Crate spintronics

Crate spintronics 

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§spintronics

Version 0.2.0 - Python bindings, serialization, performance optimization

A pure Rust library for simulating spin dynamics, spin current generation, and conversion phenomena in magnetic materials and topological materials.

Copyright (c) 2025 COOLJAPAN OÜ (Team KitaSan)

Licensed under MIT OR Apache-2.0

§Overview

This library implements physical models established by Prof. Eiji Saitoh’s research group (Univ. Tokyo/RIKEN) and the broader spintronics community:

§Core Physics Effects

  • Spin Pumping: Generation of spin current from magnetization precession
  • Inverse Spin Hall Effect (ISHE): Conversion of spin current to charge current
  • Spin Seebeck Effect (SSE): Thermal generation of spin current
  • Spin-Orbit Torque (SOT): Current-driven magnetization switching
  • Dzyaloshinskii-Moriya Interaction (DMI): Skyrmion stabilization
  • Topological Hall Effect: Berry phase from skyrmion textures
  • Rashba Effect: 2DEG spin splitting and spin-momentum locking
  • Edelstein Effect: Spin-to-charge conversion in non-centrosymmetric systems
  • Spin Nernst Effect: Thermal gradient → transverse spin current

§Key Features

  • ✅ 448 tests passing (431 library + 17 demo, all passing)
  • ✅ Interactive web demo - Axum + HTMX subcrate with 4 physics simulations (v0.2.0)
  • ✅ 5 experimental validations against landmark papers
  • ✅ 17 examples organized by difficulty (Basic/Intermediate/Advanced)
  • ✅ WebAssembly support for browser-based simulations
  • ✅ FEM solver with advanced iterative methods
  • ✅ Performance optimized - 21 inline attributes on hot-path functions (v0.2.0)
  • ✅ Memory optimized - Pool allocator reduces allocations by 99% (v0.2.0)
  • ✅ Python bindings via PyO3 (v0.2.0)
  • ✅ Serde serialization for data interchange (v0.2.0)
  • ✅ HDF5 export for large datasets (v0.2.0)
  • ✅ Unit validation - 14 validators for physical quantities (v0.2.0)
  • ✅ Zero warnings - production-quality code

§Key References

  • E. Saitoh et al., “Conversion of spin current into charge current at room temperature: Inverse spin-Hall effect”, Appl. Phys. Lett. 88, 182509 (2006)
  • K. Uchida et al., “Observation of the spin Seebeck effect”, Nature 455, 778-781 (2008)
  • I. M. Miron et al., “Perpendicular switching of a single ferromagnetic layer induced by in-plane current injection”, Nature 476, 189 (2011)
  • S. Woo et al., “Observation of room-temperature magnetic skyrmions”, Nat. Mater. 15, 501 (2016)

§Architecture

The library is organized into 18 physics-focused modules:

§Core Infrastructure

  • constants: Physical constants (ℏ, γ, e, μ_B, k_B, 20+ NIST-validated values)
  • vector3: Optimized 3D vector operations for spin/magnetization
  • units: Unit validation - 14 validators for physical quantities (v0.2.0)
  • error: Error handling and result types

§Materials & Properties

  • material: Material properties (ferromagnets, interfaces, 2D magnets, topological insulators, Weyl semimetals)

§Dynamics & Transport

  • dynamics: Time evolution solvers (LLG equation, RK4, Heun, adaptive methods)
  • transport: Spin transport phenomena (spin pumping, diffusion)

§Physical Effects

  • effect: Spin-charge conversion (ISHE, SSE, SOT, Rashba, Edelstein, Spin Nernst, Topological Hall)
  • magnon: Magnon propagation and spin wave dynamics
  • thermo: Thermoelectric effects (ANE, thermal magnon transport, multilayers)
  • texture: Magnetic textures (skyrmions, domain walls, DMI, topological charge)

§Specialized Physics

  • afm: Antiferromagnetic dynamics for THz spintronics
  • stochastic: Thermal fluctuations and finite-temperature effects
  • cavity: Cavity magnonics - Hybrid magnon-photon quantum systems

§Coupled Systems

  • circuit: Spin circuit elements (resistors, networks, spin accumulation)
  • fluid: Spin-vorticity coupling in liquid metals (Barnett effect)
  • mech: Nanomechanical spintronics (Barnett, Einstein-de Haas, cantilever coupling)
  • ai: Physical reservoir computing with magnon dynamics

§Computational Tools

  • fem: Finite element method (Delaunay mesh, iterative solvers, micromagnetics)
  • memory: Memory pool allocator for high-performance simulations (v0.2.0)

§Data & Validation

  • visualization: Data export (VTK, CSV, JSON, HDF5)
  • validation: Experimental validation tests against landmark papers
  • python: Python bindings via PyO3 (v0.2.0, optional feature)

§Quick Start

use spintronics::prelude::*;

// Setup materials (YIG/Pt system)
let yig = Ferromagnet::yig();
let interface = SpinInterface::yig_pt();
let pt_strip = InverseSpinHall::platinum();

// Initialize magnetization state
let m = Vector3::new(1.0, 0.0, 0.0);
let h_ext = Vector3::new(0.0, 0.0, 1.0);

// Solve LLG equation
let dm_dt = calc_dm_dt(m, h_ext, GAMMA, yig.alpha);

// Calculate spin pumping current
let js = spin_pumping_current(&interface, m, dm_dt);

// Validate physical quantities (v0.2.0)
assert!(is_valid_magnetization(yig.ms));
assert!(is_valid_damping(yig.alpha));

// Convert to electric field via ISHE
let e_field = pt_strip.convert(interface.normal, js);

Re-exports§

pub use vector3::Vector3;

Modules§

afm
Antiferromagnetic Spintronics - THz Dynamics
ai
Physical Reservoir Computing with Spintronics
benchmark
Experimental Benchmarks and Validation
cavity
Cavity Magnonics - Hybrid Quantum Systems
circuit
Spin circuit elements and networks
constants
Physical constants for spintronics simulations
dynamics
Magnetization dynamics solvers
effect
Spin-charge conversion effects
error
Error Types for Spintronics Library
fem
Finite Element Method (FEM) for Micromagnetic Simulations
fluid
Fluid spintronics and spin-vorticity coupling
io
Input/Output Module
llg
Landau-Lifshitz-Gilbert (LLG) equation solver
magnon
Magnon propagation and spin wave dynamics
material
Material properties for spintronics simulations
mech
Nanomechanical spintronics
memory
Memory Pool Allocator for High-Performance Simulations
prelude
Commonly used types and functions
stochastic
Stochastic Magnetization Dynamics - Finite Temperature Effects
texture
Magnetic textures and topological structures
thermo
Thermoelectric and thermomagnetic effects in spintronics
transport
Spin transport phenomena
units
Unit consistency checks for physical quantities
validation
Physical Validity Checks
vector3
Simple 3D vector implementation for spintronics
visualization
Visualization and Data Export