The critical micelle concentration is the approximate surfactant concentration above which additional dissolved amphiphile predominantly enters micelles rather than remaining as isolated molecules. It is a concentration crossover governed by equality of the molecular chemical potential in the two environments, not a claim that absolutely no aggregates exist below a sharp threshold. Temperature, ionic conditions and molecular structure affect its value.

For an amphiphile, let $v$ be its hydrophobic-tail volume, $a_0$ its effective head-group area, and $\ell$ its maximum tail extension. The dimensionless packing parameter $P=v/(a_0\ell )$ estimates compatible aggregate curvature. For a spherical micelle of core radius $r$ containing $n$ molecules, $nv=4\pi r^3/3$ and $n{a}_0=4\pi r^2$, giving $v/a_0=r/3$. Since $r\le \ell$, spherical packing requires $P\le 1/3$. The analogous long-cylinder calculation gives $v/a_0=r/2$ and the limiting value $1/2$; a planar monolayer has $v/a_0$ equal to its thickness and limiting value one. Thus small $P$ favors spherical micelles, intermediate values favor cylindrical aggregates, and values near one favor lipid bilayers. This is a geometric guide, not a full thermodynamic prediction of every phase boundary.

A femtometre is $10^{-15}$ metre, written $\mathrm{fm}$. It is a convenient unit of measurement for the dimensions of an atomic nucleus, rather than the much larger dimensions of a chemical atom. For example, a length of $5\mathrm{fm}$ is $5\times 10^{-15}\mathrm{m}$.

Scattering probes such small lengths through momentum transfer rather than a miniature mechanical ruler. The relation between wavelength and momentum explains why increasingly short-distance structure requires increasingly large momentum transfer.

A meteorologist studies the atmosphere and weather using observations, physical theory and numerical models. Fluid mechanics, thermodynamics and radiative processes connect measured pressure, temperature and moisture with changing winds and clouds.

Forecasting requires an estimated initial state as well as evolution equations. Uncertainty in observations and model approximations can grow, so an ensemble of forecasts is useful for expressing a range of plausible outcomes.

Charmonium is a family of bound states of a charm quark and its antiquark, with zero net charm. It differs from open-charm D mesons, which carry a charm quark together with a light antiquark.

The constituent spins and relative orbital angular momentum distinguish states such as the J/psi meson, eta c meson and chi c mesons. Their level separations and radiative transitions test the interaction between heavy quarks. Decay can proceed through annihilation of the charm–anticharm pair, so net charm conservation does not imply that a charmonium state is stable. A valence quark label organizes the spectrum while additional gluonic and quark-pair contributions remain part of the interacting state.

A bottom quark-antiquark bound state. Its $4S$ resonance provides a source of B meson pairs.

A meson containing a bottom quark or its antiquark partner. The neutral pair $B^0=d\bar{b}$ and ${\bar{B}}^0=\bar{d}b$ undergoes neutral meson mixing.

A quarkonium is a bound state of a heavy quark and its own antiquark. Examples are charmonium and the bottom-antibottom states called Upsilon mesons. Spectroscopic labels $n{}^{2S+1}{L}_J$ distinguish radial excitation, total quark spin, relative orbital angular momentum and total angular momentum.

In a simple constituent quark model, a spin-dependent contribution $A{\mathbf{S}}_1\cdot {\mathbf{S}}_2/(m_1{m}_2)$ splits a spin-zero and spin-one meson having the same spatial configuration. For two spin-half constituents, addition of angular momentum gives ${\mathbf{S}}_1\cdot {\mathbf{S}}_2=[S(S+1)-3/2]/2$, equal to $-3/4$ for $S=0$ and $+1/4$ for $S=1$. ThusThe spin-averaged mass is $(M_0+3M_1)/4=M_{\mathrm{base}}$. Positive $A$ places the vector state above the pseudoscalar. Determining $A$ from just $M_0$ needs an additional assumption about $M_{\mathrm{base}}$; setting it equal to $m_1+m_2$ neglects all other spin-independent binding terms. A splitting below the pion mass closes a one-pion strong decay to the lower meson, often making the allowed electromagnetic transition with photon emission dominant.

Lateral mobility of membrane proteins is movement along a membrane surface. It differs from membrane transport through the boundary and from reversing membrane topology. Attachment, crowding and barriers can restrict diffusion; the fluid mosaic model does not require every membrane protein to wander freely.^[ref]

An original local model treats a small, approximately flat patch as an unbounded plane with uniform diffusion coefficient $D$, no drift and no trapping. Represent the two displacement coordinates by independent Brownian motions, each with zero expected value and variance $2Dt$. Since $r^2=x^2+y^2$, addition of the two coordinate expectations givesThis is a root-mean-square displacement, not distance traveled along a jagged trajectory or the displacement of every protein. For a stipulated $D=0.08\mu {\mathrm{m}}^2{\mathrm{s}}^{-1}$ and $t=5\mathrm{s}$, $⟨r^2⟩=1.6\mu {\mathrm{m}}^2$ and $r_{\mathrm{rms}}\approx 1.265\mu \mathrm{m}$. Reaching a stipulated root-mean-square scale $L=2\mu \mathrm{m}$ gives $t=L^2/(4D)=12.5\mathrm{s}$. These model values are not measured diffusion coefficients or mixing times from the historical experiment.

Multiplying the target displacement scale by two multiplies the model time by four. This quadratic scaling is a useful way to see why local encounters and redistribution over an entire biological cell need not happen on the same timescale. A curved, bounded cell membrane, restricted paths and different mobile populations require more than this flat-patch model; disappearance of an initial pattern alone does not determine $D$.

Membrane topology specifies the sidedness of a membrane-associated polypeptide chain: where its N-terminus, C-terminus and intervening protein domains lie relative to the lipid bilayer. Side-specific placement is essential to interpreting a cell-surface receptor.^[ref]

For an original worked example, stipulate a continuous polypeptide chain with its N-terminus outside a biological cell, exactly three complete crossings of the cell membrane, and no additional excursions into the lipid bilayer. Its segments lie, in order, outside, inside, outside, inside. A protein domain between the first and second crossings faces the cytosol; one between the second and third faces the exterior; the C-terminus faces the cytosol. Counting crossings determines these placements without specifying an atomic protein structure.

The proof is a side-switching argument. Assign exterior the sign $+1$ and interior $-1$. Each complete crossing multiplies the sign by $-1$, so after $m$ crossings,An odd number puts the termini on opposite sides, an even number on the same side. This assumes complete crossings of one boundary; a chain that enters and returns to the same side without crossing must not be counted as a complete crossing. Nor does the rule determine which side the N-terminus starts on.

As a constructed accessibility test, put an epitope on the outside segment between crossings two and three, and another on the inside segment between crossings one and two. Stipulate an intact cell membrane that excludes the test antibody and accessible epitopes that bind it. Applying the antibody outside can label only the first epitope. If both become accessible after opening the boundary, the difference tests sidedness under those assumptions. Failure to label an epitope alone is insufficient: it could also be inaccessible because of protein folding or poor antibody affinity. This is a proposed reasoning exercise, separate from the historical mixing experiment below.