Acid catalyzed carbohydrate degradation and dehydration

Facile commercial production of versatile polyfunctional compounds from biomass constitutes a great challenge for establishing a sustainable chemical industry. One such example is the production of furfural and hydroxymethyl furfural via dehydration of pentoses and hexoses. Identified as primary building blocks in polymer industry, their massive production is highly desired, yet suffers from several problems, such as feedstock availability, low product yields due to excessive side reactions and lack of an industrially feasible heterogeneous catalyst. Organic acid functional groups incorporated onto mesoporous silica offer well defined catalytic sites beside their unique textural properties and therefore could be considered as promising catalysts. However, a rational approach for fine tuning of the catalyst to meet the reaction system requirements entails detailed understanding of the nature of the catalytic sites in condensed phase under similar conditions mimicking the reaction environment. For the characterization in condensed phase, a methodology was developed using potentiometric titration, and the acidic strength and total acid capacity of the organic acid functionalized materials were determined. Organic acid moieties of different strength were able to display their own acidity without being leveled in water, strongest being arene sulfonic group followed by propyl sulfonic, ethyl phosphonic and butyl carboxylic. When compared to literature, some discrepancy was noticed about the acidic strength of propyl sulfonic and arene sulfonic groups. Because most of these studies were focused on examining the interaction of the acidic group with a gas phase probe molecule, the effect of solvation was neglected. The effect of solvation on the acidic strength of these moieties was investigated via quantum chemical simulations. A change in the acidic strength trend was observed with the increasing number of water molecules, indicating that one-to-one interaction in the gas phase does not necessarily represent the interaction of the moiety with the solvent molecules. The difference in the acidic strength for these organic acid groups incorporated into mesoporous silica was not observed when they were tested for their activity on hexose and pentose dehydration due to poor hydrothermal stability of the materials at elevated temperatures. Doping of sulfated zirconia onto mesoporous silica materials was another alternative due to their high activity in cellobiose hydrolysis, but these materials did not provide hydrothermal stability either. Monosaccharide decomposition parameters with mesoporous silica materials could not be thoroughly validated with previously reported data due to the lack of systematic studies in literature. A systematic study with mineral and organic homogeneous acids of varying strength built the platform for catalyst comparison and revealed that different mechanisms were dominating for glucose decomposition in the presence of weak acids according to the pH value of the solution. Although lower acid concentration leads to higher selectivity toward HMF, this could not be considered as an industrially viable solution. Alternatively, addition of alkaline earth metals and appliance of pressure in the presence of acid catalyst activated the glucose ring and resulted in high HMF yields. Further enhancement was obtained by addition of an organic phase for HMF extraction. This process also allows for combining it with polysaccharides hydrolysis and one pot HMF production from biomass. By further optimization of the parameters, an industrially feasible process for HMF production can be achieved

Exact solution of a one-dimensional continuum percolation model

I consider a one dimensional system of particles which interact through a hard core of diameter \si and can connect to each other if they are closer than a distance $d$. The mean cluster size increases as a function of the density $\rho$ until it diverges at some critical density, the percolation threshold. This system can be mapped onto an off-lattice generalization of the Potts model which I have called the Potts fluid, and in this way, the mean cluster size, pair connectedness and percolation probability can be calculated exactly. The mean cluster size is S = 2 \exp[ \rho (d -\si)/(1 - \rho \si)] - 1 and diverges only at the close packing density \rho_{cp} = 1 / \si . This is confirmed by the behavior of the percolation probability. These results should help in judging the effectiveness of approximations or simulation methods before they are applied to higher dimensions.Comment: 21 pages, Late

A spatial mixed Poisson framework for combination of excess-of-loss and proportional reinsurance contracts

In this paper a purely theoretical reinsurance model is presented, where the reinsurance contract is assumed to be simultaneously of an excess-of-loss and of a proportional type. The stochastic structure of the set of pairs (claim’s arrival time, claim’s size) is described by a Spatial Mixed Poisson Process. By using an invariance property of the Spatial Mixed Poisson Processes, we estimate the amount that the ceding company obtains in a fixed time interval in force of the reinsurance contract

Superimposed Renewal Processes in Reliability

This paper reviews the existing literature on the superimposed renewal process, with its foci on probabilistic and statistical properties, statistical inference, and applications in reliability analysis and maintenance policy optimisation. It then proposes future research topics

Bayesian off-line detection of multiple change-points corrupted by multiplicative noise : application to SAR image edge detection

This paper addresses the problem of Bayesian off-line change-point detection in synthetic aperture radar images. The minimum mean square error and maximum a posteriori estimators of the changepoint positions are studied. Both estimators cannot be implemented because of optimization or integration problems. A practical implementation using Markov chain Monte Carlo methods is proposed. This implementation requires a priori knowledge of the so-called hyperparameters. A hyperparameter estimation procedure is proposed that alleviates the requirement of knowing the values of the hyperparameters. Simulation results on synthetic signals and synthetic aperture radar images are presented

A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems