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A rate law specifies how a reaction rate depends on concentrations under stated conditions. A common form iswhere $k$ is a rate constant and the exponents are partial orders of reaction. Determine them experimentally, or derive them from a justified reaction mechanism. Do not infer $\alpha =a$ and $\beta =b$ from the net chemical equation: its coefficients describe consumption ratios, whereas the exponents describe sensitivity to concentration. See IUPAC Gold Book: rate law and Flowers et al., Chemistry 2e, §12.3: rate laws.

A rate law becomes a prediction of time evolution when combined with stoichiometry in a rate equation, for example $d[\mathrm{A}]/dt=-av$. Agreement with a measured rate law is useful evidence for a reaction mechanism, but several routes can give the same dependence.

A reaction intermediate is formed during a reaction mechanism and consumed in a subsequent step, cancelling from the net chemical equation. It can accumulate, as I does in the consecutive first-order reaction mechanism. A reaction intermediate can also connect transformations in energy coupling. Unlike a catalyst, it need not be present before conversion begins.^[ref]

A reaction intermediate is distinct from a transition state: the former can persist between steps, whereas the latter describes passage through a barrier. The existing potential energy surface and energy profile provide the configuration-space picture; the time-dependent concentration of an intermediate instead measures an ensemble of reacting entities. Low concentration or short lifetime can make detection difficult, so failure to detect a proposed reaction intermediate is not by itself proof of absence. Conversely, detecting a chemical species does not establish that it carries the proposed route to the final reaction products; it could belong to a competing route.

A reaction mechanism describes how reactants become reaction products through specified elementary reactions. Adding the steps must recover the overall chemical equation; intermediate chemical species cancel. That accounting is necessary, but the proposed steps must also predict a rate law compatible with experiment. Several reaction mechanisms can pass the same test.^[ref]

For example, the stipulated steps $\mathrm{A}+\mathrm{B}⟶\mathrm{I}$ and $\mathrm{I}⟶\mathrm{P}$ sum to $\mathrm{A}+\mathrm{B}⟶\mathrm{P}$. I is a reaction intermediate: it is formed and then consumed. The catalyst C in the existing catalytic cycle instead starts available, participates, and is regenerated; its bound form can be a reaction intermediate. Both can disappear from the summed chemical equation, so cancellation alone does not distinguish their roles. Cancellation is algebraic bookkeeping, not an assertion that every step finishes instantaneously.

The net chemical equation supplies consumption ratios, not a clock. For the stipulated two-step example, directional reaction rates $r_1=k_1[\mathrm{A}][\mathrm{B}]$ and $r_2=k_2[\mathrm{I}]$ give $d[\mathrm{I}]/dt=r_1-r_2$ and $d[\mathrm{P}]/dt=r_2$. Initially $[\mathrm{I}]=0$ can mean zero reaction product formation while A already disappears. In particular, $-d[\mathrm{A}]/dt=d[\mathrm{P}]/dt$ requires negligible intermediate accumulation here. A single elementary reaction with the same net chemical equation would instead predict immediate formation at $k[\mathrm{A}][\mathrm{B}]$. Measuring both sides can reveal a distinction hidden by the net equation.

This makes reaction mechanisms useful for designing observations: follow a candidate reaction intermediate, measure individual reaction products, or vary one starting concentration at a time. The consecutive first-order reaction mechanism quantifies an intermediate's rise and fall; the parallel first-order reaction mechanism shows how identical reactant traces can conceal different reaction products. The acetone iodination rate-law experiment connects such reasoning to a real laboratory protocol. The existing reaction coordinate, potential energy surface, and energy profile describe configurations and barriers along a route; a concentration plotted against time describes a different observable.

For one chemical reaction in a closed system of fixed volume $V$, with uniform concentrations and no competing reactions or appreciable accumulation of unlisted species, choose the chemical equationBrackets denote amount of substance per volume, for example $[\mathrm{A}]=n_{\mathrm{A}}/V$. The stoichiometry gives one instantaneous reaction ratewhere $\xi$ is the existing extent of reaction. The minus signs make forward consumption positive; dividing by the coefficients makes measurements of different chemical species agree. Units can be $\mathrm{mol}{\mathrm{L}}^{-1}{\mathrm{s}}^{-1}$. See IUPAC Gold Book: rate of reaction and Flowers et al., Chemistry 2e, §12.1: chemical reaction rates.

For the illustrative chemical equation $2\mathrm{A}+\mathrm{B}⟶3\mathrm{C}$, a measured $d[\mathrm{C}]/dt=0.060\mathrm{mol}{\mathrm{L}}^{-1}{\mathrm{s}}^{-1}$ implies $v=0.020\mathrm{mol}{\mathrm{L}}^{-1}{\mathrm{s}}^{-1}$, $d[\mathrm{A}]/dt=-0.040\mathrm{mol}{\mathrm{L}}^{-1}{\mathrm{s}}^{-1}$, and $d[\mathrm{B}]/dt=-0.020\mathrm{mol}{\mathrm{L}}^{-1}{\mathrm{s}}^{-1}$. These numbers express stoichiometry, without supplying a rate law.

Each derivative is the slope of a concentration curve at one instant. Over a finite interval, $-\Delta [\mathrm{A}]/(a\Delta t)$ instead gives an average reaction rate. For A converting reversibly to B, the net reaction rate is $v=d[\mathrm{B}]/dt=J_f-J_r$; both directional reaction rates can remain positive when $v=0$ at chemical equilibrium.

Receptor binding occupancy is the fraction of binding sites occupied by a ligand. Consider reversible, noncooperative binding at chemical equilibrium, with homogeneous independent sites: every site has the same binding properties, and binding at one site does not change binding at another. Let $L$ denote free ligand, $R$ an unoccupied receptor site and $RL$ the bound complex. In this dilute concentration model,Square brackets denote concentrations; $R_T$ is the total site concentration. Here the dissociation constant $K_d$ has concentration units. Use free ligand in excess so binding negligibly depletes it; only under that approximation may the supplied total ligand concentration substitute for $[L]$. See Analysis of Receptor–Ligand Interactions: equilibrium binding and saturation.

For an illustrative dissociation constant $K_d=10\mathrm{nM}$, where $1\mathrm{nM}=10^{-9}\mathrm{mol}{\mathrm{L}}^{-1}$, free ligand concentrations $1$, $10$ and $100\mathrm{nM}$ give $\theta =1/11\approx 0.091$, $\theta =1/2=0.5$ and $\theta =10/11\approx 0.909$, respectively. At $[L]=K_d$, exactly half the sites are occupied in this model. Raising $[L]$ tenfold from $10$ to $100\mathrm{nM}$ raises occupancy from $50\%$ to about $91\%$, rather than tenfold: the finite pool of sites causes saturation.

A short derivation uses the law of mass action: at chemical equilibrium, association balances dissociation, giving $[RL]=[L][R]/K_d$. Substitute this into $\theta =[RL]/([R]+[RL])$ and cancel $[R]$ to obtain the displayed formula. The limiting values follow directly: zero free ligand gives zero occupancy, and increasing $[L]$ far above $K_d$ drives occupancy toward one.

Receptor binding occupancy is not automatically the fraction of maximal response. Signal amplification, differing effects of bound ligands, and downstream saturation can change the relationship. Consequently, $[L]=K_d$ specifies half occupancy here; it does not universally specify either half-maximal or maximal cellular response. These numbers describe a toy binding model, not measured responses of every receptor. See Higham and Colquhoun, 2024: the affinity–efficacy problem.

A redox titration adds a measured amount of substance of one reactant to determine another through a known redox chemical equation. The burette reading becomes an amount through concentration; the balanced chemical equation supplies the amount ratio. A colour endpoint additionally needs a chemical explanation, as in the permanganate-iron titration.

The useful bridge is an Electron inventory. If each sample entity supplies $z_A$ Electrons and each titrant entity accepts $z_T$, matching the formal exchanged amount of substance of Electrons givesHere $c_T$ is the titrant molar concentration and $V_{\mathrm{eq}}$ the volume attributable to the sample at the equivalence point. These are net half-reaction counts, not a claim that free Electrons accumulate in the flask. The redox conversion must be sufficiently complete and selective for the stated stoichiometry to identify $n_A$.

This is why a small visible signal can reveal a much larger invisible inventory: the signal locates a stopping point, while titrant standardization and stoichiometry turn delivery into amount of substance. The titration endpoint estimates the equivalence point; repeatable colour alone establishes neither correct titrant concentration nor chemical selectivity. The permanganate-iron endpoint and blank model separates these assumptions.

A regulated physiological variable is a specified internal quantity whose departures elicit actions tending to restore an appropriate range. Examples include core body temperature, blood glucose concentration, blood pressure, and the pH and osmolality of extracellular fluid. Specify the compartment and readout: skin temperature and core body temperature are different quantities, and an insulin concentration is a regulatory message rather than the blood glucose it helps control.

Consider an original ideal model with sample volume $V_s$, bath volume $V_b$, and initial sample solute concentration $c_0$. Assume each volume is fixed, a freely permeant, nonbinding solute, no chemical reactions, complete mixing on each side, and equal concentrations at equilibrium. Each fresh bath initially contains none of this solute. The protein is perfectly retained in this model.

The first equilibration redistributes the initial amount of substance $c_0{V}_s$ through both compartments. Conservation givesThis denominator includes the sample itself. For the chosen $V_s=1\mathrm{mL}$ and $V_b=9\mathrm{mL}$, $c_1/c_0=1/10$, rather than $1/9$. Nine-tenths of the initial solute is in the bath and one-tenth remains in the sample; nothing has vanished during equilibration.

Discarding the equilibrated bath removes its solute. A second fresh bath starts with only $c_1{V}_s$ of solute in the entire system, so the same argument applies again. Induction gives the geometric progressionHere $n$ counts completed equilibrations with fresh baths: $n=1$ is the first bath, $n=2$ follows one replacement, and $n=3$ follows two replacements. The normalized sample concentrations are respectively $0.1$, $0.01$ and $0.001$. Leaving the first bath in place for longer cannot lower the ideal equilibrium value below $0.1$.

The same conservation argument handles a fresh bath already containing a permeant solute at fixed concentration $b$:Thus the sample approaches $b$, not necessarily zero. For example, if a hypothetical new buffer component starts at zero in the sample and at $b$ in every bath, its sample concentration reaches $0.9b$, $0.99b$ and $0.999b$ in the three equilibrations. Outward removal and inward replacement follow the same mathematics.

Equilibrium fractions do not specify elapsed time. An illustrative well-mixed linear ordinary differential equation model within one bath isHere $K$ is an effective transfer coefficient with units of volume per time. Adding the two equations conserves $V_s{c}_s+V_b{c}_b$; subtracting their normalized forms givesThe difference undergoes exponential decay. A bath replacement resets $c_b$, renewing the driving difference without making $c_s$ jump instantly. The plotted points are equilibrium endpoints, not a measured time course or a timetable for an arbitrary protein.

Real sample volume can change through osmosis; proteins can be lost through leakage or adsorption to the semipermeable membrane. Consequently, a measured decrease in protein concentration alone cannot distinguish dilution from loss of protein. Measuring recovered volume as well as protein concentration permits an estimate of recovered protein mass.^[ref]