Systems and methods for composite thermal interface material microstructure property prediction

• US 10,489,525 B2
• Filed: 02/17/2016
• Issued: 11/26/2019
• Est. Priority Date: 02/17/2016
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Motor Engineering & Manufacturing North America Incorporated (Toyota Motor Corporation)
• Inventors: Joshi, Shailesh N., Noguchi, Masao, Dede, Ercan M.
• Primary Examiner(s): Gebresilassie, Kibrom K
• Application Number:
  US15/045,934
• Publication Number:
  US 20170235852A1
• Time in Patent Office: 1,378 Days
• Field of Search: None
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 2113/26 Composites
• CPC Class Codes: G06F 2119/08 Thermal analysis or thermal optimisation
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 30/23 using finite element methods [FEM] or finite difference methods [FDM]

Abstract

Systems and methods of simulating a physical bond layer comprising a composite material and predicting one or more properties of the composite material are disclosed. A method includes obtaining one or more X-ray images of a bulk physical sample of a composite material, the one or more X-ray images including one or more visual identifiers that correspond to one or more materials present in the bulk physical sample, and generating a three dimensional image of the bulk physical sample from the one or more X-ray images. The three dimensional image includes one or more labels indicating the presence and location of the one or more materials. The method further includes creating a meshed three dimensional microstructure-based model from the three dimensional image and simulating a physical bond layer with the meshed three dimensional microstructure-based model. The meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels.

Claims

1. A method of simulating a digital representation of a physical bond layer, the method comprising:

creating a bulk physical sample of a composite material usable between an electronic device and a substrate in an assembly;

obtaining one or more X-ray images of the bulk physical sample, the one or more X-ray images comprising one or more visual identifiers that correspond to one or more materials present in the bulk physical sample;

generating a three dimensional image of the bulk physical sample from the one or more X-ray images, wherein the three dimensional image comprises one or more labels indicating the presence and location of the one or more materials;

creating a meshed three dimensional microstructure-based model from the three dimensional image, wherein the meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels; and

simulating the digital representation of the physical bond layer using the meshed three dimensional microstructure-based model.

2. The method of claim 1, wherein creating the bulk physical sample comprises creating the bulk physical sample via solder, Ag sinter, or TLP bonding.

3. The method of claim 1, wherein creating the bulk physical sample comprises:

combining a first material having a high melting temperature with a second material having a low melting temperature to obtain a combination; and

applying heat to the combination such that the combination has an average internal temperature that is greater than a melting point temperature of the first material and less than a melting point temperature of the second material,

wherein applying the heat causes the first material to melt and diffuse between portions of the second material, forming intermetallic compounds between the first material and the second material.

4. The method of claim 1, further comprising predicting one or more properties of the composite material with the simulated digital representation of the physical bond layer.

5. The method of claim 4, further comprising comparing the predicted one or more properties of the composite material with one or more properties of the bulk physical sample.

6. The method of claim 1, wherein simulating the digital representation of the physical bond layer comprises applying a load to the meshed three dimensional microstructure-based model and performing a finite element analysis test to simulate physical testing of the physical bond layer.

7. The method of claim 1, wherein:

generating the three dimensional image comprises generating, by a processing device, the three dimensional image; and

creating the meshed three dimensional microstructure-based model comprises creating, by the processing device, the meshed three dimensional microstructure-based model.

8. The method of claim 1, wherein the one or more visual identifiers are selected from a gray area, a shading, a pattern, a gradient, and a stippling.

9. The method of claim 1, wherein the one or more visual identifiers comprises a first visual identifier corresponding to a first material present in the bulk physical sample and a second visual identifier corresponding to a second material present in the bulk physical sample.

10. The method of claim 1, further comprising optimizing the digital representation of the physical bond layer for a particular application by manipulating the meshed three dimensional microstructure-based model to obtain particular properties of the physical bond layer.

11. The method of claim 1, further comprising constructing the physical bond layer for use between the electronic device and the substrate in the assembly such that the physical bond layer binds the electronic device and the substrate and exhibits the particular properties.

12. A system for optimizing a digital representation of a physical bond layer comprising a composite material from a bulk physical sample of the composite material that is usable between an electronic device and a substrate in an assembly, the system comprising:

a processing device; and

a non-transitory, processor readable storage medium, the non-transitory, processor readable storage medium comprising one or more programming instructions stored thereon that, when executed by the processing device, cause the processing device to;

obtain one or more X-ray images of a bulk physical sample of the composite material, the one or more X-ray images comprising one or more visual identifiers that correspond to one or more materials present in the bulk physical sample;

generate a three dimensional image of the bulk physical sample from the one or more X-ray images, wherein the three dimensional image comprises one or more labels indicating the presence and location of the one or more materials;

create a meshed three dimensional microstructure-based model from the three dimensional image, wherein the meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels;

simulate the digital representation of the physical bond layer using the meshed three dimensional microstructure-based model; and

optimize the digital representation of the physical bond layer for a particular application by manipulating the meshed three dimensional microstructure-based model to obtain particular properties of the physical bond layer.

13. The system of claim 12, wherein the non-transitory, processor readable storage medium further comprises one or more programming instructions stored thereon that, when executed by the processing device, cause the processing device to:

predict one or more properties of the composite material with the simulated digital representation of the physical bond layer.

14. The system of claim 13, wherein the non-transitory, processor readable storage medium further comprises one or more programming instructions stored thereon that, when executed by the processing device, cause the processing device to:

compare the predicted one or more properties of the composite material with one or more properties of the bulk physical sample.

15. The system of claim 12, wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to simulate the digital representation of the physical bond layer further cause the processing device to:

apply a load to the meshed three dimensional microstructure-based model; and

perform a finite element analysis test to simulate physical testing of the physical bond layer.

16. The system of claim 12, wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to obtain one or more X-ray images further cause the processing device to electronically receive the one or more X-ray images via a user input.

17. The system of claim 12, wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to obtain one or more X-ray images further cause the processing device to electronically receive the one or more X-ray images from an X-ray device.

18. The system of claim 12, wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to optimize the digital representation of the physical bond layer further cause the processing device to:

apply one or more optimization algorithms to the digital representation of the physical bond layer to determine a composition of the bulk physical sample that has one or more of a particular Young'"'"'s modulus and a particular coefficient of thermal expansion property for the particular application.

19. A method for predicting one or more properties of a composite material, the method comprising:

creating a bulk physical sample of the composite material that is usable between an electronic device and a substrate in an assembly;

arranging the bulk physical sample at an X-ray machine such that the X-ray machine generates one or more X-ray images of the bulk physical sample, the one or more X-ray images comprising one or more visual identifiers that correspond to one or more materials present in the bulk physical sample;

generating a three dimensional image of the bulk physical sample from the one or more X-ray images, wherein the three dimensional image comprises one or more labels indicating the presence and location of the one or more materials;

creating a meshed three dimensional microstructure-based model from the three dimensional image, wherein the meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels;

simulating a digital representation of a physical bond layer using the meshed three dimensional microstructure-based model;

predicting the one or more properties of the composite material with the simulated digital representation of the physical bond layer; and

optimizing the digital representation of the physical bond layer for a particular application by using the meshed three dimensional microstructure-based model to obtain particular properties of the physical bond layer.

20. The method of claim 19, wherein creating the bulk physical sample comprises:

combining a first material having a high melting temperature with a second material having a low melting temperature to obtain a combination; and

applying heat to the combination such that the combination has an average internal temperature that is greater than a melting point temperature of the first material and less than a melting point temperature of the second material,

wherein applying the heat causes the first material to melt and diffuse between portions of the second material, forming intermetallic compounds between the first material and the second material.