{"spec_id":"line-arrhenius","library":"echarts","language":"javascript","code":"// anyplot.ai\n// line-arrhenius: Arrhenius Plot for Reaction Kinetics\n// Library: echarts 5.5.1 | JavaScript 22.22.3\n// Quality: 90/100 | Created: 2026-06-24\n//# anyplot-orientation: landscape\n\nconst t = window.ANYPLOT_TOKENS;\n\n// --- Data (deterministic, in-memory) ----------------------------------------\n// First-order thermal decomposition of hydrogen peroxide (H₂O₂ → H₂O + ½O₂)\nconst temps_K = [300, 325, 350, 375, 400, 425, 450, 475, 500, 525, 550];\nconst R_GAS = 8.314; // J/(mol·K)\nconst EA_TRUE = 95000; // J/mol — activation energy\nconst LN_A = 27.0; // ln(A) where A is the pre-exponential factor in s⁻¹\n\n// Deterministic perturbations to simulate experimental measurement scatter\nconst noise = [0.12, -0.08, 0.15, -0.11, 0.09, 0.07, -0.13, 0.10, -0.06, 0.14, -0.09];\nconst inv_T = temps_K.map(T => 1 / T);\nconst ln_k = temps_K.map((T, i) => LN_A - EA_TRUE / (R_GAS * T) + noise[i]);\n\n// Linear regression: ln(k) = slope * (1/T) + intercept (slope = -Ea/R)\nconst n = inv_T.length;\nconst sx = inv_T.reduce((a, b) => a + b, 0);\nconst sy = ln_k.reduce((a, b) => a + b, 0);\nconst sxy = inv_T.reduce((a, xi, i) => a + xi * ln_k[i], 0);\nconst sx2 = inv_T.reduce((a, xi) => a + xi * xi, 0);\nconst slope = (n * sxy - sx * sy) / (n * sx2 - sx * sx);\nconst intercept = (sy - slope * sx) / n;\n\n// R² coefficient of determination\nconst y_mean = sy / n;\nconst ss_res = ln_k.reduce((a, yi, i) => a + (yi - (slope * inv_T[i] + intercept)) ** 2, 0);\nconst ss_tot = ln_k.reduce((a, yi) => a + (yi - y_mean) ** 2, 0);\nconst r_sq = (1 - ss_res / ss_tot).toFixed(4);\n\n// Extracted activation energy from Arrhenius slope: slope = -Ea/R\nconst Ea_kJ = (-slope * R_GAS / 1000).toFixed(1);\nconst Ea_over_R = (-slope).toFixed(0);\n\n// Regression line (51 points for smooth rendering, extended beyond data range)\nconst x_lo = Math.min(...inv_T) * 0.995;\nconst x_hi = Math.max(...inv_T) * 1.005;\nconst line_data = Array.from({ length: 51 }, (_, i) => {\n const x = x_lo + (x_hi - x_lo) * i / 50;\n return [x, slope * x + intercept];\n});\n\n// --- Init -------------------------------------------------------------------\nconst chart = echarts.init(document.getElementById(\"container\"));\n\n// --- Option -----------------------------------------------------------------\nchart.setOption({\n animation: false,\n color: t.palette,\n backgroundColor: \"transparent\",\n title: {\n text: \"line-arrhenius · javascript · echarts · anyplot.ai\",\n left: \"center\",\n top: 22,\n textStyle: { color: t.ink, fontSize: 22, fontWeight: \"bold\" }\n },\n legend: {\n data: [\"Experimental data\", \"Arrhenius fit\"],\n top: 60,\n textStyle: { color: t.inkSoft, fontSize: 14 },\n itemWidth: 22,\n itemHeight: 14\n },\n tooltip: {\n trigger: \"item\",\n backgroundColor: t.elevatedBg,\n borderColor: t.inkSoft,\n textStyle: { color: t.ink, fontSize: 13 },\n formatter: function(params) {\n if (params.seriesType === \"scatter\") {\n const T = Math.round(1 / params.data[0]);\n return (\n \"T = \" + T + \" K
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