In this part of the paper, we present a model to treat formation and transport of liquid water in proton exchange membrane ͑PEM͒ fuel cells ͑FCs͒ in three-dimensional ͑3-D͒ geometry. The performance of modern-day PEM FCs at high current density are largely dictated by the effective management of liquid water. In the first part of this paper, a rigorous model was presented to model PEM FCs using a computational fluid dynamic technique. It was found that under the assumption of no liquid water formation, the model consistently overpredicted measured polarization behavior. In the model presented here, the phase change process is modeled as an equilibrium process, while the transport of liquid water is governed by pressure, surface tension, gravity and electro-osmotic drag. Results show that the inclusion of liquid water transport greatly enhances the predictive capability of the model and is necessary to match experimental data at high current density.Despite several studies on water management in proton exchange membrane ͑PEM͒ fuel cells ͑FCs͒ within the past decade, effective water management has remained elusive. This is partly due to the fact that once liquid water is formed, it is transported within the membrane-electrode-assembly ͑MEA͒ by several co-existing and comparable forces, and therefore, it is extremely difficult to control its motion. The other complication results from the conflict that while liquid water is necessary to maintain high electrical conductivity of the membrane, excessive water can result in clogging of the electrodes. In particular, in a hydrogen-air PEM FC operating at high loads, water is generated at the cathode due to electrochemical reactions, and significant condensation and clogging can occur within the cathode if the liquid water is not managed properly. Thus, it is neither desirable to remove water completely, nor is it desirable to have it in excessive amounts, and this poses a design challenge. The best scenario is to have liquid water in optimum amounts in certain regions of the MEA only, and this is almost impossible to achieve. One can only hope to alleviate the problem by understanding how much water is produced, where it finally resides within the cell, and what effects it has on the performance of the cell. Part of the role of modeling and simulation is to answer these questions.Modeling of liquid water formation and transport has been a topic of intense debate and discussion in the past five years. While such modeling can be extremely useful in understanding some of the aforementioned issues, the models available today are by no means predictive in the truest sense of the word. In this paper, we carefully explore the various ''gray areas'' associated with liquid water formation and transport that make the modeling difficult, and point out their repercussions in the prediction of performance of the FC.Several examples of mathematical modeling of water transport in PEM FCs can be found in the literature. The earliest models 1-3 were semi-empirical in nature, and attempte...

This article presents a rigorous mathematical model to predict performance of proton exchange membrane ͑PEM͒ fuel cells ͑FCs͒ of arbitrary three-dimensional ͑3-D͒ geometry. Mathematical modeling of FCs is necessary in order to understand the precise effect of operating conditions and material properties on the performance of fuel cells. The model is based on solution of the conservation equations of mass, momentum, energy, species, and electric current in a fully integrated finite-volume solver. Simulations are performed in 2-D and 3-D geometries assuming that water stays in its vapor phase and that no liquid water is formed. Results are compared against experimental data under various operating conditions, and show that 3-D modeling is key to predicting performance of PEM FCs at high current densities.

The waste ashes from a commercial biomass combustion facility are successfully converted into mesoporous structured silica utilising a biorefinery approach, with potential high value applications in catalysis, adsorption and separation processes. Potassium silicate solutions are formed via a simple hydrothermal extraction of miscanthus bottom ashes, rich in amorphous silica, with a reproducible extraction of 60-70%. The extension and validation of a rapid and facile infrared method for the quantification of the silicate solutions is demonstrated with important industrial applications for continuous online screening and tuning of the silicate solution ratio and concentration. The alkali solutions from the waste ashes are used for the formation of a structured high surface area mesoporous silica, MCM-41 (1043 m 2 g −1 , 1.12 cm 3 g −1 ). The resulting mesoporous silica was analysed by XRD, N 2 adsorption porosimetry and TEM. † Electronic supplementary information (ESI) available. See

We present a systematic approach to the modeling of rapid thermal processing systems. In this approach, a discretized version of a computer-aided design file of a rapid thermal processing system is incorporated into fundamental physically based models of the transport phenomena to aid in design and optimization of these reactors. These models include a detailed radiative-heat-transfer description which is used to compute radiative exchange factors involving both diffuse and specular surfaces. The radiative exchange factors are then incorporated into transient finite element fluid-flow and heat-transfer models to investigate effects of conductive and convective heat transfer on wafer temperature uniformity. This approach is illustrated in investigations of the effects of thermal guard rings and radiative properties of the chamber on wafer temperature uniformity. Comparisons are made with experiments, and reduced-complexity models are evaluated to identify their range of applicability.

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Abstract-We present a systematic method for developing low order nonlinear models from physically based, large scale finite element models of rapid thermal processing (RTP) systems. These low order models are extracted from transient results of a detailed finite element model using the proper orthogonal decomposition (POD) method. Eigenfunctions obtained from the POD method are then used as basis functions in spectral Galerkin expansions of the governing partial differential equations solved by the finite element model to generate the reduced models. Simulation results with the reduced order models demonstrate good agreement with steady state and transient data generated from the finite element model, with an order of magnitude reduction in execution time.

Abstract-We present a systematic method for developing low order nonlinear models from physically based, large scale finite element models of rapid thermal processing (RTP) systems. These low order models are extracted from transient results of a detailed finite element model using the proper orthogonal decomposition (POD) method. Eigenfunctions obtained from the POD method are then used as basis functions in spectral Galerkin expansions of the governing partial differential equations solved by the finite element model to generate the reduced models. Simulation results with the reduced order models demonstrate good agreement with steady state and transient data generated from the finite element model, with an order of magnitude reduction in execution time.

We present a general purpose Monte Carlo method for the simulation of radiation heat transfer in rapid thermal processing (RTP) chambers. Three-dimensional mesh generation software is used to discretize the surfaces within the system, allowing the simulation of realistic chamber and reflector designs. An adaptive subdivision of the chamber geometry reduces the number of raysurface intersections which must be computed. The method models internal reflection, absorption, and transmission within participating media, and includes wavelength, temperature, and material dependent optical properties. Radiation heat transfer simulations are used to examine a reflector assembly, and to test the assumptions of optical wafer temperature measurement techniques.