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Phase Transitions

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Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...

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Related Experiment Video

Updated: Jul 12, 2025

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

Roadmap for phase change materials in photonics and beyond.

Patinharekandy Prabhathan^1,2, Kandammathe Valiyaveedu Sreekanth³, Jinghua Teng³

¹Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore.

|October 19, 2023

Summary

Phase Change Materials (PCMs) enable reconfigurable micro-nanophotonic devices across the electromagnetic spectrum. This review covers PCM materials, devices, and applications from terahertz to visible frequencies.

Keywords:

Applied physics Materials application Physics

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Last Updated: Jul 12, 2025

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

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Area of Science:

Optoelectronics
Materials Science
Nanotechnology

Background:

Phase Change Materials (PCMs) are crucial for advanced micro-nanophotonic devices.
PCMs offer tunable functionalities across terahertz to visible frequencies.
Reconfigurable photonic devices require novel material platforms.

Purpose of the Study:

To provide a comprehensive roadmap of Phase Change Materials in micro-nanophotonics.
To review material and device aspects of PCMs for photonic applications.
To explore diverse applications and future directions for PCMs.

Main Methods:

Review of existing literature on PCMs in photonics.
Analysis of material properties and device configurations.
Discussion of optimization techniques, including deep learning-based metasurface design.

Main Results:

PCMs facilitate active and reconfigurable photonic devices.
Integration with Photonic Integrated Circuits and electric-driven PCMs are key advancements.
Deep learning enhances metasurface design for PCMs.

Conclusions:

PCMs are pivotal for multifunctional photonic devices.
Promising applications include non-volatile memory, optical data storage, and neuromorphic computing.
PCMs are essential for future innovations in photonics, energy, and electronics.