Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Inductive Effects on Chemical Shift: Overview

Inductive Effects on Chemical Shift: Overview

The protons in unsubstituted alkanes are strongly shielded with chemical shifts below 1.8 ppm. Methine, methylene, and methyl protons appear at approximately 1.7, 1.2 and 0.7 ppm, while the proton signal from methane appears at 0.23 ppm. An electronegative substituent, such as chlorine, withdraws the electron density from the protons, increasing their chemical shift. Progressive substitution of the hydrogens in methane by chlorine shifts the proton signals increasingly downfield, to 3.05 ppm in...

MALDI-TOF Mass Spectrometry

MALDI-TOF Mass Spectrometry

Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

Chemical and Solubility Equilibria

Chemical and Solubility Equilibria

The free energy change associated with dissolving a solute in a liter of solvent is called the free energy of a solution, ΔGsolution. The overall ΔGsolution is expressed as the balance of ΔGinteraction against the always-favorable free-energy of mixing, ΔGmixing. Solution formation is favorable if ΔGsolution is less than zero, whereas it is unfavorable if ΔGsolution is greater than zero. In short, for a solution to form and complete dissolution to take place,...

Drug Discovery: Overview

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Modeling takeover decisions in driving automation: a multilevel drift-diffusion model (MDDM) framework integrating human, system, and environmental factors.

Accident; analysis and prevention·2026

Same author

Case Report: Ventriculoperitoneal Shunt Catheter Migration into the Gluteal Muscle.

Frontiers in pediatrics·2026

Same author

Lecanemab treatment modulates brain volume and cerebrospinal fluid pathways in early Alzheimer's disease: Insights from longitudinal magnetic resonance imaging.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same author

Encapsulated droplet array for intensified micromole-scale high-throughput reaction screening.

Nature communications·2026

Same author

Using Machine-Learning and Network Analysis to Investigate the Risk Factors of AI Dependence: The Crucial Role of Escape and Social Motivation.

Behavioral sciences (Basel, Switzerland)·2026

Same author

A Direct ALAD-SSUII Interaction Implies a Potential Link Between Tetrapyrrole and Terpenoid Pathways Toward Chlorophyll Biosynthesis in Plants.

International journal of molecular sciences·2026

Search research articles

Related Experiment Video

Updated: Feb 25, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Use of Machine Learning and Large Language Models in Chemical Information Extraction.

Yufan Chen, Yuxuan Zhang, Haifan Zhou

¹Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, China;

Annual Review of Chemical and Biomolecular Engineering

|February 23, 2026

Summary

This summary is machine-generated.

Automated chemical information extraction from scientific literature accelerates discovery. Advances in machine learning and large language models (LLMs) are key to digitizing chemical science.

Keywords:

chemical information extraction deep learning large language models machine learning vision language models

Related Experiment Videos

Last Updated: Feb 25, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Area of Science:

Chemical informatics
Computational chemistry
Digital transformation in chemistry

Background:

The chemical literature contains vast data crucial for accelerating chemical discovery and optimization.
Manual curation of this data into structured databases is inefficient, time-consuming, and expensive.
Automated methods are needed to unlock the potential of chemical information.

Purpose of the Study:

To review recent advancements in automatic chemical information extraction from literature.
To focus on methods utilizing image and text data modalities.
To guide researchers in applying machine learning and LLM technologies.

Main Methods:

Examined evolution from rule-based and machine learning to large language models (LLMs) and vision language models.
Focused on core tasks: optical chemical structure recognition, reaction diagram parsing, named entity recognition, and experimental procedure extraction.
Highlighted representative methods, benchmark datasets, and challenges like multimodal integration and data annotation.

Main Results:

Identified key trends and limitations in current automated chemical information extraction techniques.
Showcased the progression towards sophisticated LLM and vision language model applications.
Demonstrated the growing importance of multimodal integration and data annotation strategies.

Conclusions:

Automated chemical information extraction frameworks are essential for the digital transformation of chemistry.
LLMs and vision language models represent the state-of-the-art, offering significant improvements.
Future work should focus on robust, scalable, and fully automated systems for chemical data extraction.