Oxidation of cellulose in pressurized carbon dioxide

This work presents first results upon oxidation of type II cellulose by nitrogen dioxide dissolved in carbon dioxide at high pressure. This reaction leads to oxidized cellulose, a natural-based bioresorbable fabric used for biomedical applications. The oxidation reaction takes place in a heterogeneous fluid–solid system. Kinetics of oxidation is presented here and effects of operating conditions such as pressure, temperature and initial moisture content of cellulose are investigated. Results are presented in terms of degree of oxidation of cellulose and quality of the final oxidized cellulose, which has been characterized using liquid-state and solid-state 13C NMR. The experimental results show the existence of possible secondary reactions which may lead to oxidized cellulose with insufficient mechanical strength. An attempt is made to evidence and understand the role of CO2 as a solvent in this system. Indeed, although supercritical CO2 appears to be a suitable candidate as a solvent for oxidation reactions, some inhibiting effect on nitrogen dioxide activity are observed in this case

Turbo-XZ Algorithm: Low-Latency Decoders for Quantum LDPC Codes

International audienceWe propose a low latency hardware-friendly decoding framework for Calderbank-Shor-Steane (CSS) quantum lowdensity parity-check (QLDPC) codes under the depolarizing noise model. With a given latency constraint, the proposed decoder, referred to generally as the Turbo-XZ decoding algorithm utilizes the correlation of Pauli X and Z errors. In this framework, we introduce early stopping and switching decoders to meet latency constraints and improve error correction performance for different decoders including the bit-flip (BF), fixed BF (proposed hardware-friendly variant of BF), and normalized min-sum algorithm (nMSA). This decoding framework allows various tradeoffs in terms of latency, complexity, and decoding performance which are discussed briefly. Simulation results show that the BF-Turbo-XZ decoder performs close to (and beyond in some cases) the nMSA version with lower complexity and latency. Our proposed fixed BF approach reduces complexity with minimal performance degradation. For example with a generalized bicycle code, nMSA performs better for higher depolarizing values (p > 0.02) at a higher cost, while low-complexity BF-Turbo-XZ decoders are better at low depolarizing values