Sheet Resistance = R (L/W) = R N ------------------ L

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Sheet Resistance Rewrite the resistance equation to separate (L / W), the length-to-width ratio... which is the number of squares N from R, the sheet resistance = (σ n t) - R L = ----------------------- = qµ n N d Wt ------------------ L ---- q µ n N d t W = R (L/W) = R N The sheet resistance is under the control of the process designer; the number of squares is determined by the layout and is specified by the IC designer. For average doping levels of 0 5 cm -3 to 0 9 cm -3 and a typical layer thickness of 0.5 µm, the sheet resistance ranges from 00 kω/ to 0 Ω/. Other conducting materials: (MOSIS µm CMOS process Ω / n + polysilicon (t =500 nm) 0 aluminum (t = µm) 0.07 silicided polysilicon 5 silicided source/drain diffusion 3

Integrated Circuit Resistors Fabricate an n-type resistor in a p-type substrate using the process described in Chapter. oide mask (dark field),, contact mask (dark field),,, metal mask (clear field),,,,,,,,,,,, I I,,,,,,,,, A 3 4 5 6 7 8 9 W A,, L (a),,,,,,,, contact deposited oide metal,,,,,,,,,, A,, drift current n-type region t,, A thermal oide p-type substrate (b) Given the sheet resistance, we need to find the number of squares for this layout L / W = 9 squares

Laying Out a Resistor Rough approach: R known --> N = R / R. Select a width W (possibly the minimum to save area) --> the length L = W N and make a rectangle L W in area Add contact regions at the ends... ignore their contribution to R More careful approach: account for the contact regions and also, for corners W 3 W W 3W W W 0.65 squares (a) 0.56 squares (b) Measurement shows that the effective number of squares of the dogbone style contact region is 0.65 and for a 90 o corner is 0.56. For the resistor with L / W = 9, the contact regions add a significant amount to the total square count: N = 9 + (0.65) = 0.3 In design, the contact regions and the corners should be accounted for to accurately determine the layout needed to yield the desired resistance.

Uncertainties in IC Fabrication The precision of transistors and passive components fabricated using IC technology is surprisingly, poor! Sources of variations: ion impant dose varies from point to point over the wafer and from wafer to wafer thicknesses of layers after annealing vary due to temperature variations across the wafer widths of regions vary systematically due to imperfect wafer flatness (leading to focus problems) and randomly due to raggedness in the photoresist edges after development etc., etc.

Quantifying Variations in Device Parameters We will write an uncertain parameter (such as the acceptor conc.) as: N a = N a ( ± ε Na ) where N a is the average doping and ε Na is the normalized uncertainty (Note - we ve swept a lot of probability and statistics under the rug here) As an eample, an average acceptor concentration N a = 0 6 cm -3 and a normalized uncertainty ε Na = 0.04 means that the acceptor concentra- tion ranges from 6 0.96 0 cm 3 6 to.04 0 cm 3 How do variations combine to determine the variation in an IC resistor? assume that the variations are independent assume that the normalized uncertainty of a function of several variables is the square root of the sum of the squares of the individual uncertainties ε T = ε a + ε b + ε c (Note - this assumes a normal distribution (bell curve))

IC Resistor Uncertainty R = ------------------ L ---- qn d µ n t W Note that N d, µ n, t, L, and W are all subject to random variations The average resistance is found by substituting the averages: L R = ------------------ ---- qn d µ n t W The normalized uncertainty in resistance is found from the sum of squares of the normalized uncertainties in N d, µ n, t, L, and W ε R = ε Nd + + ε t + ε L + ε W ε µn This estimate is reasonable for relatively small uncertainties independent variables ε< 0. and

Linewidth Uncertainties Due to lithographic and etching variation, the edges of a rectangle are ragged - - greatly eagerrated in the figure δ / W δ / L The width is W W ± δ ---> -- δ δ = ± -- = W ± δ W = W ± ---- W = W( ± ε W ) Conclusion : wider resistors have smaller normalized uncertainty (since δ is independent of width) Conclusion : the length L >> W and so its normalized uncertainty is negligible compared to that of W

Geometric Design Rules Uncertainties in the linewidth and the overlay precision of successive masks determines (in part) the rules for laying out masks n-well polysilicon 4 5 active metal select contact polysilicon active contact-toactive metal polysilicon 3 active n-well

Electrostatics: The Key to Understanding Electronic Devices Physics approach: vector calculus, highly symmetrical problems Gauss s Law: Def. of Potential: Poisson s Eqn.: ( εe) E = = φ ρ ( ε( φ)) = ε φ = ρ Device physics Real problems (not symmetrical, complicated boundary conditions) Gauss s Law: d( εe) -------------- = ρ d Definition of Potential: E = d φ ----- d Poisson s Equation: d ----- ε d φ ----- d d = ε -------- dφ d = ρ

Boundary Conditions. Potential: φ( =0 - ) = φ( =0 + ) φ() 0. Electric Field: ε E=0 ( - ) + Q = ε E=0 ( + ) where Q is a surface charge (units, C/cm ) located at the interface for the case where Q = 0: common materials: silicon, ε s =.7 ε o silicon dioide (SiO ), ε o =3.9 ε o E() ε = 3ε 0

Intuition for Electrostatics Rules of Thumb for sketching the solution BEFORE doing the math: Electric field points from positive to negative charge Electric field points downhill on a plot of potential Electric field is confined to a narrow charged region, in which the positive charge is balanced by an equal and opposite negative charge Use boundary conditions on potential or electric field to patch together solutions from regions having different material properties Gauss s law in integral form relates the electric field at the edges of a region to the charge inside. Often, the field on one side is known to be zero (e.g., because it s on the outside of the charged region), which allows the electric field at an interface to be solved for directly Charge density functions: only two cases needed for basic device physics ρ = 0 > E constant --> φ linear ρ = ρ o = constant --> E linear --> φ quadratic surface or sheet charge Q is sometimes present (e.g., on the surface of good conductors); the effect on electric field can be incorporated through the boundary condition

Eample I: Applied Electrostatics Given: charge distribution ρ() ρ() Given: φ( << 0) = 0.5 V Given: φ( >> 0) = - 0.4 V Sketch the electric field and the charge. E φ 0.5-0.5

Eample II: Applied Electrostatics * Given the electric field, E() Sketch the charge density and the potential ρ() φ() Given: φ( >>0) = 0.3 V