Nec Corporation

Koichi Sawahata

Susumu Asada

An ion implantation process simulation device includes a Dual Pearson data extracting unit for generating a Dual Pearson data table from ion implantation profile data, a Dual Pearson data for interpolation obtaining unit for obtaining a parameter for use in the interpolation and extrapolation of a dose coefficient from the Dual Pearson data table, a dose coefficient interpolating/extrapolating unit for expressing an ion implantation profile by linear connection of two functions respectively representing an amorphous component and a channeling component, as well as using a dose-independent moment parameter and a coefficient of linear connection dependent on dose to interpolate and extrapolate a logarithmic value of a channeling component dose coefficient with respect to logarithmic values of all dose values, and a simulation result outputting unit for outputting a simulation result.

Ion implantation process simulation device realizing accurate

On simulating ion implantation on the basis of Monte Carlo method, a plurality of triangle meshes are produced to a polygonal substrate to be label serial numbers at a first step. An ion is implanted as an implanted ion to the polygonal substrate at a second step. At a third step, the triangle meshes are checked in an ascending order until one of triangle meshes is found as a specific triangle mesh in which the implanted ion is positioned. Point defect concentration is extracted from the specific triangle mesh at a fourth step. Random numbers are generated in order to calculate scattering of the implanted ion a fifth step. The point defect concentration is renewed into a renewed point defect concentration in the specific triangle mesh at a sixth step. The energy, the position, and the travelling direction is renewed in the implanted ion at a seventh step. The third to the seventh steps is repeated until the implanted ion stops in said polygonal substrate.

Method capable of accurately simulating ion implantation at a high speed

An ion-implantation simulation method including (1) a step of generating orthogonal meshes for a multilayer-structure substrate, (2) a step of taking out a longitudinal strip, (3) a step of determining a function representing an impurity distribution in the longitudinal strip, (4) a step of integrating the function representing the impurity distribution in the range of each cell in the longitudinal strip, and dividing the integration value by the integration range to set the division result as the impurity concentration in the cell, (5) a step of taking out a transverse strip, (6) a step of determining a function of re-distributing the impurity distribution in the transverse strip in the transverse direction, and (7) a step of integrating the re-distributing function in the range of each cell in the transverse direction, dividing the integration result by the integration range and setting the division result as the impurity concentration in the cell.

Method, apparatus and computer program product for simulating ion

In a computer-implemented simulation method for implanting ions into a semiconductor substrate, a region is defined in a vertical cross-section of the substrate between first and second horizontal lines, the first horizontal line being spaced a distance R.sub.p -N.sigma. from a top surface of the substrate and the second horizontal line being spaced a distance R.sub.p +N.sigma. from the top surface, where R.sub.p is a projected range of implanted ions from the top surface, N is an integer, and .sigma. is a standard deviation of horizontal spread of an impurity profile. An orthogonal coordinate system is then defined by a set of narrowly spaced horizontal parallel lines within the region, a set of widely spaced horizontal parallel lines outside of the region and a set of vertical parallel lines at spacing which increases as a function of distance from opposite vertical edges of the coordinate system. A simulation of ion implantation is performed into the substrate and an impurity profile is obtained using the coordinate system.

Simulation method for high resolution deep impurity profile

Disclosed is an ion implantation simulation method including calculating a particle scattering process of each of sample particles as a simulation target using a Monte Carlo method, determining that the particle has stopped when scattering calculation gives zero energy of the particle, continuously performing the scattering calculation when the energy is not 0. When the scattering calculation yields an energy of the particle that has decreased to .alpha. (0.ltoreq..alpha..ltoreq.1) times the energy value at the time of implantation, the particle Is divided into a predetermined number N (N is an integer) such that the weight of the particle after division becomes 1/N that before division. The scattering calculation and the particle division process is repeated until particles having non-zero energy values are divided the predetermined number of times M (M is an integer) counting from the first division, and consequently, the weight of the particle becomes 1/N.sup.M that of the initially implanted particle, performing the scattering calculation for particles which have been divided the predetermined number of times M until the energy value becomes 0, and determining the positions where the energy values of all the sample particles become 0 as stop positions in a substrate, thereby obtaining an impurity distribution.

Ion implantation simulation method

A method for simulating an impurity distribution in a multilayer structure includes analytically simulating an impurity distribution for each layer to obtain a first impurity distribution profile for each layer by using impurity distribution moments defined for the material of each layer, analytically simulating a point defect distribution for a crystal layer to obtain a point defect distribution profile by using the first impurity distribution profile and point defect distribution moments defined for the material of crystal layer, simulating a thermal diffusion to obtain a final impurity distribution profile for each layer by using the first impurity distribution profile and point defect distribution profile. The point defect distribution moments are obtained previously for the material of the crystal layer by Monte Carlo method under typical conditions to obviate using the Monte Carlo method for each simulation under a specified condition.

Method for impurity distribution simulation

An ion implantation simulation system includes a grid generating portion for generating an orthogonal grid with respect to a two-dimensional configuration of a simulation object, an elongated segment extracting portion for extracting elongated segments defined by two grid lines in the orthogonal grid, a cell analyzing portion for extracting cells defined by adjacent grid lines perpendicular to the longer edge of the elongated segment, in the extracted elongated segments, and linearly rearranging polygon elements presenting in the cell along the longer edge direction, simulation performing portion performing linear ion implantation simulation with respect to the cell, in which the polygon elements are linearly rearranged, and a calculation result registering portion for registering an impurity concentration obtained as a result of simulation for each polygon element and registering the impurity concentration in each polygon element.

Method and system for simulating ion implantation for performing

A novel method for analyzing a light intensity distribution on a flat surface in a projection system wherein a pattern is projected by use of a light through a pupil on the flat surface. The pattern is analyzed into plural polygonal elements where a combination of the polygonal elements constitutes the pattern. Fourier transformations of vertexes of each of the polygonal elements except for the pattern are calculated for subsequent addition and subtraction of the Fourier transformations of all the polygonal elements to thereby obtain a Fourier transformation of the pattern. A product of the Fourier transformation of the pattern and a pupil function is calculated for the pupil. An invert Fourier transformation of the product is calculated to thereby obtain a light intensity distribution.

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Tokyo, Japan

Koichi Sawahata