1. Introduction

Over the last decades numerous powerful circuit simulation programs have been
developed. Amongst those are general purpose programs which have been
designed to cope with all different kinds of circuits and special purpose
programs which provide highly optimized algorithms for, e.g., filter design.
General purpose programs can be divided into two categories. Programs
belonging to the first category provide the user with a general purpose
modeling language which can be used to define fairly arbitrary dependencies
between the circuit elements. The most prominent member of this category is
*ASTAP* [33] which was developed by IBM in the 70-ties. To provide
the user with a maximum of flexibility, *ASTAP* generates *FORTRAN* source
files which need to be compiled before execution. The other category consists
of programs which only allow for a predefined set of circuit elements and
dependencies. Although the flexibility is strongly diminished, this approach
allows for a much faster execution and a compact, highly optimized simulator
kernel. The most prominent member of this category is *SPICE* which was
developed at the University of Berkeley [43].

Circuit simulation programs have in common that the electrical behavior of the devices is modeled by means of a compact model, that is, analytical expressions describing the device behavior. Once a suitable compact model is found, it can be evaluated in a very efficient way. However, this task is far from being trivial and many complicated models have been developed. Even if the behavior of the device under consideration can be mapped onto one of the existing compact models, the parameters of this compact model need to be extracted. In the case of the BSIM2 model [60] for short-channel MOS transistors 300 parameters are available for calibration purposes the identification of which is obviously a cumbersome task. If the device design is known and not modified, these parameters need to be extracted only once and can be used for circuit design if the accuracy of the models is sufficient. When there is need to optimize a device using modified geometries and doping profiles the compact model parameters have to be extracted for each different layout as many of these parameters are mere fit parameters without any physical meaning.

The electrical behavior of the devices can either be measured or simulated.
When performing a device optimization, fabricating and measuring each
optimization step would be very expensive. Hence, device simulators became
more and more popular, e.g., *DESSIS* [34],
*MEDICI* [69], *MINIMOS* [58], and *PISCES*
[47]. These device simulators solve the transport equations for a
device with given doping profiles and a given geometry. The transport
equations form a highly nonlinear partial differential equation system which
cannot be solved analytically. Numerical methods have to be used to calculate
a solution by discretizing the equations on a suitable simulation grid. The
data obtained from these simulations can be used to extract the parameters of
the compact model.

Altogether, this subsequent use of different simulators and extraction tools
is cumbersome and error-prone. To overcome these problems several solutions
have been published where a device simulator was coupled to *SPICE*
[49,12,39]. This is again problematic when considering
the communication between two completely different simulators. On the other
hand some solutions were presented where circuit simulation capabilities were
added to a device simulator [40]. However, the restrictions imposed
were so severe that many examples published in this thesis could not be
properly dealt with. For example, the number of distributed devices was
limited to either one or only a few.

To overcome these shortcomings, the device simulator *MINIMOS-NT* has been equipped
with full circuit simulation capabilities with the only limitation being the
amount of computer resources available. *MINIMOS-NT* is a general purpose device
simulator developed as the successor of *MINIMOS* [55]. Simulations
in *MINIMOS* are restricted to rectangular MOS structures, a too severe
limitation for state-of-the-art devices. *MINIMOS-NT* can cope with arbitrary
device structures and geometries. An important prerequisite for accurate
simulation of non-planar structures are triangular grids which have been
introduced into *MINIMOS-NT*.

The traditional drift-diffusion equations can be augmented by the lattice heat
flow equation to account for self-heating effects. To account for non-local
effects a hydrodynamic equation set is available. These equations can be
solved for static and transient problems.

As heterostructures are becoming more and more important, proper handling of
all kinds of heterostructures has been a major design goal for *MINIMOS-NT*
[15]. This is achieved by splitting the device into logical units,
so-called segments which can consist of different materials. Furthermore,
these segments form the basic units of model selection. Due to the flexible
equation assembly it is, for instance, possible to use a drift-diffusion model
on one segment, a hydrodynamic model on another segment, and to account for
self-heating on even another segment.

*MINIMOS-NT* employs a powerful input deck language, enabling the user to customize
the simulation in many details. The basic idea is that the input deck is not
evaluated once at the beginning of the simulation, but is stored as a database
which can be accessed at runtime. Since each keyword in this input deck can be
an arbitrary complex and time dependent expression, fine-tuning can be done
without the need of any predefined heuristic algorithms, e.g., increasing the
number of allowed fill-ins into the sparse system matrix only for one bias
point or time steps with large curvature of the input signals.

Different materials are treated in an abstracted way since all material
properties are handled via a database which controls the model server. The
only information needed in *MINIMOS-NT* is the so-called material class, e.g.,
semiconductor or insulator. For each material class a distinct set of models
is supplied via this database. The model server provides a *C++* like
interpreter language [41] allowing the user to add new models in a
simple fashion. This implies that any material can be added to the simulator
by either providing proper parameters for the existing models or by adding
completely new models. These models can be organized in libraries to extend
the simulator at runtime whenever needed.

So far many different devices have been simulated with *MINIMOS-NT* demonstrating
its wide applicability. Besides traditional MOSFETS [15,23,24],
Charge-Coupled-Devices (CCDs) [50],
Poly-Emitter-Bipolar transistors [19],
Silicon-On-Insulator (SOI) devices [36],
High-Electron-Mobility-Transistors (HEMTs) [61,15,4,62],
Heterostructure-Bipolar-Transistors (HBTs) [46,21], and
Ultra-Low-Power technologies [52] were investigated.

With the new mixed-mode capabilities at hand devices can be characterized by their performance in a circuit as a function of transport models, doping profiles, mobility models, etc. This is of fundamental importance when investigating the behavior of modern submicron devices and non-mainstream devices like HBTs or HEMTs where compact models are not readily available. Furthermore, when the devices are scaled down, non-local effects become more and more pronounced which can alter the device behavior completely. This cannot be handled by scaling the parameters of compact models.

1999-05-31