This review paper comprehensively examines the dynamic landscape of 3D printing and
Machine Learning utilizing biodegradable polymers and their composites, presenting a …

The growing potential of sustainable materials such as polyhydroxyalkanoates (PHAs),
polylactic acid (PLA), alginate, carrageenan, and ulvan for bioplastics production presents …

Hybrid modeling, with an appropriate blend of the mechanistic and data‐driven framework,
is increasingly being adopted in bioprocess modeling, model‐based experimental design …

Microbial polyhydroxyalkanoates (PHA) are encouraging biodegradable polymers, which
may ease the environmental problems caused by petroleum-derived plastics. However …

In recent years, the integration of mechanistic process models with advanced machine
learning techniques has led to the development of hybrid models, which have shown …

The utilization of biochar derived from biomass residue to enhance anaerobic digestion (AD)
for bioenergy recovery offers a sustainable approach to advance sustainable energy and …

With recent advances in digitisation and big data analytics, more pharmaceutical firms are
adopting digital tools to achieve modernisation. The biological phenomena within …

Biopolymers from renewable materials are promising alternatives to the traditional
petroleum-based plastics used today, although they face limitations in terms of performance …

Deep learning is emerging in many industrial sectors in hand with big data analytics to
streamline production. In the biomanufacturing sector, big data infrastructure is lagging …

While plastics have brought considerable convenience to our daily lives, most of them are
still made up of petroleum-based materials. The plastic production industry accounts for a …