This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …

This study introduces two novel Reinforcement Learning (RL) agents for the design and
optimization of chemical process flowsheets (CPFs): a discrete masked Proximal Policy …

This work provides an overview of recent applications of Machine Learning (ML) to process
systems engineering problems related to sustainability. The review is organized by the type …

The startling success of ChatGPT and other large language models (LLMs) using
transformer-based generative neural network architecture in applications such as natural …

This study introduces a Reinforcement Learning (RL) approach for generating, designing,
and controlling chemical process flowsheets (CPFs). The proposed RL framework makes …

Control structure design is an important but tedious step in P&ID development. Generative
artificial intelligence (AI) promises to reduce P&ID development time by supporting …

The applicability of superstructure optimization to process synthesis is often limited to simple
models and flowsheets. The state operator network (SON)(Smith and Pantelides, 1995) …

Nanomaterials, with their unique properties at the nanoscale, have significant potential to
revolutionize various fields, including healthcare, electronics, and energy. This chapter …

Process flowsheet synthesis and design involves simultaneously solving several problems,
including determining the unit operations and their sequence, underlying reactions and …

We present a string representation for hybrid extraction and distillation using symbols
representing phenomena building blocks. Unlike the conventional equipment-based string …