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Carbon Dioxide

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Mathematical modeling and numerical simulation of supercritical processing of drug nanoparticles optimization for green processing: AI analysis.

PloS one
In recent decades, unfavorable solubility of novel therapeutic agents is considered as an important challenge in pharmaceutical industry. Supercritical carbon dioxide (SCCO2) is known as a green, cost-effective, high-performance, and promising solven...

Imitating the respiratory activity of the brain stem by using artificial neural networks: exploratory study on an animal model of lactic acidosis and proof of concept.

Journal of clinical monitoring and computing
Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute volume during spontaneous breathing after being trained using data from an animal model of...

Production of high calorific value hydrogen-rich combustible gas by supercritical water gasification of straw assisted by machine learning.

Bioresource technology
This article reveals the basic laws of straw supercritical water gasification (SCWG) and provides basic experimental data for the effective utilization of straw. The paper studied the impact of three operational conditions on the production of high-c...

Co-firing characteristic prediction of solid waste and coal for supercritical CO power cycle based on CFD simulation and machine learning algorithm.

Waste management (New York, N.Y.)
The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO (S-CO) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, a...

Forecasting carbon dioxide emissions in Chongming: a novel hybrid forecasting model coupling gray correlation analysis and deep learning method.

Environmental monitoring and assessment
Predicting regional carbon dioxide (CO2) emissions is essential for advancing toward global carbon neutrality. This study introduces a novel CO2 emissions prediction model tailored to the unique environmental, economic, and energy consumption of Shan...

Artificial intelligence can regulate light and climate systems to reduce energy use in plant factories and support sustainable food production.

Nature food
Plant factories with artificial lighting (PFALs) can boost food production per unit area but require resources such as carbon dioxide and energy to maintain optimal plant growth conditions. Here we use computational modelling and artificial intellige...

Leveraging experimental and computational tools for advancing carbon capture adsorbents research.

Environmental science and pollution research international
CO emissions have been steadily increasing and have been a major contributor for climate change compelling nations to take decisive action fast. The average global temperature could reach 1.5 °C by 2035 which could cause a significant impact on the e...

Global forecasting of carbon concentration through a deep learning spatiotemporal modeling.

Journal of environmental management
Given the global urgency to mitigate climate change, a key action is the development of effective carbon concentration reduction policies. To this end, an influential factor is the availability of accurate predictions of carbon concentration trends. ...

Optimizing the early-stage of composting process emissions - artificial intelligence primary tests.

Scientific reports
Although composting has many advantages in treating organic waste, many problems and challenges are still associated with emissions, like NH, CO and HS, as well as greenhouse gases such as CO. One promising approach to enhancing composting conditions...