/* maglab.jsx — MagLab research toolchain card + case-study page. "AI for Science as a lab instrument, not a demo prompt." github.com/TaewoooPark/MagLab MagLab is a harness platform for magnetism / spintronics research. The LLM layer plans, routes, explains, and drafts; deterministic domain modules do the actual scientific work (physics formulae, unit conversion, material lookup, simulation pipelines, fitters, figure renderers, literature connectors, SCPI safety checks, data lineage, review workflows). On the site this lives at two surfaces: 1. MagLabCard — a wide bento on /research, between papers and tooling 2. MagLabPage — /research/maglab, an interactive datasheet that: - lists the 5 manifesto principles with cross-links to features - renders the 8-layer pipeline as an isometric multilayer stack (hover lifts; ↑↓ buttons reorder; click expands) - walks the 10-stage research lifecycle by pointer X - plays 5 example research-loop CLI sequences - shows 15+ effect models as a 4×4 schematic catalog - prints the verifiable-orchestrator architecture as ASCII art - closes with 5 pillars and a one-line install strip No comparison table, no §01–§03 prose blocks. The page IS the instrument's datasheet. */ const { useState: useStateML, useEffect: useEffectML, useMemo: useMemoML, useRef: useRefML } = React; const MAGLAB_REPO = "https://github.com/TaewoooPark/MagLab"; /* ---- Data ------------------------------------------------------ */ const ML_MANIFESTO = [ { id: "tools", title: "LLM reasons, tools compute", feature: "physics oracle · honesty gate · DataPoint", layerIds: ["physics", "fitting", "sim"] }, { id: "numbers", title: "Every number is verifiable", feature: "formula module · unit conversion · physics-range checks", layerIds: ["physics", "fitting"] }, { id: "citations", title: "Every citation is real", feature: "OpenAlex · Semantic Scholar · arXiv · Crossref", layerIds: ["lit"] }, { id: "figures", title: "Every figure is reproducible", feature: "FigureSpec JSON · vector · journal styles · data lineage", layerIds: ["figures"] }, { id: "results", title: "Every result has provenance", feature: "W3C PROV ledger · ELN entries · append-only artifacts", layerIds: ["fitting", "authoring"] }, ]; /* 8 pipeline layers, top-down on the page = closest-to-paper (Comms) at the top, closest-to-keyboard (Terminal UX) at the bottom. The stack reads like a magnetic multilayer schematic: each layer is a stripe. */ const ML_LAYERS_SEED = [ { id: "comms", name: "Communications", brief: "slides · posters · emails — always marked for review", tools: ["LaTeX", "PowerPoint", "Word", "smolagents"], principles: ["citations", "figures"] }, { id: "authoring", name: "Authoring", brief: "manuscripts · cover letters · revisions · rebuttals", tools: ["LaTeX", "Word", "LiteLLM"], principles: ["citations", "results"] }, { id: "figures", name: "Figures", brief: "FigureSpec JSON · vector · journal styles · primitives", tools: ["Matplotlib", "SciencePlots", "PyVista", "CairoSVG"], principles: ["figures"] }, { id: "fitting", name: "Analysis & Fit", brief: "effect registry · lmfit · symmetry · ELN hook", tools: ["lmfit", "SciPy", "pandas", "Pydantic"], principles: ["numbers", "results"] }, { id: "sim", name: "Simulation", brief: "DFT → atomistic → micromagnetic → device handoff", tools: ["Ubermag", "OOMMF", "magnum.np", "Paramiko"], principles: ["numbers", "results"] }, { id: "physics", name: "Physics & Mat", brief: "formulae · units · oracle · materials registry", tools: ["NumPy", "SciPy", "Pydantic", "PROV"], principles: ["tools", "numbers"] }, { id: "lit", name: "Literature", brief: "OpenAlex · Semantic Scholar · arXiv · Crossref", tools: ["KeyBERT", "LanceDB", "scikit-learn"], principles: ["citations"] }, { id: "term", name: "Terminal UX", brief: "Typer · Rich · prompt_toolkit", tools: ["Python", "Typer", "Rich", "pyfiglet"], principles: ["tools"] }, ]; /* 10 lifecycle stages, ordered left → right like the cycle on the MagLab hero poster (image1). */ const ML_LIFECYCLE = [ { id: "lit", name: "Literature", hint: "Search/audit across OpenAlex, Semantic Scholar, arXiv, Crossref. Build an evidence matrix." }, { id: "materials", name: "Materials", hint: "Query magnetic materials, build multilayer stacks, exchange-length / FMR / DW formulae." }, { id: "physics", name: "Physics", hint: "Formula evaluation, unit conversion, physics oracle before downstream work." }, { id: "sim", name: "Simulation", hint: "DFT → atomistic → micromagnetic → device-scale handoff with validated specs." }, { id: "fit", name: "Fitting", hint: "AMR · AHE · ST-FMR · FMR/Kittel · damping · spin pumping · DMI · DW · skyrmion · hysteresis · Curie-T." }, { id: "analysis", name: "Analysis", hint: "Effect model registry · symmetry · consistency · DataPoint lineage." }, { id: "instr", name: "Instruments", hint: "PyVISA scaffolds · SCPI safety check · manual RAG ingest · script generation." }, { id: "figures", name: "Figures", hint: "FigureSpec JSON · vector · journal-aware styles · schematic primitives." }, { id: "authoring", name: "Authoring", hint: "Manuscripts · cover letters · revision letters · rebuttals · grants — marked for review." }, { id: "comms", name: "Communications", hint: "Slides · posters · emails · abstracts — always marked for human review." }, ]; const ML_LOOPS = [ { id: "lit-to-plan", title: "Literature → experiment plan", cmds: [ "maglab lit search papers/pt_cofeb_mgo --top-n 40", "maglab lit authors \"spin orbit torque CoFeB MgO\"", "maglab lab plan \"SOT efficiency in Pt/CoFeB/MgO\" --n-doe 16 --output sot_plan.yaml", ] }, { id: "meas-fit-fig", title: "Measurement → fit → figure", cmds: [ "maglab analyze load data/stfmr.csv --columns frequency,field,voltage", "maglab fit --effect stfmr data/stfmr.csv --method least_squares", "maglab sim plot data/stfmr.csv --journal aps --format pdf --output figures/stfmr.pdf", ] }, { id: "multiscale", title: "Multiscale handoff", cmds: [ "maglab sim dft --structure bcc_fe --engine qe --calc-type jij", "maglab sim atomistic --engine vampire --j-ij-k 398 --t-max-k 1300", "maglab sim pipeline --structure bcc_fe --scales dft,atomistic,micro,device --backend mock", ] }, { id: "instr", title: "Instrument workflow", cmds: [ "maglab instr ingest \"Keithley 2400\" --manual-path manuals/k2400.pdf", "maglab instr skillgen \"Keithley 2400\" --safety-model keithley-2400", "maglab instr script \"Keithley 2400\" --description \"field sweep Hall voltage\"", "maglab instr check hall_sweep.py", ] }, { id: "authoring", title: "Verified result → manuscript", cmds: [ "maglab write \"ST-FMR fit gives xi_DL=0.12 with provenance IDs ...\" --journal prl --dry-run", "maglab comms cover-letter --journal \"Physical Review Letters\" --title \"SOT in Pt/CoFeB/MgO\"", "maglab present slides \"Key results from the SOT study\" --template aps-12min --format beamer --n-slides 10", ] }, ]; const ML_EFFECTS = [ { id: "amr", name: "AMR", glyph: "hall-bar" }, { id: "ahe", name: "AHE", glyph: "hall-arrow" }, { id: "ohe", name: "OHE", glyph: "hall-linear" }, { id: "phe", name: "PHE", glyph: "hall-cross" }, { id: "smr", name: "SMR", glyph: "bilayer" }, { id: "usmr", name: "USMR", glyph: "bilayer-arrow" }, { id: "stfmr", name: "ST-FMR", glyph: "lorentzian" }, { id: "fmr", name: "FMR / Kittel", glyph: "kittel" }, { id: "alpha", name: "Damping", glyph: "lorentzian-w" }, { id: "ishe", name: "Spin pump · ISHE", glyph: "spin-pump" }, { id: "dmi", name: "DMI", glyph: "spiral" }, { id: "dw", name: "Domain wall", glyph: "domain-wall" }, { id: "sky", name: "Skyrmion / Thiele", glyph: "skyrmion" }, { id: "hyst", name: "Hysteresis", glyph: "hyst-loop" }, { id: "tc", name: "Curie-T", glyph: "tc-curve" }, ]; const ML_PILLARS = [ { id: "cli", name: "CLI-first", hint: "Reproducible. Every step is a command on disk." }, { id: "ver", name: "Verifiable", hint: "Physics oracle + honesty gate gate every number." }, { id: "prov", name: "Provenance", hint: "W3C PROV ledger + DataPoint lineage." }, { id: "int", name: "Integrity", hint: "No hallucinations. No fabrications." }, { id: "os", name: "Open science", hint: "Open data, open code, open release." }, ]; /* ---- Schematic primitives — 15+ tiny SVG glyphs ---------------- */ function MlGlyph({ kind, size = 36 }) { const sw = 1; const s = size; const c = "currentColor"; const v = (x) => (x / 36) * s; // scale helper if we ever change size switch (kind) { case "hall-bar": return ( ); case "hall-arrow": return ( ); case "hall-linear": return ( ); case "hall-cross": return ( ); case "bilayer": return ( ); case "bilayer-arrow": return ( ); case "lorentzian": return ( ); case "kittel": return ( ); case "lorentzian-w": return ( ); case "spin-pump": return ( ); case "spiral": return ( ); case "domain-wall": return ( ); case "skyrmion": return ( ); case "hyst-loop": return ( ); case "tc-curve": return ( ); default: return null; } } /* ---- Manifesto list (5 principles) ----------------------------- */ function ManifestoList({ hoverIdx, onHover, onLeave }) { return (
    {ML_MANIFESTO.map((p, i) => { const active = hoverIdx === i; return (
  1. onHover && onHover(i)} onMouseLeave={() => onLeave && onLeave()} style={{ display: "grid", gridTemplateColumns: "20px 1fr", gap: 12, padding: "10px 0", borderTop: i === 0 ? "1px solid var(--line-soft)" : "0", borderBottom: "1px solid var(--line-soft)", color: active ? "var(--fg)" : "var(--fg)", background: active ? "var(--line-soft)" : "transparent", transition: "background 220ms var(--easing-default)", }}> ▶
    {t(p.title)}
    {p.feature}
    2. ); })}
); } /* ---- Multilayer Stack — 8-layer isometric pipeline ------------- */ function MultilayerStack({ activeLayerIds, onLayerHover }) { const [layers, setLayers] = useStateML(ML_LAYERS_SEED); const [hoverIdx, setHoverIdx] = useStateML(null); const [openIdx, setOpenIdx] = useStateML(null); const move = (i, dir) => { setLayers((prev) => { const j = i + dir; if (j < 0 || j >= prev.length) return prev; const next = prev.slice(); [next[i], next[j]] = [next[j], next[i]]; return next; }); // keep focus on the moved layer setOpenIdx((cur) => (cur === i ? i + dir : (cur === i + dir ? i : cur))); }; const onEnter = (i) => { setHoverIdx(i); onLayerHover && onLayerHover(layers[i].id); }; const onLeave = () => { setHoverIdx(null); onLayerHover && onLayerHover(null); }; return (
{t("Fig. 01 · Pipeline stack")}
{t("Eight layers, top of stack = closest to paper.")}
{t("hover to lift · ↑↓ to reorder · click to expand")}
{layers.map((layer, i) => { const isHover = hoverIdx === i; const isOpen = openIdx === i; const isLinked = activeLayerIds && activeLayerIds.has(layer.id); const lifted = isHover || isLinked || isOpen; return (
onEnter(i)} onMouseLeave={onLeave} onClick={() => setOpenIdx(isOpen ? null : i)} data-cursor="link" data-cursor-label={t(isOpen ? "Close" : "Expand")} style={{ border: "1px solid var(--fg)", background: lifted ? "var(--fg)" : "var(--bg)", color: lifted ? "var(--bg)" : "var(--fg)", marginLeft: `calc(${i} * 14px)`, transform: lifted ? "translateY(-3px)" : "translateY(0)", transition: "transform 240ms var(--easing-default), background 240ms var(--easing-default), color 240ms var(--easing-default)", cursor: "pointer", userSelect: "none", }}>
{t(layer.name)}
{t(layer.brief)}
{`#${String(layers.length - i).padStart(2, "0")}`}
{isOpen && (
{t("Tool stack")}
{layer.tools.map((tool) => ( {tool} ))}
{t("Principles enforced here")}
    {layer.principles.map((pid) => { const p = ML_MANIFESTO.find((mp) => mp.id === pid); return p ? (
  • ▶ {t(p.title)}
    • ) : null; })}
)}
); })}
); } /* ---- Lifecycle Flow — 10 stages, mouse-X scrub ----------------- */ function LifecycleFlow() { const [stageIdx, setStageIdx] = useStateML(0); const wrapRef = useRefML(null); const stage = ML_LIFECYCLE[stageIdx]; const onMove = (e) => { if (!window.__hasHover) return; const r = wrapRef.current.getBoundingClientRect(); const f = Math.max(0, Math.min(1, (e.clientX - r.left) / r.width)); const idx = Math.min(ML_LIFECYCLE.length - 1, Math.floor(f * ML_LIFECYCLE.length)); setStageIdx(idx); }; return (
{t("Fig. 02 · Research lifecycle")}
{t("Ten stages. Mouse along the row to scrub.")}
{t("hover or tap a stage")}
{ML_LIFECYCLE.map((s, i) => { const active = i === stageIdx; return ( ); })}
{String(stageIdx + 1).padStart(2, "0")} · {t(stage.name)}
{t(stage.hint)}
); } /* ---- Research Loop Strip — 5 vertical sequences ---------------- */ function ResearchLoopStrip() { const [openIdx, setOpenIdx] = useStateML(0); return (
{t("Fig. 03 · Example research loops")}
{t("Five sequences, all command-line.")}
{t("click a row to inspect the command sequence")}
{ML_LOOPS.map((loop, i) => { const open = openIdx === i; return (
{open && (
{loop.cmds.map((c, ci) => (
${c}
))}
)}
); })}
); } /* ---- Effect Catalog Grid — 15 effects in a 4×4 specimen row ---- */ function EffectCatalogGrid() { const [active, setActive] = useStateML(0); const a = ML_EFFECTS[active]; return (
{t("Fig. 04 · Effect catalog")}
{t("Fifteen spintronic effects, one fit registry.")}
{t("hover or tap a cell to inspect")}
{ML_EFFECTS.map((eff, i) => { const isActive = i === active; return ( ); })}
{t("Effect")}
{a.name}
{t("Fit command")}
$maglab fit --effect {a.id} DATA.csv
); } /* ---- Orchestrator Diagram — ASCII-style verifiable harness ----- */ function OrchestratorDiagram() { const nodes = [ { id: "intent", label: "Researcher intent", hint: "A question, a draft, a measurement, a hypothesis." }, { id: "surface", label: "CLI · REPL · MCP · gateways", hint: "Terminal-first; the same surface works for chat, IDE, and bot front-ends." }, { id: "orch", label: "Orchestrator · subagents · skills · checkpoints", hint: "Plan, route, budget, persist. Where LLMs reason." }, { id: "gate", label: "Physics oracle · honesty gate · DataPoint · PROV", hint: "Verification layer. Nothing leaves without provenance." }, { id: "engines", label: "Deterministic engines", hint: "physics · materials · simulation · analysis · figures · instruments" }, { id: "apps", label: "Lifecycle applications", hint: "literature · lab notebook · review · authoring · communications" }, { id: "output", label: "Human-reviewed scientific output", hint: "Always marked for review. Inspectable later." }, ]; const [activeId, setActiveId] = useStateML("gate"); const active = nodes.find(n => n.id === activeId) || nodes[0]; return (
{t("Fig. 05 · Verifiable orchestrator")}
{t("Where the LLM thinks vs. where the lab decides.")}
{t("hover a layer to read its responsibility")}
{nodes.map((n, i) => { const isActive = n.id === activeId; return (
setActiveId(n.id)} data-cursor="link" data-cursor-label={t(n.label)} style={{ padding: "10px 12px", background: isActive ? "var(--fg)" : "transparent", color: isActive ? "var(--bg)" : "var(--fg)", border: isActive ? "1px solid var(--fg)" : "1px solid var(--line-soft)", cursor: "pointer", transition: "background 180ms var(--easing-default), color 180ms var(--easing-default)", }}> {String(i + 1).padStart(2, "0")} {n.label}
); }).reduce((acc, el, i, arr) => { acc.push(el); if (i < arr.length - 1) { acc.push(
↓
); } return acc; }, [])}
※ {t("On this layer")}
{t(active.label)}
{t(active.hint)}
{t("The verification layer is not the mission statement. It is the safety rail that lets MagLab be useful in scientific work.")}
); } /* ---- Five Pillars Strip --------------------------------------- */ function FivePillarsStrip() { return (
{ML_PILLARS.map((p, i) => (
{String(i + 1).padStart(2, "0")} · {t(p.name)}
{t(p.hint)}
))}
); } /* ---- MagLabCard — research-page bento card -------------------- */ function MagLabCard({ onClick }) { const ref = useRefML(null); const [hover, setHover] = useStateML(false); const [phase, setPhase] = useStateML(0); // gentle idle tick — a top-down sweep highlights one layer at a time useEffectML(() => { let raf; const start = performance.now(); const tick = (now) => { const elapsed = (now - start) / 1000; const cyc = 6; setPhase((elapsed % cyc) / cyc); raf = requestAnimationFrame(tick); }; raf = requestAnimationFrame(tick); return () => cancelAnimationFrame(raf); }, []); const liveIdx = Math.floor(phase * ML_LAYERS_SEED.length); return (
setHover(true)} onMouseLeave={() => setHover(false)} data-cursor="link" data-cursor-label={t("View Project")} className="ml-card" style={{ border: "1px solid var(--line)", background: "var(--bg)", padding: 28, display: "grid", gridTemplateColumns: "1.1fr 1fr 1fr", gap: 28, cursor: "pointer", alignItems: "center", minHeight: 220, }}> {/* left — mini multilayer stack schematic */}
{/* middle — title + tagline */}
{t("02b · Toolchain · Open source")}
MagLab
{t("Magnetism and spintronics research lifecycle copilot.")}
{/* right — tagline + stack + cycle pointer */}
※ {t("Manifesto")}
{t("LLM reasons. Tools compute. Every number, citation, figure, and result has provenance.")}
Python · Ubermag · OpenAlex · lmfit · LiteLLM · MCP
{`▸ ${ML_LAYERS_SEED[liveIdx].name}`}
); } /* ---- MagLabPage — the case-study page ------------------------ */ function MagLabPage() { useLang(); const { go } = useRouter(); const [hoverPrincipleIdx, setHoverPrincipleIdx] = useStateML(null); const activeLayerIds = useMemoML(() => { if (hoverPrincipleIdx == null) return null; return new Set(ML_MANIFESTO[hoverPrincipleIdx].layerIds); }, [hoverPrincipleIdx]); return (
{t("Case study · MagLab")} {t("GitHub ↗ TaewoooPark/MagLab")}
{/* Hero — title left, AI-for-Science rationale right */}

MAGLAB

{t("MAGNETISM AND SPINTRONICS RESEARCH LIFECYCLE COPILOT_")}

{t("A harness platform for spintronics research. The LLM plans, routes, explains, and drafts. Domain modules — formulae, units, materials, simulations, fitters, figure renderers, literature connectors, SCPI safety checks, provenance ledgers — do the actual scientific work.")}

{t("\"AI for Science as a lab instrument, not a demo prompt.\"")}

{t("Why does AI for Science need a harness?")}

{t("Modern research is no longer limited only by ideas. It is limited by coordination overhead — too many papers to audit, too many file formats, too many unit conventions, too many simulation backends, too many figure revisions, and too much undocumented context living in lab notebooks, scripts, and memory.")}

{t("A useful scientific AI system therefore cannot be a chatbot. It needs a controlled environment where language models ask for deterministic tools, receive structured results, preserve provenance, and expose enough of the process for a scientist to inspect it.")}

{t("MagLab treats the LLM as an orchestration layer, not the source of scientific truth. Numerical values come from formulae, fitters, simulations, datasets, literature records, or explicit user input. Figures are vector artifacts bound to data and provenance — not generated raster guesses.")}

{/* Fig.01 — Pipeline stack (left) + Manifesto principles (right) */}
※ {t("Five manifesto principles")}
{t("Rules the pipeline must obey.")}
setHoverPrincipleIdx(null)} />
{t("hover a principle — the pipeline layers that enforce it lift on the left")}
{/* § 01 — Research bottlenecks the harness addresses */}
§ 01 — {t("What it helps with")}
{t("Ten bottlenecks of a real spintronics project.")}

{t("MagLab does not chase a leaderboard score. It targets the slow parts of research that no benchmark captures — auditing literature, translating material stacks into parameters, checking units, handing off between simulation scales, fitting spintronic effects, producing reproducible figures, scripting instruments, keeping an electronic lab notebook, reviewing manuscripts, and turning verified results into communication artifacts.")}

  • · {t("Literature overload — OpenAlex / Semantic Scholar / arXiv / Crossref evidence matrix")}
  • · {t("Material and unit friction — physics oracle, multilayer builder, CGS↔SI conversion")}
  • · {t("Simulation handoff — DFT → atomistic → micromagnetic → device spec")}
  • · {t("Fitting and interpretation — 15-effect registry, lmfit, bounds, residuals")}
  • · {t("Figure reproducibility — FigureSpec, vector renderers, journal styles")}
  • · {t("Instrument scripting — PyVISA scaffold, SCPI validation, safety checks")}
  • · {t("Lab memory — ELN entries, measurement plans, DOE next steps")}
  • · {t("Review and critique — persona review, anomaly explanation, disclosure")}
  • · {t("Authoring — manuscript, cover letter, revision, rebuttal, abstract, grant")}
  • · {t("Orchestration — REPL, Ralph loops, MCP, subagents, gateways, checkpoints")}
{/* § 02 — Loops, not one-shots */}
§ 02 — {t("Loops, not one-shots")}

{t("Research is a loop, not a prompt. A paper folder becomes a plan. A plan becomes a measurement. A measurement becomes a fit. A fit becomes a figure. A figure becomes a manuscript. Each step calls deterministic tools, each output gets a DataPoint, and the orchestrator decides what runs next.")}

{t("The Ralph loops, MCP server/client, subagents, skills, gateway bots, cost tracking, and checkpoints are not productivity polish. They are how a multi-step research process stays inspectable when an LLM is in the middle of it.")}

{/* § 03 — One fit registry */}
§ 03 — {t("One fit registry")}

{t("AMR, AHE, OHE, PHE, SMR, USMR, ST-FMR, FMR/Kittel, damping, spin pumping/ISHE, DMI, domain-wall, skyrmion/Thiele, hysteresis, and Curie-temperature models are fit through the same registry. Same loader, same lmfit backend, same parameter-bounds machinery, same ELN/provenance hooks.")}

{t("A user can run maglab analyze model to inspect the model, then maglab fit --effect data.csv. The output is a fitted parameter set, a residuals report, and a DataPoint — not a paragraph of LLM speculation.")}

{/* § 04 — Honesty gate */}
§ 04 — {t("Honesty gate")}

{t("Before a number, a citation, or a figure leaves the harness, it passes through the physics oracle, the honesty gate, the DataPoint store, and a W3C PROV ledger. The verification layer is not the mission statement. It is the safety rail that lets MagLab be useful in scientific work.")}

{t("Without this rail, a research-grade LLM agent is just a faster way to publish wrong things. With it, the loop becomes auditable — every value points back to a deterministic source, every citation resolves, every figure has a recipe.")}

{/* § 05 — Open invitation */}
§ 05 — {t("Open source, open invitation")}

{t("MagLab ships under a permissive license. The CLI runs without LLM credentials for any module that is itself offline — formula evaluation, unit conversion, material lookup, fitting, figure rendering, ELN, provenance inspection. LLM-driven planning, drafting, and review activate when keys are configured.")}

{t("If you study magnetism, spin transport, multilayers, domain walls, skyrmions, or related device physics — and you want your AI tooling to be a lab instrument instead of a chat window — clone the repository, run maglab doctor, and start the loop.")}

{/* One-row install strip — no comparison table */}
{t("Try it")}
git clone …/MagLab && uv sync && .venv/bin/python -m maglab --help
{t("Python · MIT-style license · Ubermag · OpenAlex · LiteLLM")}
{t("github.com/TaewoooPark/MagLab →")}
); } Object.assign(window, { MagLabPage, MagLabCard, ML_MANIFESTO, ML_LAYERS_SEED, ML_LIFECYCLE, ML_LOOPS, ML_EFFECTS, ML_PILLARS, MlGlyph, ManifestoList, MultilayerStack, LifecycleFlow, ResearchLoopStrip, EffectCatalogGrid, OrchestratorDiagram, FivePillarsStrip, });