Product Fingerprints for the Evaluation of Tool/Polymer Replication Quality in Injection Molding at the Micro/Nano Scale

Dario Loaldi; Francesco Regi; Dongya Li; Nikolaos Giannekas; Matteo Calaon; Yang Zhang; Guido Tosello

doi:10.1007/s41871-021-00105-7

Product Fingerprints for the Evaluation of Tool/Polymer Replication Quality in Injection Molding at the Micro/Nano Scale

Dario Loaldi, Francesco Regi, Dongya Li, Nikolaos Giannekas, Matteo Calaon, Yang Zhang, Guido Tosello^*

^*Corresponding author for this work

Technical University of Denmark

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

Replication processes for the manufacturing of micro/nano-structured components are characterized by a certain degree of precision and accuracy. The transcription loss, or replication fidelity, defines the geometrical and dimensional correspondence of micro/nano-structure from metal tool inserts into plastic patterned products. The employment of a vast spectrum of micro/nano-structured geometries calls for methodologies that can be used for the estimation of replication fidelity. This study presents a number of product fingerprints, which propose multiple ways to characterize micro/nano structures in replication technologies. Replication fidelity yielded values above 80% and up to 96% depending on the considered product fingerprints and their definition. Thereafter, a correlation of the product fingerprint with the process parameters was found to optimize the replication process. Measurement uncertainty accompanies the analysis of the product fingerprints, enabling a standardized, robust, and quantitative methodology for process learning, modeling, and optimization.

Original language	English
Journal	Nanomanufacturing and Metrology
Volume	4
Pages (from-to)	278–288
ISSN	2520-8128
DOIs	https://doi.org/10.1007/s41871-021-00105-7
Publication status	Published - 2021

Keywords

Micro/nano replication
Product fingerprinting
Metrology
Micro injection molding

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10.1007/s41871-021-00105-7

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title = "Product Fingerprints for the Evaluation of Tool/Polymer Replication Quality in Injection Molding at the Micro/Nano Scale",

abstract = "Replication processes for the manufacturing of micro/nano-structured components are characterized by a certain degree of precision and accuracy. The transcription loss, or replication fidelity, defines the geometrical and dimensional correspondence of micro/nano-structure from metal tool inserts into plastic patterned products. The employment of a vast spectrum of micro/nano-structured geometries calls for methodologies that can be used for the estimation of replication fidelity. This study presents a number of product fingerprints, which propose multiple ways to characterize micro/nano structures in replication technologies. Replication fidelity yielded values above 80% and up to 96% depending on the considered product fingerprints and their definition. Thereafter, a correlation of the product fingerprint with the process parameters was found to optimize the replication process. Measurement uncertainty accompanies the analysis of the product fingerprints, enabling a standardized, robust, and quantitative methodology for process learning, modeling, and optimization.",

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AU - Loaldi, Dario

AU - Regi, Francesco

AU - Li, Dongya

AU - Giannekas, Nikolaos

AU - Calaon, Matteo

AU - Zhang, Yang

AU - Tosello, Guido

PY - 2021

Y1 - 2021

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AB - Replication processes for the manufacturing of micro/nano-structured components are characterized by a certain degree of precision and accuracy. The transcription loss, or replication fidelity, defines the geometrical and dimensional correspondence of micro/nano-structure from metal tool inserts into plastic patterned products. The employment of a vast spectrum of micro/nano-structured geometries calls for methodologies that can be used for the estimation of replication fidelity. This study presents a number of product fingerprints, which propose multiple ways to characterize micro/nano structures in replication technologies. Replication fidelity yielded values above 80% and up to 96% depending on the considered product fingerprints and their definition. Thereafter, a correlation of the product fingerprint with the process parameters was found to optimize the replication process. Measurement uncertainty accompanies the analysis of the product fingerprints, enabling a standardized, robust, and quantitative methodology for process learning, modeling, and optimization.

KW - Micro/nano replication

KW - Product fingerprinting

KW - Metrology

KW - Micro injection molding

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DO - 10.1007/s41871-021-00105-7

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