conformer

A conformer, short for conformational isomer, is one of the distinct three-dimensional arrangements of a molecule that can be interconverted into another arrangement by rotation about single chemical bonds. Conformers retain the same connectivity and stereochemistry at all chiral centers, but differ in torsional angles and overall energy.

Molecules rapidly interconvert between conformers at moderate temperatures when the barriers to rotation are small. The relative stability of conformers is described by their energies, and populations follow the Boltzmann distribution. Common examples include ethane, which has lower-energy staggered forms and higher-energy eclipsed forms, and butane, which favors the anti conformer with several gauche conformers as less populated. Cyclohexane features chair and boat forms, with the chair conformation being the most stable. Conformational changes can influence reactivity, binding interactions, and physical properties.

Techniques used to study conformers include computational methods such as molecular mechanics and quantum chemical calculations, as well as experimental approaches like NMR spectroscopy. Conformational analysis helps explain reaction mechanisms, conformational preferences in supramolecular assemblies, and the behavior of biomolecules in different environments.

Conformer also denotes a neural network architecture used in speech recognition, introduced by Google researchers in 2020. The Conformer architecture blends convolutional neural networks with the Transformer, aiming to capture both local and global dependencies in audio data. It uses convolutional blocks to model local context and combines feed-forward networks with self-attention to capture longer-range patterns. Conformer has been applied to end-to-end automatic speech recognition and related audio processing tasks, delivering strong performance with computational efficiency.

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