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The thermal performance of rural building envelopes is mostly non-standardized in Northern China, resulting in significant heat loss. In this study, we take, as an example, the central area of Liaoning province, with the objective of proposing some low-cost and energy-efficient solutions. Through our investigations, we found that heating energy consumption was reduced by 20% and construction costs increased by less than CNY 8000 (USD 1108), which can be accepted by rural residents. In order to achieve this target, the NSGA-II algorithm integrated with Rhino + Grasshopper and EnergyPlus simulation kernel was used to establish a thermal performance optimization model for the heat transfer of rural building envelopes in this severe cold region. Among the above-calculated Pareto optimal solutions, the recommended thickness of insulation layers for room floors, roofs, and external walls was about 70 mm, 50 mm, and 40 mm, respectively. Furthermore, we tried to reduce the window-to-wall ratio as much as possible. Finally, based on both the lower building renovation cost and energy-saving rate, three technical solutions from which rural residents could select, according to their specific needs, are put forward. [ABSTRACT FROM AUTHOR]

Although some natural fibres have been used in cementitious materials, the performance of cement with natural fibres has been found to be less satisfactory. The strength loss is partially attributed to the water absorbed by the fibres. In order to alleviate this problem, cellulose fibres were chemically modified to reduce its water adsorption capacity. Results show that calcium hydroxide pretreatment reduces the water adsorption capacity to some extent. Fine grinding treatment further reduced water adsorption. The lowest water adsorption was achieved by cuprammonium solution pretreatment. Theoretical calculation of the hydroxyl groups demonstrates the water adsorbed by crystalline region is almost negligible. [ABSTRACT FROM AUTHOR]

This preliminary study developed a novel cellulose pretreatment method for cost-effective cellulosic utilization using a modified cuprammonium solution as a solvent to dissolve cellulose followed by molecular oxygen/Fenton depolymerization. The modified cuprammonium solution is composed of cuprammonium solution and a special catalyst that could efficiently enhance cellulosic oxygen sensitivity and therefore improve cellulosic depolymerization. The molecular oxygen depolymerization and Fenton depolymerization of cellulosic biomass dissolved in the modified cuprammonium solution were investigated. The results demonstrate that the Fenton reaction efficiently depolymerized the cellulose dissolved in the modified cuprammonium solution and reached the monomers with no loss of organic carbon, and almost all the cellulose maintained solubility without reagglomeration after cuprammonium was removed. Molecular oxygen oxidation reduced the cellulose average degree of polymerization (DP) to approximately 4 with less cost, and the oxygen pre-oxidation increased the H2O2 utilization in the Fenton depolymerization and remarkably reduced the H2O2 requirement. [ABSTRACT FROM AUTHOR]

A novel cellulose-based colorimetric sensor (DAC-Tu) with N, S sites for Ag + was prepared. The DAC-Tu exhibited excellent selectivity and sensitivity for Ag + with a naked eyes color change from white to black in mixed metal ions aqueous solutions. The naked-eye in-situ detection limit of DAC-Tu for Ag + was 10 -6  mol/L within 10 min. The cellulose matrix and the grafted functional groups (CS, NH 2 ) of DAC-Tu all contributed to the low naked-eye in-situ detection limit. The mechanism of the visual recognition of DAC-Tu sensor for Ag + was proposed, the N and S atoms of DAC-Tu preferentially coordination chelated with Ag + to form NAg, SAg, and Ag 2 S, and enriched on the cellulose matrix, thus the DAC-Tu presented different color change in response to different concentrations of Ag + . The as-prepared DAC-Tu colorimetric sensor showed a great application prospect for in-situ naked eyes detection of Ag + ., (Copyright © 2020. Published by Elsevier B.V.)