AIMC Topic: Cellulose

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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
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...

High-Adhesive Hydrogel-Based Strain Sensor in the Clinical Diagnosis of Anterior Talofibular Ligament Sprain.

ACS sensors
Anterior talofibular ligament (ATFL) sprain is one of the most prevalent sports-related injuries, so proper evaluation of ligament sprains is critical for treatment options. However, existing tests suffer from a lack of standardized quantitative eval...

Advanced machine learning-driven characterization of new natural cellulosic Lablab purpureus fibers through PCA and K-means clustering techniques.

International journal of biological macromolecules
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
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.)
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
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
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
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 ...

High-throughput prediction of stalk cellulose and hemicellulose content in maize using machine learning and Fourier transform infrared spectroscopy.

Bioresource technology
Cellulose and hemicellulose are key cross-linked carbohydrates affecting bioethanol production in maize stalks. Traditional wet chemical methods for their detection are labor-intensive, highlighting the need for high-throughput techniques. This study...

An artificial intelligence handheld sensor for direct reading of nickel ion and ethylenediaminetetraacetic acid in food samples using ratiometric fluorescence cellulose paper microfluidic chip.

International journal of biological macromolecules
User-friendly in-field sensing protocol is crucial for the effective tracing of intended analytes under less-developed countries or resources-limited environments. Nevertheless, existing sensing strategies require professional technicians and expensi...