The separation of a toluene/methanol/water ternary mixture is a difficult task due to the toluene/water and toluene/methanol azeotropes. In this article, low-energy pervaporation is proposed for the separation of the ternary azeotrope toluene-methanol-water. This work investigates the effects of feed temperature, feed flow rate, and vacuum on pervaporation and compares the energy consumption of pervaporation with that of distillation. The results showed that at the optimized flow rate of 50 L/h and a permeate side vacuum of 60 kPa at 50 °C, the water and methanol content in the permeate was about 63.2 wt.% and 36.8 wt.%, respectively, the water/ methanol separation factor was 24.04, the permeate flux was 510.7 g/m·h, the water content in the feed out was reduced from 2.5 wt.% to less than 0.66 wt.%, and the dehydration of toluene methanol could be realized. Without taking into account the energy consumption of pumps and other power equipment, pervaporation requires an energy consumption of 43.53 kW·h to treat 1 ton of raw material, while the energy consumption of distillation to treat 1 ton of raw material is about 261.5 kW·h. Compared to the existing distillation process, the pervaporation process consumes much less energy (about one-sixth of the energy consumption of distillation). There is almost no effect on the surface morphology and chemical composition of the membrane before and after use. The method provides an effective reference for the dehydration of organic solvents from ternary mixtures containing toluene/methanol/water.
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http://dx.doi.org/10.3390/membranes14060139 | DOI Listing |
Nat Comput Sci
January 2025
IBM Research Europe, Rüschlikon, Switzerland.
Large language models (LLMs), with their remarkable generative capacities, have greatly impacted a range of fields, but they face scalability challenges due to their large parameter counts, which result in high costs for training and inference. The trend of increasing model sizes is exacerbating these challenges, particularly in terms of memory footprint, latency and energy consumption. Here we explore the deployment of 'mixture of experts' (MoEs) networks-networks that use conditional computing to keep computational demands low despite having many parameters-on three-dimensional (3D) non-volatile memory (NVM)-based analog in-memory computing (AIMC) hardware.
View Article and Find Full Text PDFSci Rep
January 2025
School of Economics and Management, Nanchang University, Nanchang, 330031, China.
The growth in carbon emissions poses a severe challenge to global sustainable development, making it imperative to explore the impacts of economic restructuring and technological progress on Carbon Emission Performance (CEP). However, existing studies often lack an integrated analysis of economic restructuring and technological progress, while giving limited attention to the indirect role of Environmental Regulation (ER). This study constructs a multidimensional theoretical framework, breaking down economic restructuring into four dimensions-industrial structure, factor input, ownership, and new-type urbanization (NTU), and refining technological progress into technological innovation and energy efficiency.
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January 2025
Institute of Developing Economy, Japan External Trade Organization, Chiba, 2618545, Japan.
Carbon emission research based on input-output tables (IOTs) has received attention, but data quality issues persist due to inconsistencies between the sectoral scopes of energy statistics and IOTs. Specifically, China's official energy data are reported at the industry level, whereas IOTs are organized by product sectors. Valid IOT-based environmental models require consistent transformation from industry-level to product-level emissions.
View Article and Find Full Text PDFFood Chem Toxicol
January 2025
Military Nutrition Division, US Army Research Institute of Environmental Medicine, Natick, MA, USA. Electronic address:
Caffeine is a popular stimulant, predominantly consumed from beverages. The caffeinated beverage marketplace is continually evolving resulting in considerable interest in understanding the impact caffeinated beverages have on levels of intakes. Therefore, estimates of caffeine intakes in the U.
View Article and Find Full Text PDFSci Total Environ
January 2025
Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China; Jilin Provincial Key Laboratory of Water Resources and Environment, Jilin University, Changchun 130021, China; College of New Energy and Environment, Jilin University, Changchun 130012, China; School of Earth and Environmental Sciences, Cardiff University, Cardiff CF10 3AT, UK. Electronic address:
Composing regional total income jointly with government income, private income represents levels of development and affluence from the household perspective. Considering the need for fair carbon emission reduction responsibility distributions among regions with divergent income levels, private income-embedded emission (PIEE) and the inter-regional inequalities remain to be explored. Combining input-output analysis and the Gini coefficient, this study traces the sources and disposals of regional private income in China, as well as their embedded carbon emission flow, and quantifies the distribution and inequality of PIEE across industrial sectors and provincial regions.
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