AIMC Topic: Powders

Clear Filters Showing 11 to 20 of 61 articles

Methodology for quality risk prediction for milk powder production plants with domain-knowledge-involved serial neural networks.

Food chemistry
In dairy enterprises, predicting product quality attributes that are influenced by operating parameters is a major task. To reduce quality loss in production, a prediction-based quality control method is proposed in this study. In particular, a seria...

Data-driven insights into the properties of liquisolid systems based on machine learning algorithms.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Liquisolid systems (LS) represent a formulation approach where liquid drug or its dispersion is transformed into a powder with good flowability and compactibility, leading to enhanced drug dissolution and bioavailability. Many research groups have fo...

Virtual screening of drug materials for pharmaceutical tablet manufacturability with reference to sticking.

International journal of pharmaceutics
The manufacturing of pharmaceutical solid dosage forms, such as tablets involves a large number of successive processing operations including crystallisation of the drug substance, granulation, drying, milling, mixing of the formulation, and compacti...

Smart laser Sintering: Deep Learning-Powered powder bed fusion 3D printing in precision medicine.

International journal of pharmaceutics
Medicines remain ineffective for over 50% of patients due to conventional mass production methods with fixed drug dosages. Three-dimensional (3D) printing, specifically selective laser sintering (SLS), offers a potential solution to this challenge, a...

Explainable AI: Machine Learning Interpretation in Blackcurrant Powders.

Sensors (Basel, Switzerland)
Recently, explainability in machine and deep learning has become an important area in the field of research as well as interest, both due to the increasing use of artificial intelligence (AI) methods and understanding of the decisions made by models....

Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques.

Scientific reports
Discriminating different cultivars of maca powder (MP) and detecting their authenticity after adulteration with potent adulterants such as maize and soy flour is a challenge that has not been studied with non-invasive techniques such as near infrared...

Geographical discrimination of Asian red pepper powders using H NMR spectroscopy and deep learning-based convolution neural networks.

Food chemistry
This study investigated an innovative approach to discriminate the geographical origins of Asian red pepper powders by analyzing one-dimensional H NMR spectra through a deep learning-based convolution neural network (CNN). H NMR spectra were collecte...

Image-based simultaneous particle size distribution and concentration measurement of powder blend components with deep learning and machine vision.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of ...

An overview of the implementation of SeDeM and SSCD in various formulation developments.

International journal of pharmaceutics
The Sediment Delivery Model explains experimental analysis and quantitative assessment of the powdered substance characterizing parameters, which offer pertinent data about the material's appropriateness for direct compression (DC) of tablet, which i...

Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar.

PloS one
Using solid waste in building materials is an efficient approach to achieving sustainability goals. Also, the application of modern methods like artificial intelligence is gaining attention. In this regard, the flexural strength (FS) of cementitious ...