Recent advances and application of machine learning in food flavor prediction and regulation
H Ji, D Pu, W Yan, Q Zhang, M Zuo, Y Zhang - Trends in Food Science & …, 2023 - Elsevier
Background Food flavor is a key factor affecting sensory quality. Predicting and regulating
flavor can result in exceptional flavor characteristics and improve consumer preferences and …
flavor can result in exceptional flavor characteristics and improve consumer preferences and …
Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective
Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …
fossil-based power and industrial sectors and is a bridging technology for a sustainable …
Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors
Artificial intelligence (AI), machine learning (ML), and data science are leading to a
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
Exploring the potential of time-series transformers for process modeling and control in chemical systems: an inevitable paradigm shift?
N Sitapure, JSI Kwon - Chemical Engineering Research and Design, 2023 - Elsevier
The last two years have seen groundbreaking advances in natural language processing
(NLP) with the advent of applications like ChatGPT, Codex, and ChatSonic. This revolution …
(NLP) with the advent of applications like ChatGPT, Codex, and ChatSonic. This revolution …
Recent advances in deep learning for retrosynthesis
Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and
drug manufacturing access to poorly available and brand‐new molecules. Conventional rule …
drug manufacturing access to poorly available and brand‐new molecules. Conventional rule …
Introducing hybrid modeling with time-series-transformers: A comparative study of series and parallel approach in batch crystallization
N Sitapure, J Sang-Il Kwon - Industrial & Engineering Chemistry …, 2023 - ACS Publications
Given the hesitance surrounding the direct implementation of black-box tools due to safety
and operational concerns, fully data-driven deep-neural-network (DNN)-based digital twins …
and operational concerns, fully data-driven deep-neural-network (DNN)-based digital twins …
A review on artificial intelligence enabled design, synthesis, and process optimization of chemical products for industry 4.0
With the development of Industry 4.0, artificial intelligence (AI) is gaining increasing attention
for its performance in solving particularly complex problems in industrial chemistry and …
for its performance in solving particularly complex problems in industrial chemistry and …
Generative ai and process systems engineering: The next frontier
This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …
such as large language models (LLMs), can enhance solution methodologies within process …
SUSIE: Pharmaceutical CMC ontology-based information extraction for drug development using machine learning
V Mann, S Viswanath, S Vaidyaraman… - Computers & Chemical …, 2023 - Elsevier
Automatically extracting information from unstructured text in pharmaceutical documents is
important for drug discovery and development. This information can be integrated with …
important for drug discovery and development. This information can be integrated with …
Key Directions for Development of Modern Expert Systems
Анотація The paper reviews areas of application modern expert systems, on basis of which
advantages and disadvantages of using ES are considered; main components of typical ES …
advantages and disadvantages of using ES are considered; main components of typical ES …