inverse problems in semiconductor devices

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Inverse Problems in Semiconductor Devices. Martin Burger. Johannes Kepler Universität Linz. Outline. Introduction: Drift-Diffusion Model Inverse Dopant Profiling Sensitivities. Joint work with. Heinz Engl, RICAM Peter Markowich, Universität Wien & RICAM - PowerPoint PPT Presentation

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Inverse Problems in Semiconductor Devices

Martin Burger

Johannes Kepler Universität Linz

Inverse Problems in Semiconductor Devices

Linz, September, 2004 2

OutlineIntroduction: Drift-Diffusion Model

Inverse Dopant Profiling

Sensitivities

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Joint work withHeinz Engl, RICAM

Peter Markowich, Universität Wien & RICAM

Antonio Leitao, Florianopolis & RICAM

Paola Pietra, Pavia

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Inverse Dopant ProfilingIdentify the device doping profile from measurements of the device characteristics

Device characteristics:

Current-Voltage map

Voltage-Capacitance map

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Inverse Dopant ProfilingDevice characteristics are obtained by applying different voltage patterns (space-time) on some contact

Measurements:

Outflow Current on Contacts

Capacitance = variation of charge with

respect to voltage modulation

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Mathematical ModelStationary Drift Diffusion Model:

PDE system for potential V, electron density n and hole density p

in (subset of R2)

Doping Profile C(x) enters as source term

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Boundary ConditionsBoundary of homogeneous Neumann boundary conditions on N and

on Dirichlet boundary D (Ohmic Contacts)

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Device CharacteristicsMeasured on a contact 0 on D :Outflow current density

Capacitance

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Scaled Drift-Diffusion SystemAfter (exponential) transform to Slotboom

variables (u=e-V n, p = eV p) and scaling:

Similar transforms and scaling for boundary

conditions

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Scaled Drift-Diffusion SystemSimilar transforms and scaling for boundary

Conditions

Essential (possibly small) parameters

- Debye length - Injection Parameter -Applied Voltage U

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Scaled Drift-Diffusion SystemInverse Problem for full model ( scale = 1)

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Optimization ProblemTake current measurements on a contact 0 in the following

Least-Squares Optimization: minimize

for N large

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Optimization ProblemThis least squares problem is ill-posed

Consider Tikhonov-regularized version

C0 is a given prior (a lot is known about C)

Problem is of large scale, evaluation of F involves N solves of the nonlinear drift-diffusion system

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SensitiviesDefine Lagrangian

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SensitiviesPrimal equations,

with different boundary conditions

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SensitiviesDual equations

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SensitiviesBoundary conditions on contact 0

homogeneous boundary conditions else

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Sensitivies

Optimality condition (H1 - regularization)

with homogeneous boundary conditions for C - C0

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Numerical Solution

If N is large, we obtain a huge optimality system of

6N+1 equations

Direct discretization is challenging with respect to memory consumption and computational effort

If we do gradient method, we can solve 3 x 3 subsystems, but the overall convergence is slow

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Numerical Solution

Structure of KKT-System

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Close to Equilibrium

For small applied voltages one can use linearization of DD system around U=0Equilibrium potential V0 satisfies

Boundary conditions for V0 with U = 0→ one-to-one relation between C and V0

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Linearized DD System Linearized DD system around equilibrium

(first order expansion in for U = )

Dirichlet boundary condition V1 = - u1 = v1 = Depends only on V0:

Identify V0 (smoother !) instead of C

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Advantages of LinearizationLinearization around equilibrium is not strongly coupled (triangular structure)

Numerical solution easier around equilibrium

Solution is always unique close to equilibrium

Without capacitance data, no solution of linearized potential equation needed

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Advantages of LinearizationUnder additional unipolarity (v = 0), scalar elliptic equation – the problem of identifying the equilibriumpotential can be rewritten as the identification of a diffusion coefficient a = eV0

Well-known problem from Impedance Tomography

Caution:

The inverse problem is always non-linear, even for the linearized DD model !

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Identifiability

Natural question: do the data determine the doping profile uniquely ?

For a quasi 1D device (ballistic diode), the doping profile cannot be determined, information content of current data corresponds to one real number (slope of the I-V curve)

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IdentifiabilityFor a unipolar 2D device (MESFET, MOSFET), voltage-current data around equilibrium suffice only when currents ar measured on the whole boundary (B-Engl-Markowich-Pietra 01) – not realistic !

For a unipolar 3D device, voltage-current data around equilibrium determine the doping profile uniquely under reasonable conditions

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Numerical TestsTest for a P-N Diode

Real Doping Profile Initial Guess

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Numerical Tests

Different Voltage Sources

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Numerical Tests

Reconstructions with first source

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Numerical Tests

Reconstructions with second source

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The P-N Diode

Simplest device geometry, two Ohmic contacts, single p-n junction

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Identifying P-N JunctionsDoping profiles look often like a step function, with a single discontinuity curve (p-n junction)

Identification of p-n junction is of major interest in this case

Voltage applied on contact 1, device characteristics measured on contact 2

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Model Reduction 1Typically small Debye length Consider limit → 0 (zero space charge)

Equilibrium potential equation becomes algebraic relation between V0 and C

- V0 is piecewise constant

- identify junction in V0 or a = exp(V0 )

Continuity equations

div ( a u1 ) = div ( a-1 v1 ) = 0

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IdentifiabilitySince we only want to identify the junction , we need less measurements

For a unipolar diode with zero space charge, the junction is locally unique if we only measure the current for a single applied voltage (N=1)

Computational effort reduced to scalar elliptic equation

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Model Reduction 2If, in addition to zero space charge, there is also low injection ( small), the model can be reduced further (cf. Schmeiser 91)

In the P-region, the function u satisfies

u = 0

Current is determined by u only

Inverse boundary value problem in the P-region, overposed boundary values on contact 2 (u = 0 on u = 1 on contact 2, current flux = normal derivative of u measured)

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Identifiability

For a P-N Diode, junction is determined uniquely by a single current measurement (B-Engl-Markowich-Pietra 01)

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Numerical Results

For zero space charge and low injection, computational effort reduces to inverse free boundary problem for Laplace equation

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Results for C0 = 1020m-3

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Results for C0 = 1021m-3

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