A simplified explanantion of the beers lambert law?
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BEER'S LAW, sometimes also referred to as the Beer-Lambert law is a physical law stating that the quantity of light absorbed by a substance dissolved in a nonabsorbing solvent is directly proportional to the concentration of the substance and the path length of the light through the solution  Beer's law is commonly written in the form A = cl, where A is the absorbance, c is the concentration in moles per liter, l is the path length in centimeters, and is a constant of proportionality known as the molar extinction coefficient. The law is accurate only for dilute solutions; deviations from the law occur in concentrated solutions because of interactions between molecules of the solute, the substance dissolved in the solvent.
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It's a polynomial. You've added no NaOH so far, so it's:\n\nDraw an ICE chart, where ICE is initial, change, equilibrium. Let x be the amount of BA\n\nBAH  <---> H+ + BA-\nI 1.0 M    0     0\nC  -x      +X    +X \nE 1.0-X    X      X\n\nI don't expect the formating to surivive, so the equation becomes, based on the law of mass action:\n\nX^2/1-x = 6.3*10^-5\n\nThere are two ways to proceed at this point. We can assume that the amount of benzoic acid that has diassociated is much larger than the amount that has not. If we assume this, we disregard the -x and figure out:\n\nx^2 = 6.3*10^-5  so x = 0.007937.\n\n-LOG (0.007937) = 2.1\n\nSay we don't make that assumption, then we have to solve the equation: \n\n\nX^2/1-x = 6.3*10^-5
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Using DeMorgan's law, it is A' ∩ B'.\n\nAnother way?  I guess S-A-B?
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(1) Take a container and measure the length of the container. Let us say the length of the container is L. \n\n(2) Take a beam of light (preferably a monochromatic source like laser beam) and shine it through the empty container. \n\n(3) Measure the intensity of the light at the end where the beam has gone through the empty container. Let this be Io. \n\n(4) Now fill the container with the liquid whose molar extinction coefficient is unknown. Now measure the light intensity as the beam travels the length L of the container. The measured intensity is I.\n\n(5) Beer-Lamberts law is I=Io exp(-a L) where all the quantities have been experimentally determined except a which is the extinction coefficient. \nRearrange the above formula and we get, a=(-1/L)*log(I/Io) where log is to the base e.
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I would use the ideal gas law...more specifically...the combined ideal gas law...\n\nP1*V1/T1 = P2*V2/T2
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Some of the basis laws that govern the behavior of gases follow:\n\nBoyle's Law= Volume is proportional to the inverse of pressure\n\nCharles' Law= Volume is proportional to temperature\n\nAvaogadro's Law= Volume is proportional to number of moles present\n\nThese together lead to the ideal gas equation:\n\nPV = nRT\n\nwhere P is pressure\n      V is volume\n      n is the number of moles present\n      R is the gas constant\n      T is the temperature\n\nThe value of R is 0.082057 L*atm/(mol*K).\nTemperature must be in kelvins for this relationship.  Temperature in kelvins = tempature in Celcius +273.15.
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Biot-Savart Law. Look it up.
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Well, probably easier to explain empirically -- I know that one of the equations that you would be looking for is Planck's law of black-body radiation.  That, along with other equations involved in transport phenomena could be used to model the system and let you know how much heat you lose from the glass.\n\nOff the top of my head, I can't remember every equation that one would want to use.  Good luck!\n\nThe link is to Wiki's entry for Transport Phenomena -- the first reference there would be an excellent -- if very heavy on the math -- reference for solving this problem.
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Try Google or Yahoo.  You'll find worked examples there.  I think it needs diagrams to understand; they and the accompanying explanations are too complex to attempt to reproduce here.
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The index-of-reaction equation (i.r.e.): dF/dtZ = kZ(l - βF)m is compared with a generalized Prout-Tompkins equation (g.P.T.e.): dF/dt = kn(l - βF)y With the boundary condition F = 0, t = 0 the equations are equivalent for z = 2 or m = 0 or β ≤ 1 and the i.r.e, is closely approximated by the g.P.T.e. for other values of the parameters by use of the following approximation ∫(1- F)-m dF ≈ AF(1-BF)5 The parameter s is a function of m. Both A and B are close to unity for 1/3 < m < 3. The i.r.e. is recommended as being more useful than the g.P.T.e. because the i.r.e. has a better theoretical basis and because it is more readily integrated and fitted to experimental data.
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Get some help here:\nhttp://en.wikipedia.org/wiki/Brownian_movement
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There's a article here: \n"The cutoff phenomenon in finite Markov chains"\n\nhttp://www-stat.stanford.edu/~cgates/PERSI/papers/cutoff.pdf
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Using the Michaelis-Menten equation.\n\nMore details on teh attached link\n\nhttp://www.le.ac.uk/by/teach/biochemweb/tutorials/michment2print.html\n\nGood luck
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Assuming temperature is static, I think Dalton's Law would apply:\nThe sum of all the partial pressures.\n\nP(gas 1)V(vol 1) = P(new gas 1)V(together)\n10 bars * 300L = ? bars * 600 L\nP(new gas 1) = 5 bars\n\nP(gas 2)V(vol 2) = P(new gas 2)V(together)\n3 bars * 400L = ? bars * 600 L\nP(new gas 2) = 2 bars\n\nP(together) = P(new gas 1) + P(new gas 2)\nP(together) = 7 bars
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A graph of many rates (rate of reaction, population growth, etc.) produce exponential curves (asymptotic).\nThese are difficult to interpret.\nTo linearise the curve plot log y against x, or log y against log x. The properties of the rate can now easily be established.\nHave a look here (note, second reference is PDF format):
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When I read the Foundation trilogy for the first time I wondered about this too. I thought a bit about the equivalent of a gas law\np V T =constant for populations as deduced from the behavious of molecules. But I guess that even planet size populations are too small to be predictable. \n\nPsychohistory  as a science exist (see my references)  but it different from the Asimovian  science.
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i am not sure with who came up with the concept, but this might be usefull \n\nhttp://en.wikipedia.org/wiki/Probability_Density_Function