A R C O

ARCO (Algorithms for Recognition of Chemical Objects) is a Computer-Assisted Structure Elucidation (CASE) framework that integrates machine learning and rule-based chemical constraints to generate and rank plausible molecular structures from infrared (IR) spectral data and molecular formula information.

Daniel Villanueva^[1], Luis Armando González-Ortiz^[1], Lisset Noriega^[1] and Gabriel Merino^[1] [1] Departamento de Física Aplicada, Centro de Estudios Avanzados (Cinvestav), Unidad Mérida

IR Peaks (wavenumber, intensity)

Molecular Formula

Machine Learning Model

🔬 Enter IR peaks and a molecular formula to begin elucidation

Functional Group Fragments

Molecular Formula

Fragment

🧪 Select fragments and enter a molecular formula to generate candidates

Research output

Publications

P A P E R S

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A R C O T H E S Y S

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Learn ARCO

Tutorials

⚗️

A R C O I R Tutorial

Learn how to input IR spectral data and molecular formulas to elucidation candidate structures.

Spectroscopy

🧩

A R C O Fragments Tutorial

Generate plausible molecular structures using fragment-based constraints and formula matching.

Structure generation

The team behind ARCO