An organized compilation of ideas for oneself to communicate strategically and implement practical ideas. Formed and written by Onri Jay Benally in 2025.
This tree of terminologies have been helpful to me over the years in the English-speaking world, and it also contains some of the best adverbs I have found to be effective in speech and literature. Enjoy.
Communication Strategy Tree - by Onri
├─ Reality Alignment
│ ├─ Literally – exact portrayal
│ ├─ Faithfully – integrity-anchored depiction
│ ├─ Metaphorically – figurative framing
│ └─ In its direct or true form – unmediated, canonical phrasing
│
├─ Degree of Certainty
│ ├─ Perhaps – tentative probability
│ ├─ Arguably – defensible, yet contestable, speaker-oriented epistemic stance (hedged assertion)
│ ├─ Relatively – context-bound qualification
│ ├─ Reasonably – logically justified, moderately confident
│ └─ Plausibly – appears possible or credible given current knowledge
│
├─ Extent/ Completeness
│ ├─ Virtually – almost wholly (≈ 99 %)
│ ├─ Practically – nearly, within pragmatic limits (≈ 95 %)
│ └─ Effectively – operationally equivalent in outcome (≈ 95–99 %), results-focused
│
├─ Modal/ Counterfactual Stance
│ ├─ Hypothetically – speculative scenario testing
│ ├─ Theoretically – arithmetically supported, by logic or data-pattern model
│ ├─ Suppose – assumed premise posited for exploration
│ ├─ If it were any different – counterfactual premise introduction
│ └─ On the flip side – alternative-outcome contrast
│
├─ Methodological Lens
│ ├─ Critically – careful, evidence-weighing evaluation of assumptions, sources, causal claims, and alternatives
│ ├─ Analytically – evidence-weighted derivation (systematic)
│ ├─ Systematically – step-wise, protocol-driven approach
│ ├─ Strategically – purpose-aligned planning
│ ├─ At the implementation level – code-/hardware-layer perspective
│ └─ Organically – emerging naturally from context without forced structure
│
├─ Conditionality & Contingency
│ ├─ Conditionally – valid only under stated premise(s)
│ └─ By default – baseline assumption prior to override
│
├─ Ideal-Real Spectrum
│ ├─ Ideally – perfect-world benchmark
│ ├─ Realistically thus far – evidence-based checkpoint
│ └─ Currently deployed – empirically instantiated case
│
├─ Temporal & Agency Orientation
│ └─ Proactively – forward-acting, anticipatory intervention
│
├─ Attention & Salience
│ ├─ Notably – signals noteworthy element
│ ├─ Interestingly – highlights engaging detail
│ └─ Of interest – flags relevant point
│
└─ Norms & Baselines
└─ Conventionally – by established practice or standard usage
Functional Analogy Categories to Help Explain Virtually Anything to a General Audience - by Onri
└─ Root
├─ Analogy Families
│ ├─ LEGO analogy
│ ├─ Gravity-based/ potential energy hill analogy
│ ├─ Basketball analogy
│ ├─ Football/ soccer analogy
│ ├─ Mechanical analogy
│ └─ Car-related analogies
├─ Abstraction & Convergence
│ ├─ Heat map
│ └─ “Spherical cow”
├─ Perception & Analysis
│ ├─ Can be felt or seen
│ └─ Analyzed with dots in a finite dimension
│ └─ Often two-dimensional (2D)
│ └─ Exception: three-dimensional (3D) chess
└─ Communication Reminder
└─ “Say it with your chest.”
Idea Formation Pathways - by Onri
Scaffolding
│ – Pre‑formation of rudimentary tables & smaller trees
│
├─ Formation of hierarchy/ mind‑map/ pathway diagram(s)
│ └─ Decision: which simulation to run?
│ ├─ Steady‑state simulation
│ │ └─ (optional) feed results into scatter‑plot refinement
│ └─ Transient simulation (animated)
│ └─ (optional) feed results into scatter‑plot refinement
│
├─ Formation of heatmap(s)/ action‑consequence diagram(s)
│ └─ (Supplement with a gravity‑hill diagram or a mechanical analogy)
│ └─ Decision: which simulation to run if applicable?
│ ├─ Steady‑state simulation
│ │ └─ (optional) feed results into scatter‑plot refinement
│ └─ Transient simulation (animated)
│ └─ (optional) feed results into scatter‑plot refinement
│
└─ Draft scatter‑plot (based on the initial tables)
└─ Refine scatter‑plot (incorporate data produced by any simulation or literature search)
└─ Comprehensive scatter‑plot (final result)
Towards a Resource Lean Hardware Engineering Strategy - by Onri
Resource-lean Hardware Engineering Strategy
│
├─ Intuition-driven Early Design & Leap-frogging
│ ├─ Do order-of-magnitude checks (size, voltage, frequency, mass)
│ ├─ Rank design levers (material, geometry, feed-through) by one-change impact
│ ├─ Sketch performance barriers (max field, thermal limit) before any simulation
│ ├─ Quick validation: generate a coarse ParaView heat-map from a low-res GDSTK model
│ └─ Update priors; if no equilibrium, inject damping/feedback → closed-loop potential V₍closed-loop₎
│
├─ Open-source Design & Simulation Stack
│ ├─ Geometry definition & parametric CAD → GDSTK (Python API)
│ ├─ 3-D modelling & mesh generation → Blender + Blender-Python scripts
│ ├─ Curve-fitting & Approximation Techniques
│ │ ├─ Polynomial & least-squares fitting (NumPy polyfit, SciPy curve_fit)
│ │ ├─ Rational/ Padé approximants (SciPy, custom Python utilities)
│ │ ├─ Spline & B-spline/ NURBS fitting (SciPy interpolate, NURBS-Python)
│ │ ├─ Robust/ RANSAC regression (scikit-learn) for outlier-tolerant fits
│ │ ├─ Regularized & Bayesian fitting (PyMC, TensorFlow Probability) for
│ │ │ uncertainty-aware models
│ │ ├─ Machine-learning surrogates (Gaussian Processes, lightweight neural nets)
│ │ └─ Hybrid tetrational-Bezier approximation
│ │ • Combines iterated tetration with classic Bezier control points
│ │ • Generates high-order, smooth profiles with very few
│ │ control points → low memory & compute cost
│ ├─ Electromagnetic solver → openEMS (FDTD) consumes GDSTK geometry
│ ├─ Field visualization → ParaView (remote/Colab-linked)
│ ├─ Cloud compute & notebooks → Google Colab (run GDSTK, openEMS, post-process)
│ ├─ Collaborative version control → GitHub (repo, Issues, CI with GitHub Actions)
│ ├─ Optional electronics layout → KiCad (open-source PCB) & FreeCAD (mechanical)
│ ├─ Qiskit Metal – quantum-hardware layout & EM design
│ │ ├─ Open-source Python package (part of the Qiskit ecosystem) for
│ │ │ superconducting qubit, resonator, and package geometry creation.
│ │ ├─ Generates 3-D models that can be exported directly to GDSTK or
│ │ │ to a Blender scene for further meshing.
│ │ ├─ Built-in parametric constraints (trace width, substrate thickness,
│ │ │ coupling gaps) let you explore design space with the same intuition-driven
│ │ │ “one-change’’ ranking used elsewhere.
│ │ ├─ Runs in Google Colab via a pre-built Docker image (GPU optional) – the
│ │ │ notebook pulls Qiskit Metal, builds the layout, and hands the mesh to
│ │ │ openEMS for full-wave simulation.
│ │ ├─ Coupled to Qiskit’s circuit simulators (Aer, Aer-GPU) so you can
│ │ │ co-simulate the quantum circuit (e.g., gate fidelity) together with
│ │ │ the electromagnetic environment (crosstalk, Purcell loss).
│ │ └─ All geometry files, material tables, and simulation results are
│ │ version-controlled in the same GitHub repo as the rest of the project.
│ └─ Advanced low-cost HPC simulation – AWS Palace
│ ├─ Spot-instance EC2 fleet + AWS ParallelCluster for massive FDTD/ Meep sweeps
│ ├─ Pre-baked AMIs that contain openEMS, Meep, GDSTK, Python env. → one-click launch
│ ├─ Job orchestration via AWS Batch/ Step Functions; auto-scale to demand
│ ├─ Input/Output stored on S3 (versioned, cheap, lifecycle-controlled)
│ ├─ Interactive notebook front-end on Amazon SageMaker Studio (or Studio Lab)
│ │ → launch ParaView remote-rendering sessions directly from the notebook
│ ├─ Cost-control: Spot-price alerts, max-price caps, auto-shutdown of idle clusters
│ └─ CI integration – GitHub Actions can trigger a Palace run on every PR,
│ archive results as artefacts, and post a ParaView snapshot as a comment.
│
├─ Open-source Multiphysics & Micromagnetics (Google Colab)
│ ├─ Micromagnetics (GPU-accelerated)
│ │ ├─ MuMax3 – runs natively on Colab GPU runtimes via a Docker image;
│ │ │ Jupyter notebooks drive geometry import (GDSTK → OMF), material tables,
│ │ │ time-step scripts, and automatic post-processing with ParaView.
│ │ ├─ OOMMF – classic CPU-only code; compiled for Linux-x86 and invoked from Colab
│ │ │ using a persistent “/content/oommf” directory; results visualized with
│ │ │ `oommf::boxsi` or exported to VTK for ParaView.
│ │ └─ Fidimag – Python-based micromagnetic framework built on FEniCS; useful for
│ │ research-grade custom energy terms and easy integration with
│ │ SciPy optimisation loops.
│ ├─ Optics/ Photonics (continuum & wave)
│ │ ├─ MEEP (MIT-licensed FDTD) – already packed in the Colab-friendly image;
│ │ │ supports sub-pixel smoothing, dispersive media, and near-field scans.
│ │ ├─ pyMieScatt – analytical Mie-scattering calculations for nanoparticles.
│ │ └─ OpenFDTD/ FDTD-Calc – lightweight wrappers for rapid 2-D/3-D simulations.
│ ├─ Large-scale Magnetics & Induction
│ │ ├─ MagPar – finite-element micromagnetics for bulk magnetic components;
│ │ │ can be compiled on Colab’s Ubuntu environment.
│ │ ├─ Nmag – FEM micromagnetics that couples to PETSc; useful for
│ │ │ multi-physics (magneto-mechanical) studies.
│ │ └─ gprMax – open-source electromagnetic wave propagation (including RF/MW);
│ │ runs on CPU/GPU and can be scripted from Python notebooks.
│ ├─ RF/ Microwave Circuit & Antenna
│ │ ├─ openEMS (already in the stack) - extend with circuit-extraction (S-parameter)
│ │ │ post-processing scripts written in Python.
│ │ ├─ Qucs-S – circuit simulation (SPICE-like) for RF; command-line usage from Colab.
│ │ └─ PyAEDT (open-source wrapper) - can drive an offline install of ANSYS
│ │ Electronics Desktop when a licensed installation is available;
│ │ otherwise fall-back to openEMS.
│ ├─ Mechanical & Multi-physics (continuum)
│ │ ├─ Calculix – FEM for static/dynamic structural analysis;
│ │ │ driven by Python front-end (PyCalculix) and visualized in ParaView.
│ │ ├─ Elmer FEM – supports coupled magneto-thermal-mechanical problems;
│ │ │ scripts run on Colab via a small pre-built Docker image.
│ │ └─ OpenFOAM – CFD (including magnetohydrodynamics) – can be compiled
│ │ and executed on Colab’s CPU nodes; data streamed to ParaView.
│ ├─ Molecular-Dynamics (MD)
│ │ ├─ LAMMPS – general-purpose MD; GPU-accelerated package (`GPU` or `KOKKOS`);
│ │ │ input decks generated from GDSTK geometry → atomistic lattice.
│ │ ├─ GROMACS – biomolecular MD (useful for soft-matter or polymeric
│ │ │ adhesives); runs on Colab GPU with the `gmx_mpi` binary.
│ │ └─ ASE (Atomic Simulation Environment) – Python glue that spawns
│ │ LAMMPS, GPAW, or Quantum ESPRESSO runs and collects results.
│ ├─ Density-Functional Theory (DFT) & Quantum-Scale
│ │ ├─ Quantum ESPRESSO – plane-wave DFT; compiled for Linux x86 on Colab;
│ │ │ used for material-property extraction (permittivity, permeability,
│ │ │ magnetocrystalline anisotropy) that feed into higher-level models.
│ │ ├─ SIESTA – localized-basis DFT, lighter memory footprint for large cells.
│ │ └─ DFTB+ – density-functional tight-binding; fast for preliminary band-structure
│ │ calculations in a resource-lean context.
│ ├─ Hybrid/ Multi-scale Frameworks
│ │ ├─ Multiscale Modeling Toolbox (MMTB) – Python orchestrator that couples
│ │ │ continuum FEM (Calculix/Elmer) ↔ MD (LAMMPS) ↔ DFT (Quantum ESPRESSO).
│ │ ├─ PyMD-Hybrid – template scripts for handing off boundary regions
│ │ │ between micromagnetic (MuMax3) and atomistic (LAMMPS) domains.
│ │ └─ AiiDA – workflow manager that tracks provenance across all the
│ │ above codes, automatically storing inputs/outputs on Git-LFS.
│ └─ Colab-friendly Workflow
│ ├─ Every tool is wrapped in a Jupyter notebook cell that:
│ │ • pulls a Docker image or pre-compiled binary from the repository,
│ │ • mounts the project’s `/content/` directory (shared with Git-Hub),
│ │ • runs the simulation, and
│ │ • writes VTK/CSV results directly to an S3 bucket (or keeps them in the
│ │ notebook runtime for quick ParaView view).
│ └─ Notebook templates (saved in the repo) include:
│ • “Micromagnetics - MuMax3 Demo.ipynb’’,
│ • “Optical-FDTD - MEEP Demo.ipynb’’,
│ • “MD-Cascade - LAMMPS → Quantum ESPRESSO.ipynb’’,
│ • “Hybrid FEM-MD-DFT.ipynb’’,
│ • “Quantum-Hardware - Qiskit Metal Demo.ipynb’’.
│
├─ Resource-lean Fabrication Materials & Processes
│ ├─ Cardboard, corrugated paper, double-sided tape (cheap, biodegradable)
│ ├─ Water-based adhesives/ water-less dry-fit joints
│ ├─ Low-cost sheet plastics (PET, acetate) for moisture barriers
│ ├─ Hobby-grade 3-D printing (PLA/ABS) for functional hinges & enclosures
│ ├─ Laser-cutting from open-source SVG/DXF (Inkscape) → inexpensive batch cuts
│ ├─ Modular origami-inspired foldable patterns designed in Blender
│ ├─ Tape-based Engineering Solutions
│ │ ├─ Tape-based microfluidics
│ │ │ ├─ Define channels by stacking/laminating double-sided adhesive tape
│ │ │ ├─ Cut geometry with a hobby plotter, laser cutter, or craft-knife
│ │ │ ├─ Use wicking paper or PDMS-coated tape as a capillary membrane
│ │ │ ├─ Simple valves: perforated tape patches or pressure-actuated flap tape
│ │ │ └─ Couple reservoirs via zip-lock pouches or blister packs
│ │ ├─ Tape-based low-cost electronics
│ │ │ ├─ Copper-foil adhesive tape for trace routing (DIY flexible PCB)
│ │ │ ├─ Vinyl or polyester tape substrate – waterproof, foldable, inexpensive
│ │ │ ├─ Mount components with conductive epoxy or solder-less pressure-fit pads
│ │ │ ├─ Rapid redesign by peeling/re-positioning tape segments
│ │ │ └─ Integrate with the same adhesive-tape mechanical frames used elsewhere
│ │ └─ Nano-tape (van-der-Waals adhesion)
│ │ ├─ Gecko-inspired nanostructured adhesive film (graphene, polymer nanoribbons, nanocellulose)
│ │ ├─ Cut with laser/plotter; no glue, can be peeled & re-used many times
│ │ ├─ Shear strength > 10 MPa while thickness < 50 µm → essentially invisible bond line
│ │ ├─ Bonds directly to cardboard, PET, copper-foil tape, and 3-D-printed nodes
│ │ └─ Enables “click-and-release’’ assembly of fluidic/electronic modules without permanent fasteners
│ └─ Nanofabrication & Green Lithography
│ ├─ Water-based photoresists (AZ P4620, S1800, “green’’ SU-8 variants)
│ ├─ Egg-white albumen lithography resist (fully biodegradable & <$0.02/ cm²)
│ │ ├─ Mix fresh egg white (≈30 % protein) with a pinch of glycerol (improved adhesion)
│ │ ├─ Spin-coat 5–10 µm film; soft-bake at 80 °C for 2 min
│ │ ├─ UV expose (365 nm) – dose 50–100 mJ cm⁻² (adjustable via IBM Granite 4-generated scripts)
│ │ ├─ Develop in warm de-ionized water (≈30 °C) – 30 s rinse, no toxic chemicals
│ │ └─ Optional post-exposure bake at 100 °C for 1 min to increase contrast
│ ├─ TMAH-free developers – sodium carbonate, NaOH, citric-acid based
│ ├─ DIY spin-coater – 3-D-printed spinner, Arduino-driven motor, speed-control firmware
│ ├─ Low-cost hot-plate bake oven – repurposed soldering-iron base with PID control
│ ├─ Maskless exposure systems
│ │ ├─ Open-source DLP projector or laser-diode scanner
│ │ └─ Pattern-generation software: OpenLAF/ gLith/ PyLitho (Python)
│ ├─ Open-source GDSII/ OASIS layout tools → KLayout Python API, gdsfactory for photonic circuits
│ ├─ Nano-scale simulation → openEMS or Meep (FDTD) for plasmonic/ photonic structures
│ ├─ Documentation & Knowledge Capture
│ │ ├─ Every resist recipe, bake schedule, and exposure-parameter set is uploaded
│ │ │ • as a Markdown page in the project Wiki (auto-generated via GitHub Actions)
│ │ │ • and mirrored in a collaborative Google Doc SOP for quick lab-member access
│ │ └─ Revision history tracked in Git – each edit creates a new Wiki version
│ ├─ AI-assisted code & recipe generation
│ │ ├─ Open-source, memory-efficient LLMs (IBM Granite 4, Granite 4 Micro, etc.) run on local GPU/CPU
│ │ ├─ Used to draft Python spin-coater scripts, exposure-dose calculators,
│ │ │ and to review safety-check checklists
│ │ └─ LLM outputs are gated through a PEP-8/ MISRA-C linting step before merge
│ ├─ Coding & Hardware Design Standards
│ │ ├─ Python code → PEP-8 + Black formatting; C/C++ firmware → MISRA-C/ C++ Core Guidelines
│ │ ├─ PCB design → IPC-2221 (generic) & IPC-7351 (land-pattern) compliance
│ │ ├─ Symbol & schematic convention → IEC 60617 symbols, IEEE 315 naming
│ │ └─ A “standards-matrix’’ Wiki page lists required checks for every PR
│ └─ Green waste handling – aqueous rinse, biodegradable developer disposal,
│ recycling of mask substrates
│
├─ Plug-and-Play (Agnostic) Design Implementation
│ ├─ Contract tables – list inputs, outputs, units, tolerances, latency
│ ├─ Neutral data formats: CSV, JSON, YAML, DOT (graphs), STL/STEP (geometry)
│ ├─ Standard mechanical interface: 0.1-in pitch board-to-board connectors, snap-fit tabs
│ ├─ Solver-agnostic pipelines – swap GDSTK → openEMS ↔ Blender ↔ ParaView any time
│ └─ Python “dependency-injection’’ pattern to hot-swap back-ends
│
├─ Serviceability & Lifecycle Management
│ ├─ Embedded test points, watchdog timers, LED error codes
│ ├─ Health-check scripts run from Colab notebooks or GitHub Actions CI
│ ├─ Versioned configuration files (JSON/YAML) stored side-by-side with code
│ ├─ Raw experiment data + processed results kept together (Git LFS)
│ └─ Design-for-disassembly: labeled modules, snap-fit hardware, tool-free removal
│
├─ Compact Footprint, Mechanical Foldability & Water Compatibility
│ ├─ Origami-style hinges & flexure joints modelled in Blender → STL → 3-D printed
│ ├─ Water-based operation: sealed compartments, passive heat-pipes
│ ├─ Water-less alternatives: phase-change pads, thermally conductive tapes
│ ├─ Cardboard-compatible layouts: foil-coated paper for moisture barrier
│ ├─ Low-cost Structural Support - Tensegrity Engineering
│ │ ├─ Principle: isolated compression rods + tensioned strings
│ │ │ (e.g., carbon-fiber or bamboo rods + fishing-line/ high-modulus polymer cords)
│ │ ├─ Nodes 3-D-printed from PLA/ABS with integrated thumb-screw or snap-fit holes
│ │ ├─ Parametric geometry generated in Blender; static analysis with Calculix,
│ │ │ OpenSees, or Elmer FEM
│ │ ├─ Advantages – high stiffness-to-weight, deployable, fully reversible assembly
│ │ ├─ Use nano-tape at node-string interfaces for glue-free, repeatable bonding
│ │ ├─ Serves as chassis for electronics, heat-pipes, microfluidic panels, sensor arrays
│ │ └─ Scales from tabletop prototypes to metre-scale structures by adjusting rod
│ │ length and string count
│ ├─ Advanced Low-Cost Stabilization – Compliant Mechanisms
│ │ ├─ Monolithic flexure hinges laser-cut from thin PET, FR-4, or 3-D printed PLA/ABS
│ │ ├─ Bistable snap-through origami cells for zero-power latching or toggle switches
│ │ ├─ Low-cost vibration isolator: alternating layers of silicone sheet & cardstock
│ │ ├─ Design workflow
│ │ │ • Parametric model in Blender or OpenSCAD
│ │ │ • FEM analysis with open-source Calculix/ Elmer (or PyElastica for beam theory)
│ │ │ • optimization loop in Python (SciPy, DEAP) to meet target stiffness/ travel
│ │ │ • visualize deformation in ParaView; store results on S3 via AWS Palace
│ │ ├─ Integration points
│ │ │ • Attach compliant mounts to tensegrity nodes using nano-tape → self-aligning chassis
│ │ │ • Use flexure hinges to hold micro-fluidic chips, reducing stress on fragile bonds
│ │ │ • Provide compliant isolation for sensitive electronics (e.g., accelerometers)
│ │ └─ Materials – PET, thin FR-4, flexible TPU, silicone rubber, laminated cardboard-paper
│ │ composites; all <$0.10/ cm² and compatible with laser-cut or 3-D-print processes
│ ├─ Spot Fresnel lens sunlight capture – low-cost extreme-heat collector
│ │ ├─ Generate Fresnel-zone patterns with the hybrid tetrational-Bezier technique
│ │ ├─ Print/laser-cut zones onto thin PET or acrylic sheets (≤ 1 mm) using inexpensive
│ │ │ desktop plotters or DIY DLP exposure.
│ │ ├─ Assemble a lightweight frame (tensgrity or compliant-mechanism-based)
│ │ │ to hold the lens at the optimal focal distance.
│ │ ├─ Integrate passive heat-pipes or high-thermal-conductivity tapes behind the
│ │ │ focal spot to channel concentrated solar energy into a thermal store
│ │ │ (water-less phase-change pads or low-cost metal-plate absorbers).
│ │ └─ Uses only cardboard, PET, minimal adhesive (nano-tape) – keeping cost < $5/ collector.
│ └─ If folding not feasible → rigid-fold linkages or segmented enclosures
│
├─ Biomimicry & Biomimetics (Nature-derived, resource-lean patterns)
│ ├─ Definitions & heuristics
│ │ ├─ Apply biological principles to technical systems; emphasize function transfer over literal copying.
│ │ └─ Favor low-energy, passive, reversible, and repairable patterns first.
│ ├─ Adhesion & bonding
│ │ ├─ Gecko-inspired dry adhesive films (polymer/ nanocellulose micro-/nanopillars) → reusable, high-shear, glue-free.
│ │ └─ Mussel-inspired catechol chemistries (polydopamine coatings) → wet adhesion on metals, glass, PET; water-based recipes.
│ ├─ Surface textures & wetting
│ │ ├─ Lotus-effect superhydrophobic top-coats (spray-on nano-silica + wax) → self-cleaning moisture barriers for paper/PET.
│ │ ├─ Shark-skin riblets (micro-grooved films) → drag reduction in ducts/ microchannels; laser-etched or 3-D-printed skins.
│ │ └─ Insect-wing bactericidal nanospikes (cicada/dragonfly analogues) → antifouling liners for low-cost microfluidics.
│ ├─ Optical & photonic
│ │ └─ Moth-eye sub-wavelength “nipple” arrays on PET/acrylic → anti-reflection for sensors, solar concentrators, and covers.
│ ├─ Thermal management & ventilation
│ │ └─ Termite-mound-inspired chimney + baffle networks in cardboard enclosures → passive CO₂ flushing & day/night pumping.
│ ├─ Structural mechanics & toughness
│ │ ├─ Nacre-like “brick-and-mortar’’ laminates (paper/epoxy, PLA/glass micro-laminates) → impact tolerance with thin, offset bricks.
│ │ └─ Bamboo/ bone gradients → functionally graded lattices (Voronoi, variable-infill) for stiffness-to-weight optimization.
│ ├─ Fluidics & transport networks
│ │ ├─ Leaf-venation fractal manifolds (Murray-law scaling) → uniform distribution & clog-tolerance in tape-based microfluidics.
│ │ └─ Gill-leaflet check valves → PET flap valves for passive one-way flow without power.
│ ├─ Sensing & actuation
│ │ ├─ Whisker-like flow/tactile sensors (cantilever + piezoresistive track) for airflow or contact detection.
│ │ └─ Super-coiled nylon (fishing-line) muscle actuators → low-cost, heat-driven contraction for valves/ linkages.
│ ├─ Bio-based composites & growth
│ │ ├─ Mycelium-based foams/panels grown in molds → lightweight, biodegradable enclosures and vibration liners.
│ │ └─ Chitosan/cellulose laminates → biodegradable flexible substrates, temporary PCBs, or membranes.
│ └─ Bio-inspired algorithms (zero-cost software levers)
│ ├─ Ant-colony/ bee-swarm heuristics → routing, floorplanning, and pick-list optimization.
│ └─ Slime-mold-style network minimization → duct/ manifold topology with minimal material.
│
└─ Community & DIY Ecosystem (Low Barrier to Entry)
├─ Open-source hardware platforms - Arduino, ESP32, Raspberry Pi Pico
├─ Tutorials & notebooks hosted on GitHub Pages, Google Colab, Jupyter Book
├─ Starter-kit BOM: cardboard sheets, tape, low-cost microcontroller, breadboard,
│ 3-D-printer filament, basic hand tools
├─ Collaborative documentation
│ ├─ Project Wiki (Markdown) for design rationales, standards matrix, resistance recipes
│ ├─ Google Docs shared SOPs for safety, spin-coating, bake-out procedures (real-time editing)
│ ├─ Google Sheets for experiment logs, component inventories, and cost tracking
│ └─ Google Slides for quick design briefs, stakeholder presentations, and tutorial decks
├─ AI-enhanced development workflow
│ ├─ IBM Granite 4 (and open-source variants) run locally to suggest code snippets,
│ │ debug scripts, and auto-generate GDSII/ OASIS layout macros
│ └─ All generated code passes through automated linters that enforce PEP-8/ MISRA-C
│ and are reviewed against IPC/ IEC hardware standards before merge
├─ Contribution workflow: issue templates, pull-request reviews, CI testing
└─ License under MIT/ CERN-OHL to encourage remixing and community-driven extensions
| Abbreviation/ Acronym | Meaning |
|---|---|
| 2D | Two-dimensional |
| 3D | Three-dimensional |
| ABS | Acrylonitrile butadiene styrene (thermoplastic polymer) |
| AEDT | Ansys Electronics Desktop |
| AiiDA | Automated Interactive Infrastructure and Database (workflow/provenance platform) |
| AMI | Amazon Machine Image |
| API | Application Programming Interface |
| ASE | Atomic Simulation Environment |
| AWS | Amazon Web Services |
| BOM | Bill of Materials |
| CAD | Computer-Aided Design |
| CFD | Computational Fluid Dynamics |
| CI | Continuous Integration |
| CSV | Comma-Separated Values |
| DFT | Density-Functional Theory |
| DFTB+ | Density-Functional Tight-Binding Plus |
| DLP | Digital Light Processing |
| DOT | Graphviz DOT language (graph description) |
| EC2 | (Amazon) Elastic Compute Cloud |
| EM | Electromagnetics/ electromagnetic |
| FDTD | Finite-Difference Time-Domain (electromagnetics solver method) |
| FEM | Finite Element Method |
| FR-4 | Flame-Retardant 4 (glass-epoxy laminate for PCBs) |
| GDSII | Graphic Design System II (IC layout file format) |
| GDSTK | GDSII/ OASIS Tool Kit (geometry/GDSII/OASIS Python/C++ library) |
| Git LFS | Git Large File Storage |
| GPAW | Grid-based Projector Augmented-Wave (DFT code) |
| GPR | Ground Penetrating Radar |
| GROMACS | GROningen MAchine for Chemical Simulations |
| GPU | Graphics Processing Unit |
| HPC | High-Performance Computing |
| IBM | International Business Machines |
| IEC 60617 | International Electrotechnical Commission 60617 (graphical symbols for diagrams) |
| IEEE 315 | IEEE Std 315 (graphic symbols for electrical/electronics diagrams) |
| IPC-2221 | IPC Generic Standard for Printed Board Design |
| IPC-7351 | IPC Standard for PCB land-pattern (footprint) design |
| JSON | JavaScript Object Notation |
| LAMMPS | Large-scale Atomic/Molecular Massively Parallel Simulator |
| LED | Light-Emitting Diode |
| LLM | Large Language Model |
| MD | Molecular Dynamics |
| MEEP | MIT Electromagnetic Equation Propagation (FDTD solver) |
| MISRA-C | Motor Industry Software Reliability Association – C coding guidelines |
| MMTB | Multiscale Modeling Toolbox |
| MW | Microwave (portion of RF spectrum) |
| NURBS | Non-Uniform Rational B-Splines |
| OASIS | Open Artwork System Interchange Standard (IC layout format) |
| OOMMF | Object Oriented MicroMagnetic Framework |
| OMF | OOMMF magnetization file (file extension commonly used with OVF data) |
| OpenFOAM | Open Field Operation And Manipulation (CFD framework) |
| OVF | OOMMF Vector Field (file format) |
| PALACE | PArallel LArge-scale Computational Electromagnetics (open-source FEM EM solver by AWS) |
| PCB | Printed Circuit Board |
| PDMS | Polydimethylsiloxane |
| PET | Polyethylene terephthalate |
| PETSc | Portable, Extensible Toolkit for Scientific Computation |
| PID | Proportional–Integral–Derivative (control loop) |
| PLA | Polylactic acid (polylactide) |
| PR | Pull Request (version-control collaboration) |
| PyAEDT | Python API for Ansys Electronics Desktop |
| Qucs-S | Qucs with SPICE (SPICE-enabled Qucs circuit simulator) |
| RF | Radio Frequency |
| S3 | (Amazon) Simple Storage Service |
| SIESTA | Spanish Initiative for Electronic Simulations with Thousands of Atoms |
| SOP | Standard Operating Procedure |
| SPICE | Simulation Program with Integrated Circuit Emphasis |
| STEP | Standard for the Exchange of Product model data (ISO 10303) |
| STL | StereoLithography (triangulated mesh file format) |
| SU-8 | Negative epoxy photoresist (SU-8 family) |
| TMAH | Tetramethylammonium hydroxide |
| TPU | Thermoplastic polyurethane |
| UV | Ultraviolet |
| VTK | Visualization Toolkit |