Concentration vs Time [A](t)
Semi-log Plot: ln[A] vs t
Nuclear Decay Animation (Radioactive Analogy)
Half-Life Cascade
Reaction Parameters
Kinetic Parameters
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Comparison with Other Orders
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First-Order Reaction Equations
What is a First-Order Reaction?
A first-order reaction is a chemical reaction where the rate is directly proportional to the concentration of one reactant. The concentration decreases exponentially over time following [A] = [A]₀·e^(-kt). Unlike zero-order reactions (constant rate) or second-order reactions (rate depends on [A]²), first-order reactions have a unique property: the half-life is constant and independent of initial concentration. This makes first-order kinetics particularly important in radioactive decay, pharmacokinetics, and many decomposition reactions.
First-Order Kinetics
Rate Law: For a first-order reaction, Rate = -d[A]/dt = k[A], where k is the rate constant with units of time⁻¹ (e.g., s⁻¹). The rate depends linearly on reactant concentration.
Integrated Rate Law: [A] = [A]₀·e^(-kt), which describes exponential decay. After each half-life, the concentration is halved: [A]₀ → [A]₀/2 → [A]₀/4 → [A]₀/8...
Linear Form: ln[A] = ln[A]₀ - kt, giving a straight line with slope = -k on a semi-log plot.
Half-Life: t₁/₂ = ln2/k ≈ 0.693/k, which is constant and independent of initial concentration.
Key Characteristics
Exponential Decay: Concentration follows an exponential curve, never reaching zero in finite time.
Constant Half-Life: The half-life is the same regardless of starting concentration - a defining feature of first-order processes.
Percentage Independence: The time for any percentage of decay is proportional to half-life (e.g., 75% decay ≈ 2 × t₁/₂).
Time to Complete: Theoretically infinite, but practically complete after ~10 half-lives (99.9% decayed).
Radioactive Decay Analogy
First-order kinetics perfectly describe radioactive decay: dN/dt = -λN, where N is the number of nuclei and λ is the decay constant. Each nucleus has a constant probability of decay per unit time, independent of other nuclei. This quantum mechanical process follows true first-order statistics. Common examples include Carbon-14 dating (t₁/₂ = 5,730 years) used in archaeology, and medical isotopes like Technetium-99m (t₁/₂ = 6 hours) used in diagnostics. The decay animation shows unstable parent nuclei (red) randomly transforming into stable daughter nuclei (blue).
Comparison with Other Orders
Zero-Order: Rate = k (constant), linear decay, half-life proportional to [A]₀. Examples: enzyme-catalyzed reactions at saturation.
First-Order: Rate = k[A], exponential decay, constant half-life. Examples: radioactive decay, many decomposition reactions.
Second-Order: Rate = k[A]² or k[A][B], hyperbolic decay, half-life inversely proportional to [A]₀. Examples: dimerization reactions, bimolecular substitutions.
Pseudo-First-Order: Higher order reactions can appear first-order if one reactant is in large excess.
Real-World Applications
Radioactive Dating: Carbon-14, Uranium-238, Potassium-40 dating determine ages of rocks, fossils, and archaeological artifacts.
Pharmacokinetics: Drug elimination from the body typically follows first-order kinetics, determining dosage schedules and half-life.
Food Preservation: Food spoilage and nutrient degradation often follow first-order kinetics, used to establish shelf life.
Chemical Decomposition: Many decomposition reactions (e.g., hydrogen peroxide, nitrogen pentoxide) are first-order.
Environmental Science: Pollutant degradation in environment often modeled as first-order decay.
Graphical Analysis
First-order reactions can be identified by plotting ln[A] vs time, which gives a straight line if the reaction is first-order. The slope equals -k, and the y-intercept equals ln[A]₀. This semi-log plot is a powerful diagnostic tool. On a normal [A] vs t plot, the curve shows characteristic exponential decay with steeper slope at high concentrations and shallower at low concentrations. The time to reach any fraction is constant: for 50% it's t₁/₂, for 25% it's 2×t₁/₂, for 12.5% it's 3×t₁/₂, etc. This predictability makes first-order processes particularly amenable to mathematical treatment.