AIMC Topic: Cellulose
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Data-driven insights for enhanced cellulose conversion to 5-hydroxymethylfurfural using machine learning.
Bioresource technology
Apr 23, 2025
Converting cellulose into 5-Hydroxymethylfurfural (HMF) provides a promising strategy for creating bio-based chemicals, offering sustainable alternatives to petroleum-based materials in polymers, biofuels, and pharmaceuticals. However, the efficient ...
Biofabrication of HepG2 Cells-Laden 3D Structures Using Nanocellulose-Reinforced Gelatin-Based Hydrogel Bioinks: Materials Characterization, Cell Viability Assessment, and Metabolomic Analysis.
ACS biomaterials science & engineering
Apr 16, 2025
The successful replication of the intricate architecture of human tissues remains a major challenge in the biomedical area. Three-dimensional (3D) bioprinting has emerged as a promising approach for the biofabrication of living tissue analogues, taki...
Cell Wall-Based Machine Learning Models to Predict Plant Growth Using Onion Epidermis.
International journal of molecular sciences
Mar 24, 2025
The plant cell wall (CW) is a physical barrier that plays a dual role in plant physiology, providing structural support for growth and development. Understanding the dynamics of CW growth is crucial for optimizing crop yields. In this study, we emplo...
Targeted conversion of cellulose and hemicellulose macromolecules in the phosphoric acid/acetone/water system: An exploration of machine learning evaluation and product prediction.
International journal of biological macromolecules
Mar 8, 2025
The simultaneous hydrolysis of cellulose and hemicellulose involves trade-offs, making precise control of hydrolysis products crucial for sustainable development. This study employed three machine learning (ML) models-Random Forest (RF), Extreme Grad...
Advanced machine learning-driven characterization of new natural cellulosic Lablab purpureus fibers through PCA and K-means clustering techniques.
International journal of biological macromolecules
Mar 2, 2025
The increasing demand for sustainable and eco-friendly materials has spurred significant interest in natural fibers as alternatives to synthetic reinforcements in composite applications. This study aims to explore the potential of Lablab purpureus fi...
Explainable artificial intelligence-based compressive strength optimization and Life-Cycle Assessment of eco-friendly sugarcane bagasse ash concrete.
Environmental science and pollution research international
Mar 1, 2025
Investigations on the potential use of sustainable sugarcane bagasse ash (SCBA) as a supplementary cementitious material (SCM) in concrete production have been carried out. The paper employs model agnostic eXplainable Artificial Intelligence (XAI) to...
Predicting oleogels properties using non-invasive spectroscopic techniques and machine learning.
Food research international (Ottawa, Ont.)
Feb 26, 2025
Oleogelators are considered food additives that require approval from regulatory authorities. Therefore, classifying these ingredients that may have characteristics (e.g., waxiness), cost and origin (e.g., animal or vegetable) is crucial to ensure co...
Application of supervised learning models for enhanced lead (II) removal from wastewater via modified cellulose nanocrystals (CNCs).
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Jan 16, 2025
Heavy metal ions are acknowledged to impact the environment and human health adversely. CNCs are effective materials for removing heavy metal ions in industrial applications and process innovations since they can be used in static and dynamic adsorpt...
In silico formulation optimization and particle engineering of pharmaceutical products using a generative artificial intelligence structure synthesis method.
Nature communications
Nov 7, 2024
Pharmaceutical drug dosage forms are critical for ensuring the effective and safe delivery of active pharmaceutical ingredients to patients. However, traditional formulation development often relies on extensive lab and animal experimentation, which ...
Biosorption of cobalt and chromium from wastewater using manganese dioxide and iron oxide nanoparticles loaded on cellulose-based biochar: Modeling and optimization with machine learning (artificial neural network).
International journal of biological macromolecules
Oct 28, 2024
In this study, two nanomaterials with excellent adsorption capacities were developed to remove heavy metals efficiently from wastewater. Manganese dioxide MnO nanoparticles and iron oxide FeO nanoparticles were successfully synthesized using cassava ...
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