Cover Image

Phase change materials-based photonic computing /

Phase Change Materials-Based Photonic Computing provides a clear introduction to the field, introducing concepts of photonics, computing, phase change materials and future outlooks.

Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Bhaskaran, Harish, Pernice, Wolfram H. P.
Format: eBook
Language:English
Published: Amsterdam : Elsevier, 2024.
Subjects:
Photonics > Materials.
Photonique > Matériaux.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • Phase Change Materials-Based Photonic Computing
  • Copyright Page
  • Contents
  • List of contributors
  • 1 Introduction to phase change photonics
  • 1.1 Background
  • 1.1.1 Phase change materials and computing
  • 1.1.2 Optoelectronic applications of phase change materials
  • 1.1.3 Photonics-a primer
  • 1.1.4 How this book is organized
  • References
  • 2 Non von Neumann computing concepts
  • 2.1 Introduction
  • 2.2 Essential advances
  • 2.2.1 Many core architecture
  • 2.2.2 Processing in memory
  • 2.2.3 Nonvolatile memory
  • 2.3 Phase change memory
  • 2.3.1 Technology overview
  • 2.3.2 Key computational properties
  • 2.3.2.1 Multilevel memory states
  • 2.3.2.2 Accumulative behavior
  • 2.3.2.3 Nonvolatility of binary states
  • 2.3.3 Nonidealities
  • 2.4 Computational paradigms
  • 2.4.1 Deep learning: a use case of multistate property
  • 2.4.2 Neuromorphic engineering: a use case of accumulative property
  • 2.4.3 Hyperdimensional computing: a use case of nonvolatile binary states property
  • 2.5 Outlook
  • References
  • 3 Photonic computing: an introduction
  • 3.1 Introduction
  • 3.2 Why photonics in computing
  • 3.2.1 Bandwidth
  • 3.2.2 Speed
  • 3.2.3 Latency
  • 3.2.4 Energy efficiency
  • 3.3 Photonic neural networks
  • 3.3.1 Neuron models
  • 3.4 Toward scalable neural networks
  • 3.5 Synapse and its optical implementation
  • 3.6 Interconnection protocols for matrix multiplication
  • 3.6.1 Broadcast-and-weight
  • 3.6.2 Coherent
  • 3.6.3 Free-space diffractive network
  • 3.7 Weight tuning mechanisms and devices
  • 3.8 Other photonic computing models
  • 3.8.1 Photonic reservoir computing
  • 3.8.2 Photonic Ising machine
  • 3.8.3 Photonic quantum computing
  • 3.9 Challenges and current areas of progress
  • 3.9.1 Photonic-electronic integration
  • 3.9.2 New materials and devices
  • 3.9.3 Algorithms
  • References.
  • 4 Configuring phase-change materials for photonics
  • 4.1 Introduction
  • 4.2 Optical switching: optical write, optical read
  • 4.2.1 Light-matter interaction in phase-change materials
  • 4.2.1.1 Electromagnetic heat transfer
  • 4.2.1.2 Thermo-optical effect
  • 4.2.2 Free-space switching
  • 4.2.2.1 Free-space optical switching and readout
  • 4.2.2.2 Free-space optical switching, on-chip optical readout
  • 4.2.3 Full on-chip integration-all-optical phase-change photonics
  • 4.2.3.1 Near-field coupling to phase-change materials
  • 4.2.3.2 Amorphization (Write)
  • 4.2.3.3 Crystallization (Erase)
  • 4.2.3.4 Multilevel optical memory and drift
  • 4.2.3.5 Single-pulse programming
  • 4.2.3.6 Conditioning
  • 4.3 Electrical switching: electrical write, optical read
  • 4.3.1 Direct versus indirect Joule heating
  • 4.3.1.1 Joule heating in conductors
  • 4.3.1.2 Joule heating in phase-change materials
  • 4.3.2 Current-driven direct switching
  • 4.3.2.1 Optical crossbar devices
  • 4.3.2.2 Nanogap
  • 4.3.3 Electro-thermal indirect switching
  • 4.3.3.1 Metal heaters
  • 4.3.3.2 Transparent oxide heaters
  • 4.3.3.3 Doped-silicon heaters and waveguide integration
  • 4.3.3.4 Single-element doping
  • 4.3.3.5 PIN diode heater
  • 4.3.3.6 Graphene microheater
  • 4.3.3.7 Comparison between electro-thermal platforms
  • 4.3.4 Scanning probe lithography
  • 4.3.4.1 Conductive atomic force microscopy-a direct Joule heating method
  • 4.3.4.2 Thermal scanning probe lithography-an indirect Joule heating method
  • 4.3.5 Electron-beam switching
  • 4.4 Mixed-mode devices: optoelectronic write and read
  • 4.4.1 Waveguide-integrated phase-change nanowires
  • 4.4.2 Plasmonic-enhanced mixed-mode devices
  • 4.5 Challenges and future directions
  • Author note
  • References
  • 5 Design and modeling methods for phase-change photonic devices
  • 5.1 Solve for the optical eigenmode.
  • 5.2 Solve for the wave propagation
  • 5.3 Modeling the operational behavior of integrated phase-change photonic devices
  • 5.3.1 Modeling electrical switching of nonvolatile phase-change integrated nanophotonic structures
  • 5.3.2 Modeling optical switching of nonvolatile phase-change integrated nanophotonic structures
  • 5.4 Design strategy: subwavelength patterning and conformal encapsulating
  • 5.4.1 Subwavelength patterning and conformal encapsulating of the PCM-integrated photonic device
  • 5.4.2 Example 1: 1×2 low-loss integrated phase-change photonic switch
  • 5.4.3 Example 2: programmable phase-change metasurface photonic mode converter
  • References
  • 6 New phase-change materials for photonic computing and beyond
  • 6.1 The case for new phase-change materials in photonics
  • 6.2 A close look at Ge2Sb2Te5: the archetypal phase-change alloy
  • 6.3 Performance metrics relevant to photonic applications
  • 6.3.1 Photonic applications of phase-change materials: what makes sense and what does not
  • 6.3.2 Understanding the metrics
  • 6.4 A practical guide for phase-change material engineering
  • 6.4.1 Refractive index contrast between two phases
  • 6.4.2 Optical loss in phase-change materials
  • 6.4.3 Cycle lifetime (endurance)
  • 6.4.4 Switching speed and design trade-offs
  • 6.4.5 Switching energy
  • 6.5 Examples of emerging phase-change materials for photonic applications
  • 6.5.1 Beyond GST-225: alternative stoichiometries in the Ge-Sb-Te family
  • 6.5.2 Ge2Sb2Se4Te1 (GSST): a broadband bi-state transparent phase-change material with large contrast
  • 6.5.3 Sb2S3 and Sb2Se3: low-loss phase-change materials for visible and near-infrared
  • 6.6 Summary and outlook
  • References
  • Further reading
  • 7 Materials modelling: current state-of-the-art for phase-change photonic computing
  • 7.1 Introduction.
  • 7.2 Density-functional-theory molecular dynamics
  • 7.2.1 Density-functional theory
  • 7.2.2 Exchange-correlation functionals
  • 7.2.2.1 Local (spin) density approximation (LDA or LSDA)
  • 7.2.2.2 Generalized gradient approximation
  • 7.2.2.3 Meta-generalized gradient approximation
  • 7.2.2.4 Hybrid functionals
  • 7.2.2.5 Dispersion (van der Waals) corrections
  • 7.3 Machine-learned O(N) interatomic potentials
  • 7.4 ML potentials for phase-change-memory materials
  • 7.5 Bonding in chalcogenides and phase-change-memory materials
  • 7.5.1 Resonant- and metavalent-bonding models
  • 7.5.2 Hyperbonding model
  • 7.5.2.1 Structural analysis of amorphous phase-change-memorys
  • 7.5.2.1.1 Conventional method based on an interatomic-distance criterion
  • 7.5.2.1.2 Structural analysis based on chemical-bonding indicators
  • 7.5.2.1.3 Structural building units
  • 7.5.2.2 Amorphous phase-change-memorys
  • 7.5.2.2.1 Multi-center hyperbonding interaction
  • 7.5.2.2.2 Atomic coordination
  • 7.5.2.2.3 Peierls-distortion-like short- and long-bond geometry
  • 7.5.2.2.4 Impact on dynamical properties
  • 7.5.2.3 Crystalline phase change memory
  • 7.5.2.4 Comparative study on a- and c-PCMs
  • 7.5.2.4.1 Comprehensive description of bonding interactions in GST
  • 7.5.2.4.2 Optical-property contrast
  • 7.5.2.4.3 Chemical-bonding models for PCMs
  • 7.5.2.5 Searching for new phase-change-memories
  • Acknowledgments
  • References
  • 8 Challenges associated with phase-change material selection
  • 8.1 Introduction
  • 8.2 History of phase-change materials
  • 8.3 Working principle and optical contrast
  • 8.4 Requirements of phase-change materials for photonic memory
  • 8.5 Emerging phase-change materials
  • 8.6 Summary and outlook
  • References
  • 9 Summary and outlook
  • Index
  • Back Cover.