thermodynamic properties of the building with sufficient accuracy for meaningful predictions to be made. Furthermore, a large number of tuning weights may need to be determined to achieve a desired performance. For MPC to become a practicable alternative, these issues must be addressed. Acknowledging the impact of the external environment as well as the interaction of occupants on the thermal behaviour of the building, in this work, techniques have been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive high-order simulation models, capable of replicating the thermal dynamics of a building. While a high-order simulation model allowed for control strategies to be analysed and compared, low-order models were required for use within the MPC strategy itself. The disturbance estimation techniques were adapted for use with system-identification methods to derive such models. MPC formulations were then derived to enable a more straightforward commissioning process and implemented in a validated simulation platform. A prioritised-objective strategy was developed which allowed for the tuning parameters typically associated with an MPC cost function to be omitted from the formulation by separation of the conflicting requirements of comfort satisfaction and energy reduction within a lexicographic framework. The improved ability of the formulation to be set-up and reconfigured in faulted conditions was shown.