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Flux

In physics and , flux is a measure of the amount of a that flows through a given surface per unit time, often quantified as the surface integral of a . The concept is fundamental in describing phenomena such as the of fluids, , , , and . The term derives from the Latin fluxus, meaning "flow," and is widely applied in electromagnetism (e.g., electric and magnetic flux), transport phenomena, and vector calculus, where it relates to theorems like the divergence theorem.

Terminology and Fundamentals

Terminology

The term flux derives from the Latin fluxus, meaning "a flow," which stems from the verb fluere, "to flow." It entered English in the late 14th century, initially denoting an abnormally copious discharge, such as in medical descriptions of fluid motion or bodily flows, before broadening to scientific contexts by the 16th century. In scientific usage, flux refers to the rate at which a —such as , , particles, or a —passes through a given surface, typically measured per unit time and often normalized per unit area to indicate . This captures the or across a , emphasizing the net amount crossing rather than motion parallel to the surface. Flux is always defined with respect to the direction to the surface, as only the component contributes to the passage through it; oblique flows reduce the effective flux via the cosine of the angle between the and the surface . A key distinction exists between total flux, which integrates the flow over the entire surface area to yield the overall quantity transferred, and flux density, which quantifies the flow per unit area at a local point, providing a measure of concentration or strength. In physics, flux commonly describes phenomena like particle streams in transport processes or energy radiation, while in , it denotes the surface of a over a . Beyond these domains, the term appears briefly in non-physical fields, such as , where "cash flux" or flux analysis refers to the movement or variation in financial quantities like revenue streams.

Basic Properties and Units

Flux, in its general physical sense, represents the rate of flow of a quantity through a surface, and its density form—often simply called flux—carries dimensions of that quantity per unit time per unit area. This dimensional structure arises from the fundamental definition of flux as a surface integral of a flow vector field, ensuring homogeneity in physical equations. For instance, mass flux density has dimensions of mass per time per area, expressed as kg/(s·m²) in SI units. In the International System of Units (SI), common flux densities are derived from base units without special names in most cases, promoting coherence across physical domains. Energy flux density, or , is measured in watts per square meter (W/m²), equivalent to joules per second per square meter (J/(s·m²)). Molar flux density uses moles per second per square meter (mol/(s·m²)), reflecting the flow of substance amount. These units stem directly from the SI base units of (kg), time (), (m), and (mol). While SI emphasizes coherence, historical non-SI units persist in specialized contexts, such as luminous flux measured in lumens (lm), which is the SI unit but derived from (cd) and (sr) as cd·sr. Luminous flux density, or , is then in (lx), or lm/m², bridging photometry with SI standards. These units maintain compatibility with SI base quantities like , underscoring the system's adaptability without sacrificing uniformity. A key invariant property of flux is its adherence to conservation laws, encapsulated in the , which states that the of the flux vector equals the negative rate of change of the plus any sources or sinks. This relation holds across diverse physical systems, from and charge to , ensuring local without net or destruction in the absence of sources. Flux is inherently signed, with its value positive when the flow aligns with the chosen surface and negative when opposing it, providing directional information essential for applications. This convention, often taking the outward for closed surfaces, standardizes calculations and reflects the oriented nature of flow through surfaces.

Flux as Flow Rate per Unit Area

General Mathematical Definition

In , the flux density \vec{J} represents the rate at which a Q (such as , , or ) flows through a area perpendicular to the flow per time. It is formally defined as the limit of the incremental divided by the area, as the area approaches zero: \vec{J} = \lim_{\Delta A \to 0} \frac{\Delta Q}{\Delta t \, \Delta A} \hat{n}, where \Delta Q is the amount of transported across the small area \Delta A in time \Delta t, and \hat{n} is the normal vector to the surface defining the of the flux. The vector nature of \vec{J} ensures it points in the normal to the surface, capturing both magnitude and orientation of the flow. For mass transport specifically, the flux density \vec{j} arises from the product of the local \rho and the field \vec{v}: \vec{j} = \rho \vec{v}. This expression describes the convective of , where the flux density is proportional to the and the component of aligned with the surface . To obtain the total flux \Phi through an arbitrary surface S, the flux density is integrated over the surface: \Phi = \int_S \vec{J} \cdot d\vec{A}, where d\vec{A} = \hat{n} \, dA is the element; this continuous form derives from summing the discrete contributions in the limit of infinitesimal areas. Flux densities exhibit key mathematical properties, including linearity with respect to the transported quantity and additivity across different transport mechanisms. For instance, the total flux density can be decomposed as the sum of a convective component \rho \vec{v} and a diffusive component, allowing superposition for complex flows without loss of generality. A representative example is the flux of particles through a flat plane of area A. If the particles have number density n and average velocity \vec{v}, the total particle flux is \Phi = n (\vec{v} \cdot \hat{n}) A, where the dot product \vec{v} \cdot \hat{n} projects the velocity onto the surface normal, yielding zero flux for perpendicular flows and maximum for aligned ones; this illustrates how the flux density \vec{j}_p = n \vec{v} quantifies the effective crossing rate per unit area.

Transport Phenomena Applications

In transport phenomena, the concept of flux as a flow rate per unit area finds extensive application in describing the movement of , , and through continuous media. Momentum transport, governed by viscous effects, is exemplified by Newton's law of viscosity, which states that the \tau_{yx} (flux of x-momentum across a y-oriented plane) is \tau_{yx} = -\mu \frac{\partial u_x}{\partial y}, where \mu is the dynamic and u_x is the x-component of ; this describes frictional forces in fluid flows, such as in pipe friction or boundary layers. Diffusion represents a fundamental diffusive transport process where particles move from regions of higher concentration to lower concentration due to random molecular motion, driven by thermal agitation and collisions. This molecular basis underpins Fick's , formulated by Adolf Fick in 1855, which quantifies the diffusive flux \vec{J} of a as proportional to the negative gradient of its concentration c: \vec{J} = -D \nabla c, where D is the , a material-specific property reflecting the ease of particle movement. Convective transport, in contrast, arises from the bulk motion of the fluid carrying the species along with it, often dominating in scenarios with significant fluid velocities. The convective flux \vec{J}_c is given by \vec{J}_c = c \vec{v}, where \vec{v} is the fluid velocity vector. In many practical situations, such as in chemical reactors or atmospheric flows, the total mass flux \vec{J} combines both mechanisms: \vec{J} = c \vec{v} - D \nabla c, allowing for the modeling of advection-diffusion processes where convection enhances diffusive spreading. Heat transfer by conduction similarly employs flux to describe energy flow, as captured by Fourier's law, proposed by Joseph Fourier in 1822. This law states that the heat flux vector \vec{q} is proportional to the negative temperature gradient \nabla T: \vec{q} = -k \nabla T, with k denoting the thermal conductivity, which quantifies a material's ability to conduct heat through lattice vibrations or free electron movement in solids and fluids. Applications of these flux expressions extend to specialized scenarios, such as gas effusion through porous media under Knudsen conditions, where the mean free path exceeds the pore diameter, leading to molecule-wall collisions dominating transport and yielding a flux \vec{J}_K = -\frac{1}{3} \bar{v} d_p \nabla c (with \bar{v} as the average molecular speed and d_p the pore diameter); this is critical in vacuum systems and membrane separations. Another example is flux in fluids, where suspended particles settle under , producing a downward flux J_s = c v_s (with v_s as the velocity, often derived from for low Reynolds numbers). This process governs deposition in and clarifiers, influencing patterns and . In , flux concepts apply to transport-limited reactions, particularly molar flux through membranes, where selective permeation drives separation processes like gas purification or ; here, the flux N_i of species i follows forms analogous to Fick's law, modulated by membrane permeability and pressure gradients. While traditional treatments emphasize bulk continua, flux in biological systems—such as ion flux across membranes via s—highlights selective down electrochemical gradients, enabling processes like nerve signaling with fluxes on the order of $10^7 ions per second per . Modern extensions include , where engineered s manipulate tiny fluid volumes to study or mimic these fluxes, as in devices for , achieving precise control over concentration gradients in volumes below microliters.

Flux as Surface Integral

Mathematical Formulation

In , the flux of a \vec{F} through a surface S is defined as the \Phi = \iint_S \vec{F} \cdot d\vec{A}, where d\vec{A} represents the element, given by d\vec{A} = \hat{n} \, dA with \hat{n} as the unit normal vector to the surface and dA as the scalar area element. This quantifies the net "" of the field across the surface, weighted by the field's component to the surface. The of the surface plays a crucial role in determining the direction of \hat{n}. For an oriented surface, the normal vector is chosen consistently, often following the : if fingers curl along the boundary curve in the positive direction, the thumb points in the direction of \hat{n}. This distinguishes oriented flux, which can be positive or negative depending on the alignment of \vec{F} with \hat{n}, from absolute flux, which considers only the magnitude |\vec{F} \cdot \hat{n}| \, dA. For a parametrized surface \vec{r}(u,v) = \langle x(u,v), y(u,v), z(u,v) \rangle over a D in the uv-, the flux integral becomes \Phi = \iint_D \vec{F}(\vec{r}(u,v)) \cdot (\vec{r}_u \times \vec{r}_v) \, du \, dv, where \vec{r}_u \times \vec{r}_v provides the aligned with the parametrization's . This form facilitates for non-flat surfaces by transforming the integral into a double over D. A key property of flux through a closed surface S enclosing a volume V is its to the of via the : \iint_S \vec{F} \cdot d\vec{A} = \iiint_V \nabla \cdot \vec{F} \, dV, linking surface flux to the field's local expansion or contraction within the volume. As an illustrative example, consider the flux of a field \vec{v} = v \hat{r} (with constant speed v) through a of radius r centered at the origin, oriented outward. Parametrizing the sphere in spherical coordinates and computing the yields \iint \vec{v} \cdot d\vec{A} = 4\pi r^2 v, representing the total outward flow across the surface.

Relation to

The divergence theorem establishes a fundamental connection between the flux of a vector field through a closed surface and the sources or sinks within the enclosed volume. For a vector field \vec{F} that is continuously differentiable on an open set containing the solid region V with piecewise smooth boundary surface S (oriented outward), the theorem states: \iint_S \vec{F} \cdot d\vec{A} = \iiint_V \nabla \cdot \vec{F} \, dV This equates the net outward flux through S to the integral of the divergence over V./16%3A_Vector_Calculus/16.08%3A_The_Divergence_Theorem) A proof can be sketched by considering the theorem separately for each Cartesian component of \vec{F}, say \vec{F} = (P, Q, R), and proving the result for \vec{F} = (P, 0, 0) using coordinate parametrization. By Fubini's theorem, the volume integral \iiint_V \frac{\partial P}{\partial x} \, dV reduces to integrating over slices perpendicular to the x-axis, where the fundamental theorem of calculus applied to each slice yields the surface integral of P over the x-faces, with internal contributions canceling. The cases for Q and R follow analogously, and this approach generalizes the one-dimensional fundamental theorem, akin to in higher dimensions./04%3A_Line_and_Surface_Integrals/4.04%3A_Surface_Integrals_and_the_Divergence_Theorem) The theorem implies that if \nabla \cdot \vec{F} = 0 everywhere in V, the net flux through S is zero, characterizing divergence-free (solenoidal) fields, such as those in incompressible with no sources or sinks. Conversely, nonzero indicates local (sources, \nabla \cdot \vec{F} > 0) or (sinks, \nabla \cdot \vec{F} < 0)./04%3A_Integral_Theorems/4.02%3A_The_Divergence_Theorem) In applications, the divergence theorem underpins laws, such as the for in : \frac{\partial \rho}{\partial t} + \nabla \cdot \vec{j} = 0, where \rho is and \vec{j} = \rho \vec{v} is . Integrating over V and applying the theorem yields \frac{d}{dt} \iiint_V \rho \, dV = - \iint_S \vec{j} \cdot d\vec{A}, expressing the rate of change of inside V as the negative of the outward flux through S. As an example, the theorem previews in , where for a like the , the flux through a closed equals the of the (related to enclosed sources) over the volume, quantifying how lines originate from or terminate at interior points without specifying the physical context./16%3A_Vector_Calculus/16.08%3A_The_Divergence_Theorem)

Applications in Electromagnetism

Electric Flux

, denoted \Phi_E, quantifies the flow of the \vec{E} through a given surface S and is mathematically defined as the surface \Phi_E = \iint_S \vec{E} \cdot d\vec{A}, where d\vec{A} is the infinitesimal element pointing outward from the surface. This accounts for the component of the perpendicular to the surface, making the flux positive when lines exit the surface and negative when they enter. The unit of electric flux is the volt-meter (V·m), which is dimensionally equivalent to the newton-meter squared per (N·m²/C), reflecting the field's integrated over area. Conceptually, electric flux represents the density of electric field lines piercing the surface; denser field lines correspond to higher flux, and the net flux through a closed surface is zero if no charge is enclosed, as field lines entering must equal those exiting. A fundamental relation is provided by , which states that the total \Phi_E through any closed surface is equal to the net charge Q_{encl} enclosed by that surface divided by the \epsilon_0: \Phi_E = \oint_S \vec{E} \cdot d\vec{A} = \frac{Q_{encl}}{\epsilon_0}. This law enables the calculation of in symmetric charge distributions by choosing appropriate Gaussian surfaces. Notably, the net flux through a closed surface is a Lorentz quantity, as it directly corresponds to the enclosed charge, which remains unchanged under Lorentz transformations in . For example, consider a point charge q at the center of a spherical of radius r. By symmetry, \vec{E} is radial and constant in magnitude on the sphere, so \Phi_E = E \cdot 4\pi r^2 = q / \epsilon_0, yielding the field E = q / (4\pi \epsilon_0 r^2). Similarly, for an infinite parallel-plate with uniform surface \sigma on one plate, a Gaussian pillbox straddling the plate gives \Phi_E = E \cdot A = (\sigma A) / \epsilon_0, so the field between plates is E = \sigma / \epsilon_0, independent of plate separation.

Magnetic Flux

Magnetic flux, denoted \Phi_B, quantifies the total passing through a given surface and is defined as the surface of the \vec{B} dotted with the infinitesimal area d\vec{A} over S: \Phi_B = \iint_S \vec{B} \cdot d\vec{A}. The SI unit of is the weber (Wb), equivalent to one tesla-square meter (T·m²)./22:_Induction_AC_Circuits_and_Electrical_Technologies/22.1:_Magnetic_Flux_Induction_and_Faradays_Law) This measure arises from the interaction of s with conducting circuits, where flux linkage determines electromagnetic induction effects. A key property of magnetic flux stems from Maxwell's equation \nabla \cdot \vec{B} = 0, which implies that the net through any closed surface is always zero. This reflects the nonexistence of magnetic monopoles, as magnetic field lines form continuous loops rather than originating or terminating at isolated points, in contrast to , which can be nonzero through closed surfaces due to enclosed charges. In , changing through a induces an (), as described by : the of the induced \mathcal{E} equals the negative time derivative of the flux, \mathcal{E} = -\frac{d\Phi_B}{dt}. For a or enclosing the surface, this links flux variation—due to moving magnets, changing currents, or varying fields—to generated voltages, forming the basis for transformers, generators, and inductors. complements this by specifying that the induced current flows in a direction opposing the flux change, conserving energy by resisting the alteration. Consider a , a helical coil of wire carrying I, which produces a uniform B = \mu_0 n I inside, where n is the turn density and \mu_0 the permeability of free space. The flux through each turn of area A is \Phi_B = B A, and for N turns, the total linkage is N \Phi_B; if changes, the induced opposes this via , generating a field that counters the flux variation. Similarly, in a coil—a bent into a doughnut shape—the confined field enhances flux uniformity, minimizing leakage and illustrating induction in closed magnetic paths./University_Physics_II_-Thermodynamics_Electricity_and_Magnetism(OpenStax)/13:_Electromagnetic_Induction/13.03:_Lenz's_Law) In modern applications, particularly type-II superconductors, magnetic flux penetrating the material forms quantized vortices known as fluxoids, where the flux is discrete in units of the \Phi_0 = h / (2e) \approx 2.07 \times 10^{-15} , with [h](/page/H+) Planck's constant and [e](/page/Elementary_charge) the elementary charge. This quantization, predicted by and experimentally confirmed in multiply-connected superconductors, underpins phenomena like the and enables precise magnetic sensing in devices such as SQUIDs (superconducting quantum interference devices).

Specialized Flux Concepts

Poynting Flux

The \vec{S} quantifies the flux of electromagnetic energy, representing the power flow per unit area in an . Introduced by in his 1884 paper on energy transfer in electromagnetic fields, it is defined in SI units as \vec{S} = \frac{1}{\mu_0} \vec{E} \times \vec{B}, where \vec{E} is the strength, \vec{B} is the , and \mu_0 is the , with units of watts per square meter (W/m²). The direction of \vec{S} indicates the instantaneous direction of energy propagation, while its magnitude S = \frac{EB}{\mu_0} \sin \theta gives the density, with \theta between \vec{E} and \vec{B}; in typical cases like plane waves where fields are , \sin \theta = 1. This interpretation arises from the cross-product structure, which aligns energy flow orthogonal to both fields, as derived from . Poynting's theorem provides a linking this flux to changes: \nabla \cdot \vec{S} + \frac{\partial u}{\partial t} = -\vec{j} \cdot \vec{E}, where u = \frac{1}{2} \left( \epsilon_0 E^2 + \frac{B^2}{\mu_0} \right) is the electromagnetic and \vec{j} is the , showing that the decrease in field corresponds to work done on charges or outflow. In practical applications, the calculates transport in waveguides, where \vec{S} aligns with the propagation direction to determine power handling capacity. For antennas, integrating the time-averaged over a surrounding surface yields the total radiated power, essential for efficiency analysis. In modern relativistic contexts, such as high-intensity laser interactions with plasmas, the describes driving particle acceleration and wave propagation in dense . A representative example occurs in a monochromatic plane wave propagating in free space, where the time-averaged Poynting vector magnitude is \langle S \rangle = \frac{E_0^2}{2 Z_0}, with E_0 the electric field amplitude and Z_0 = \sqrt{\mu_0 / \epsilon_0} \approx 377 \, \Omega the impedance of free space; this intensity scales quadratically with field strength, highlighting energy transport in electromagnetic radiation.

Radiometric Flux and SI Units

In radiometry, the term "flux" primarily refers to , which quantifies the total power of emitted, reflected, transmitted, or received by an object or passing through a surface. , denoted as \Phi_e, is defined as the time derivative of the Q_e, expressed mathematically as \Phi_e = \frac{dQ_e}{dt}. This quantity represents the rate at which flows, independent of direction or spatial distribution, making it the foundational measure in detector-based for characterizing light sources./Remote_Sensing_(Knudby)/01%3A_Chapters/1.02%3A_Radiometric_measurements) The unit for is the , equivalent to one joule per second (J/s), directly tying it to the base SI unit for . This unit applies to broadband measurements across the relevant to , typically from through wavelengths. For instance, the output of a or the total from a star is expressed in watts, providing a scalar measure without regard to beam geometry or area. The adoption of the ensures consistency with electrical measurements, facilitating integration of radiometric data in and scientific applications. Spectral radiant flux extends the concept to wavelength- or frequency-resolved measurements, denoted as \Phi_{e,\lambda} (per unit wavelength) or \Phi_{e,\nu} (per unit frequency). These are defined as \Phi_{e,\lambda} = \frac{d\Phi_e}{d\lambda} and \Phi_{e,\nu} = \frac{d\Phi_e}{d\nu}, respectively, allowing analysis of radiation distribution across the spectrum. The SI units are watts per meter (W/m) for \Phi_{e,\lambda} and watts per hertz (W/Hz) for \Phi_{e,\nu}, enabling precise characterization of sources like LEDs or blackbody radiators where spectral content varies significantly. Integrating spectral flux over the appropriate range yields the total radiant flux, underscoring its role in comprehensive radiometric assessments.
QuantitySymbolDefinitionSI Unit
Radiant flux\Phi_eTotal power of radiation
Spectral radiant flux (wavelength)\Phi_{e,\lambda}Power per unit wavelength
Spectral radiant flux (frequency)\Phi_{e,\nu}Power per unit frequency
This table summarizes the core flux quantities in , highlighting their units within the framework. These definitions align with international standards for optical measurements, ensuring and in fields such as photometry, , and material science.

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