5.73 Lecture #8 Rydberg Klein Rees 8-1 Last time: WKB quantization condition for bound eigenstates of almost general V(x) — Connection into bound region from left and right h x (E) ∫x −+(E) pE (x ′)dx′ = 2 (n + 1/ 2) pE (x) = [ 2m(E − V(x))] 1/2 En without ψ n ! timing of w.p. as it moves on V(x) But where do we get V(x)? Certainly not from femtochemistry! From FREQUENCY DOMAIN SPECTROSCOPY E v,J → V(x) RKR method Next time: Numerical Integration of 1-D Schr. Eq. — see handouts Then begin working toward matrix picture Need background in Ch.2 of CTDL pages 94-121 soon, pages 121-144 by next week Postulates and theorems not to be covered except as needed for solving problems. Today: E v,J → spectroscopic notation A(E, J) = E V(x) xe x dV Equilibrium: = 0 → xe dx ∂A ∂A 1 1 , → x + (E) − x − (E) and − x + (E) x − (E) ∂E ∂J WKB QC applied to ∂A ∂A , ← G( v),B(v) used to determine x ± (E). ∂E ∂J Long Range Theory: Ultra Cold Collisions: Atom in Molecule updated 9/18/02 8:57 AM 5.73 Lecture #8 8-2 Rydberg Klein Rees Someday you will discover that the energy levels of a diatomic molecule are given by E evJ / hc = T e + electronic [ G(v) vibration + F v (J) rotation cm-1 ] = νe + Y 00 + ω e (v + 1 / 2) − ω e x e (v + 1 / 2)2 +… G(v) + [Be − α e (v + 1 / 2)+…]J(J + 1) − DJ 2 (J + 1)2 B(v) RKR requires only G(v) and B(v) to get VJ(x) h 2 J(J + 1) where V J (x) = U(x) + J-dependent bare 2µx 2 effective potential potential x ≡ R − Re µ= centrifugal barrier (actually rotational kinetic energy) m1m2 m1 + m2 We are going to derive V 0 (x) directly from G(v), B(v) data. This is the only direct spectrum to potential inversion method! WKB quantization is the basis for this. x + (E v ) ∫x (E − v ) pE v ( x′)dx′ = (h / 2)(v + 1 / 2) v = 0,1,…# of nodes In this equation, what we know (Ev) and what we want (V(x) and x at turning points) are hopelessly mixed up. There is a trick! A(E, J) ≡ ∫ x + (E,J) x − (E,J) [E ± V J (x′)]dx′ x–(E) x+(E) area at E updated 9/18/02 8:57 AM 5.73 Lecture #8 8-3 Rydberg Klein Rees but, still, we know neither V J (x) nor x ± (E, J)! ! ∂A ∂A and are numerically evaluable ∂J ∂E integrals (via WKB QC) involving only E v,J info data input here ∂A ∂A 2 . independently, and determine ∂J ∂E 1 1 2 eqs. in 2 x + (E, J) − x − (E, J)] and − [ unknowns give x + (E, J) x − (E, J) Roadmap: 1 . Show that turning points Do #2 first because it is so easy ∂A ∂ x + (E,J) = ∫ ∂ E ∂ E x − (E,J) x (E,J) = ∫x +(E,J) 1dx′ − h 2 J(J + 1) E – U( x ′ ) − dx′ 2µx′ 2 + 0 + contributions from 0 ∂x ± (E, J) ∂E are zero because integrand is 0 at turning points ∂A = x + (E, J) − x − (E, J) ∂E ! ∂A ∂ x + (E,J) = ∫ ∂ J x − (E,J) ∂J h 2 J(J + 1) E – U( x ′ ) − 2 dx′ 2µx′ h 2 x + (E,J) 2J + 1 dx′ + 012 + 30 =− ∫ 2µ x − (E,J) x′ 2 integrand = 0 at x ± h2(2J + 1) 1 ∂A 1 =+ − x (E, J) x (E, J) ∂J 2µ − + So, if we can evaluate these derivatives from EvJ data, we have VJ(x)! updated 9/18/02 8:57 AM 5.73 Lecture #8 8-4 Rydberg Klein Rees some clever manipulations to put A(E,J) into convenient form (see nonlecture notes on pages 8-5,6,7) A(E, J) = ∫ [E ± V J (x′)]dx′ x + (E,J) x − (E,J) 1/2 2h 2 A(E, J) = 2 µ 1/2 E ± E′vJ ∫v(E ,J) { min 3 1424 data data v(E,J) dv skipped steps are shown on pages 8-5, 6, 7. this integral could be evaluated at any E, but we really only ∂A ∂A and . Evaluate these derivatives at J = 0. want ∂E ∂J 2h2 ∂A = 2 ∂E µ 1/ 2 −1 / 2 1 v( E, J ) E – E ′vJ ] dv + 0 + 0 [ ∫ 2 v ( E min , J ) integrand = 0 at upper limit 1 Y v(E min , J) = − − 00 2 ωe lower limit independent of E defined so that G(vmin) = 0 G(v) = Y 00 + ω e ( v + 1 / 2) 0 = G(v min ) = Y 00 + ω e ( v min + 1 / 2) Y − 00 = v min + 1 / 2 ωe Y 1 v min = − 00 − ωe 2 for J = 0 [vmin is slightly different from –1/2] E′v,J = G(v) ∂ A 2h 2 = ∂ E µ 1/ 2 data v(E) −1/ 2 ∫−1/ 2−Y 00 / ω e [ E – G(v)] dv ≡ 2f(E) data evaluate this integral numerically at any E. [Singularity at upper limit fixed by change of variable: Zeleznik JCP 42, 2836 (1965).] updated 9/18/02 8:57 AM 5.73 Lecture #8 Rydberg Klein Rees 8-5 2h 2 ⌠ v(E) ∂A ∂E = [E − G(v)]−1/ 2 dv + 0 + 0 ∂ J J=0 µ ⌡−1/ 2−Y 00 / ω e ∂J E = BJ J(J + 1) ∂E = Bv (2J + 1) ∂J 2h 2 ∂A ∴ = ∂ J J=0 µ ∂E = Bv ∂ J J=0 1/ 2 v(E) data ⌠ h2 −1/ 2 [E − G(v)] Bvdv ≡ − 2g(E) 2µ ⌡−1/ 2−Y 00 / ω e data (again, a nonfatal singularity at upper limit) f(E) and g(E) are “Klein action integrals” which are jointly determined by empirical G(v) and B(v) functions. Nonlecture derivation of this useful form of 2h 2 A(E,J) = 2 µ 1/ 2 v(E ,J) ∫v(E min 1/ 2 E − E′vJ ] dv [ ,J ) A(E, J) = ∫x +( E,J ) [ E − V J (x ′ )]dx′ x (E,J) Begin here: − b integral identity let 2 ⌠ x − a 1/2 b−a= dx π ⌡a b − x b= E a = VJ ( x ) x = E′vJ x - a E vJ − VJ ( x ) = so that b- x E − E vJ ∴ (E,J) A(E, J) = ∫xx +(E,J) [ b − a]dx′ − Now insert the integral identity updated 9/18/02 8:57 AM 5.73 Lecture #8 8-6 Rydberg Klein Rees x (E,J) ⌠ + 2 ⌠ b x − a 1/ 2 A(E, J) = dx dx′ π b − x ⌡ a ⌡x − (E,J) put in values of a, b, and x x (E,J) 1/ 2 ⌠ + ⌠E E′ − V (x ′ ) 2 J = dE′vJ dx′ vJ π E − E′ vJ ⌡x − (E,J) ⌡V J (x) reverse order of integration and recognize WKB QC in disguise E 1/2 ⌠ ⌠ x + (E,J) E′vJ − V J (x ′ ) 2 = dx′ dE′vJ π E − E′ vJ ⌡V J (x) ⌡x − (E,J) numerator of dx′ integral is QC — insert QC and then integrate by parts. denominator is independent of x′, so insert QC x (E,J) x + ⌠ + E′ − V(x ′ )]1/2 dx′ = (2µ)−1/2 ⌠ [ p(x ′ )dx′ ⌡x − (E,J) ⌡x − = (2µ)−1/2 h (v + 1/ 2) 2 E ⌠ v(E , J) + 1/ 2 ′ −1/2 h 2 dE′ ∴ A(E, J) = (2µ ) 1/2 vJ π 2 E − E′ vJ ⌡E min ( ) ** ** integrate by parts ( )−1/2 1/2 f = −2(E − E′vJ ) g = [ v(E′vJ , J) + 1/ 2] f′ = E − E′vJ g′ = dv , dE′ A(E, J) = (not a typo because variable is E′vJ not E) which is known from E vJ 2h 2 + µ 14243 E′=E fg E′=E min =0 at both limits 1/ 2 E dv ⌠ 2( E − E′ )1/ 2 dE′ ⌡E min dE′ (caution: f and g here are not Klein’s action integrals) updated 9/18/02 8:57 AM 5.73 Lecture #8 8-7 Rydberg Klein Rees ** change variables from dE′ to dv′ dv dE′ dE′ dv = limits of integration become ⌠ finished: 2h 2 A(E, J) = 2 µ 1/ 2 v(E,J) ⌡v( E min ,J ) v(E,J) ⌠ [E − E′vJ ]1/ 2 dv ⌡v( E min ,J ) we have two independent evaluations of f(E) and g(E) one leads to x + (E, 0) − x − (E, 0) = 2f(E) 1 1 − = ±2g(E) x + (E, 0) x − (E, 0) [ ] pair of turning 2 1/2 (E, 0) = f(E) / g(E) + f(E) ± f(E) x ± points from quadratic formula so we get a pair of turning points at each E. Not restricted to E’s with integer v’s! V(x) connect the dots! Robert LeRoy: modern, n-th generation RKR program at http://theochem.uwaterloo.ca/~leroy/ Download program, instructions, and sample data. ( ) RKR does not work for polyatomic molecules because E−V Q r ~ does not determine the multicomponent vector P updated 9/18/02 8:57 AM 5.73 Lecture #8 Long-Range Molecules 8 - 8 Rydberg Klein Rees W.C. Stwalley CPL 6, 241 (1970) (weak perturbation of atomic properties) R.J. Bernstein & R.LeRoy JCP 52, 3869 (1970) soft turning point hard turning point What does ψ (x) look like at very high v? * lots of nodes (v nodes) * small lobe at inner turning point. Why? * large lobe at outer turning point. Why? H int: Force = – dV(x) dx at sufficiently large v, it is certain that ψ (x) is dominated by o u t e r-most lobe and any expectation value of a function of x, such as V(x), will be dominated by the outer turning point region. Since the vibrational Schrödinger equation contains V(x), it is evident that Ev at high v should be determined primarily by the long range part of V(x) (and insensitive to details near x e and at the inner turning point). What do we know about covalent bonding? ATOMIC ORBITAL OVERLAP IS REQUIRED! NO OVERLAP at large x, V(x) determined by properties of isolated a t o m s: dipole moment, polarizability — return to this later when we do perturbation theory. It is always possible to predict the longest range term in V(x) = C n x −n where the longest range term is the one with SMALLEST n. updated 9/18/02 8:57 AM 5.73 Lecture #8 8-9 Rydberg Klein Rees Quick review of the Long-Range Theory x+(vD) = ∞ x–(vD) ε v ≡ E vD − E v x–(v) vD is noninteger v of “level” at “top” of potential x+(v) D εv is binding energy of v-th level xe V0 (x ) = U(x ) = −Cnx −n at J = 0 at long range (large x) U(∞ ) = 0 ≡ E v D U( x e ) = −De x + (v ) = ( −Cn E v ) 1/n x + ( vD ) = ∞ [E v = V( x + (v)) = −Cn x −n + ] binding energy: εv = E v D − E v = Cnx −n + How many levels are there in potential? x (v ) =∞ + D h ( vD + 1 / 2) = ⌠ 2 ⌡ x− (v D ) p D (x ′)dx ′. Now we do not know v D , Cn , or D, but we do know n and know that E v will be primarily determined by long-range part of V(x) near v D . So, for any Ev we expect that it will be possible to derive a relationship between ( v D − v) and (E v D − Ev # of levels below highest bound level ) binding energy by some clever tricks you may discover on Problem Sets #4 and 5, we find n−2 v D − v = a n ε v2n Tells us how to plot Ev vs. v to extrapolate to vD and then to obtain accurate value of De from a linear plot near dissociation. updated 9/18/02 8:57 AM 5.73 Lecture #8 8 - 10 Rydberg Klein Rees Power n=1 2 3 3 of longest range term in V(x): charge - charge charge - dipole charge - induced dipole dipole - dipole (also transition dipoles) 5 dipole - induced dipole 5 quadrupole - quadrupole 6 induced dipole - induced dipole +,– point charges (e.g. H atom) — + H + H Na 2 S + Na 2P ( ) ( ) — I( P3/ 2 ) + I( 2 P3/ 2 ) 2 ( ) ( ) Na 2 S + Na 2 S not only is the limiting n known, but also Cn is known because it is calculable from a measurable property of the free atom. Many molecular states are described at long range by the same Cn 's ! Ultra-cold collisions now used to determine V(x) to very large x. Now best route to the properties of separated atoms! Mostly, long-range theory has been used as a guide to extrapolation to accurate dissociation energy (relevant to ∆H°f ). Now Bose condensates. Molecule trapping. x −1 and x −2 potentials have ∞ number of bound levels. x −3 , x −5 , x −6 potentials have finite number, and the number of levels breaks off more abruptly as n increases. n →∞ high n low n i.e., # of bound levels action integral affected more by wider classical ∆ x region than by deeper ∆ E binding region because p ∝ (E–V(x))1 / 2 updated 9/18/02 8:57 AM 5.73 Lecture #8 8 - 11 Rydberg Klein Rees This means (equation at bottom of 8-9) that if we plot (given that we can predict n with certainty) vD v correct D: STRAIGHT LINE wrong D: guess for Ev D too high wrong D: guess for Ev D too low 0 (Ev D n−2 − E v 2n guessed n n−2 2n 3 5 6 7 1/6 3/10 1/3 5/14 ) known it is possible to determine D and v D very accurately much better than Birge − Sponer plot,which is valid only for a Morse potential Birge-Sponer: ∆G vs. v ∆G(v+1/2)=G(v+1) – G(v) • • •• long linear extrapolation to vD • v vD G( v) = ω e (v + 1 / 2) − ω e x e (v + 1 / 2) 2 ∆G(v + 1 / 2) = G(v + 1) − G(v) = ω e − ω e x e (2v + 2) decreasing to 0 as v increases Morse Potential when ∆G(v + 1 / 2) = 0, ω e = ω e x e (2v + 2) 2 ωe V0 ( x ) = D[1− e − Ax ] vD = −1 v D is noninteger # of bound vibrational levels 2ω e x e 0 for Morse D = G( v D ) = 1 ω 2e − ω e xe 4 ω e xe = ( v D + 1) ω e ω e xe ω − ≈ ( v D + 1) e 2 4 2 But Morse inevitably has incorrect long-range form updated 9/18/02 8:57 AM 5.73 Lecture #8 8 - 12 Rydberg Klein Rees Which is longer range? Morse or Cnx–n? Take ratio of binding energy at large x. lim lim −C n x −n −C n x −n = x → ∞ D 1 − e −Ax 2 − D x → ∞ De −2Ax − 2De −Ax [ ] lim −C n x −n e 2Ax x → ∞ D − 2De Ax lim C n −n Ax = x e →∞ x → ∞ 2D = dominant term This means that Morse binding energy gets small faster than Cnx–n for any n. Morse –Cnx–n G(v+1) – G(v) will get small faster for Morse. Plot ∆G(v + 1/2) vs. v. G(v+1) – G(v) 0 v Morse vD True vD linear Birge-Sponer Dissociation energy usually underestimated by linear Birge-Sponer extrapolation. Long-range plot of correct power of E v D − E v gives more accurate dissociation energy. updated 9/18/02 8:57 AM