Methyl methacrylate in poly(methyl methacrylate)--validation of direct injection gas chromatography

Gas chromatography (GC) was investigated for the determination of residual methyl methacrylate (MMA) in heat-processed poly(methyl methacrylate) (PMMA) denture base material emphasizing recovery and validation. Standard solutions of MMA and emulsion-polymerized PMMA in dichloromethane were analysed, before and after distillation by a room-temperature air stream into a liquid nitrogen trap, and in the presence of PMMA by direct injection. Quantitative NMR analysis using dimethyl sulphoxide as internal calibration standard in deuterated chloroform solutions provided validation. Good concordance was observed between results under all conditions; no problems arose from direct injection of PMMA solution for GC. Good straight line responses in log-log plots were generally observed. For GC and MMA: log-log calibration curve (slope: 0.9552 +/- 0.0051, r2: 0.9992, n = 32) indicated some non-linearity (t = 8.875, p approximately 4 x 10(-10)). Distillation gave slope: 0.9751 +/- 0.0213 (NS versus unity; t = 1.172, p > 0.25). For PMMA solutions, distillation (r2: 0.9301) gave greater scatter than direct injection (r2: 0.9704). For NMR: log-log plot of calculated versus actual MMA (slope: 0.9363 +/- 0.0157, r2: 0.9969, n = 13) again indicated non-linearity (t = 4.0682, p = 0.0019). PMMA solutions gave slope: 0.9477 +/- 0.0328, r2 = 0.9858 (NS versus unity; t = 1.5941, p = 0.13). Determination of MMA in PMMA by GC is recommended.     

An investigation of the thermal and catalytic behaviour of potassium in biomass combustion

Potassium, a key nutrient in biomass growth, contributes to problematic ash chemistry and corrosion in combustion. This study seeks to examine the behaviour and fate of potassium in biomass combustion under high temperature flame conditions. A model to predict potassium release is presented. Short rotation willow coppice was treated to reduce metals, by water-washing, and remove them, by demineralisation, and then potassium was doped into the demineralised sample. The resultant fuels have been studied for their combustion behaviours in methane–air flames, both as suspended, moving particles, and as stationary, supported particles, using high speed digital video. In the latter case, potassium release was measured simultaneously by emission spectroscopy. In both experiments, potassium was seen to catalyse devolatilisation, and for the stationary particles it was possible to detect potassium catalysis in the char burn-out rates. Demineralised willow was seen to melt in the flame and combustion resembled heavy oil combustion, rather than solid fuel combustion. The residual char was extremely slow to burn-out. In the potassium-doped particles, potassium was seen to evolve over three regimes, devolatilisation, char burn-out and, less significantly, during ash cooking. The first two evolution processes have been modelled using an apparent first order devolatilisation rate for the first stage, and a KOH evaporation model for the second stage.     

The rameses algorithm for multiple equilibria-II Some further developments

The algorithm RAMESES has been made more efficient by incorporation of additional procedures: to extrapolate to the next point by an exact polynomial of any desired order, to control the gain on the adjustment of each independent species, and to optimize the initial guess. The need to consider electroneutrality is emphasized, and some problems with convergence criteria and synthetic test systems are discussed. Some conditions for objective algorithm testing are proposed.     

The RAMESES algorithm for multiple equilibria-V. Error statements

The equations of multiple equilibria systems can be expressed succinctly in matrix algebra terms. This is the basis of the RAMESES algorithm for the solution of those equations. This matrix algebra leads directly to the differential equations for the interdependence of the vector variables of species concentration, component concentration and equilibrium constants, with or without certain constraints. The laws of propagation of errors then give an immediate expression of the covariance matrix for the dependent vector.     

The rameses algorithm for multiple equilibria-III Acceleration and standardized formation constants (RAMESES II)

By the use of a matrix-algebra identity, the algorithm RAMESES for solution of systems of equilibrium equations may be modified to reduce both computer storage requirements and execution time. As a result, standardized formation constants and solubility products are found. This may facilitate compilation of such data in uniform style. An illustrative example is given.     

The RAMESES algorithm for multiple equilibria-IV. Strategies for improvement (RAMESES III)

The algorithm RAMESES has been enhanced by the improvement of the forward extrapolation procedure to give more accurate estimates with a smoothed polynomial function in a dynamically adaptive scheme, ADEPT. A class of problems exhibiting chaotic behaviour due to exaggerated feedback has been controlled by limiting the correction factors. Improved execution speed has also been obtained through indirect addessing of sparse array elements. Some illustrative examples are given.     

A rapid algorithm for solution of the equations of multiple equilibrium systems-RAMESES

The solution of systems of equilibrium is an important though commonplace operation, rendered difficult by non-linearity. Previous methods of numerical solution have suffered from slow convergence, unreliability, and inefficient structure. An algorithm, RAMESES, is presented in matrix algebra terms, which is both simple in structure and efficient, involving only one matrix inversion per system and giving an exact solution of the set of dependent equilibrium equations at each iteration.