Modelling the self-alignment of passive chip components during reflow soldering

Krammer, Olivér

doi:10.1016/j.microrel.2013.10.010

Cited by 30 publications

(14 citation statements)

References 18 publications

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“…The high surface tension of liquid metal caused the components to self‐align. This is a phenomenon observed in reflow soldering, but demonstrated here for the first time for EGaIn–microelectronic interfacing. Video S2 (Supporting Information) demonstrates this behavior on surface‐mount resistor–LM interface.…”

Section: Resultssupporting

confidence: 60%

EGaIn–Metal Interfacing for Liquid Metal Circuitry and Microelectronics Integration

Özütemiz

Wissman

Özdoğanlar

et al. 2018

Adv Materials Inter

174

167

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provide increased robustness and better mechanical impedance matching with the host material or structure. For instance, they can be integrated into clothing or mounted on the skin without constraining natural body motion or causing discomfort. A promising approach for realizing stretchable electronics is to create microfluidic traces of liquid-metal (LM) embedded in a soft elastomer. [1][2][3] Ga-based LM circuits offer attractive advantages over alternative approaches. Stretchable electronics based on soft-elastomers embedded with percolating networks of rigid metallic particles, [4,5] carbon allotropes, [6,7] or conductive polymers [8,9] typically suffer from low conductivity (three orders of magnitude lower than metals) or poor electromechanical properties. Micro/nanoscale geometries of thin conductive elements (e.g., serpentine and "wavy" electronics) represent a promising alternative that achieves stretchable functionality through flexure or twisting on a prestrained elastomer substrates. [10][11][12][13][14] However, obtaining stretchability with deterministic architectures requires conductive traces to be patterned into specific geometries (e.g., prebuckled waves, planar serpentines) that are only deformable in prescribed directions. By contrast, Ga-based LM alloys, such as eutectic Ga-In (EGaIn; 75% Ga and 25% In, by weight) and Ga-In-Sn (Galinstan; 68% Ga, 22% In, 10% Sn), can be incorporated into elastomers and preserve their elastic properties at all length scales and in all loading conditions without requiring specialized geometries. [15] These alloys provide high electrical conductivity (3.4 × 10 6 S m −1 ), low melting point (−19 °C for Galinstan, 15 °C for EGaIn), low viscosity (2 mPa s), low toxicity, [16] and negligible vapor pressure. [3,15] Since they are liquid at room temperature and have metallic conductivity, EGaIn and Galinstan can function as intrinsically stretchable and deformable conductors that are not subject to the limitations of conductive polymers or deterministic architectures. As such, LM-based electronics can provide a unique combination of metallic conductivity and elastomeric deformability. Although this promise of LM-based electronics has been well recognized in recent literature, [17] advances in scalable fabrication approaches and effective electrical interfaces between liquid metal traces and microelectronics are still needed to create functional and practical soft and stretchable electronics.Eutectic gallium-indium (EGaIn) has attracted significant attention in recent years for its use in soft and stretchable electronics. However, advances in scalable fabrication approaches and effective electromechanical interfaces between liquid metal (LM) traces and microelectronics are still needed to create functional soft and stretchable electronics. In this study, EGaIn-metal interfacing for the effective integration of surface-mount microelectronics with LM interconnects is investigated. The electrical interconnects are produced by creating copper patterns on a soft-elastomer su...

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Section: Resultssupporting

confidence: 60%

EGaIn–Metal Interfacing for Liquid Metal Circuitry and Microelectronics Integration

Özütemiz

Wissman

Özdoğanlar

et al. 2018

Adv Materials Inter

174

167

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“…According to the principle of minimum energy [22], the maximum condensate thickness on the bottom side can be calculated [20]:…”

Section: Pysicsal Description Of the Condensate Layer Formationmentioning

confidence: 99%

Numerical simulation of condensate layer formation during vapour phase soldering

Illés

Géczy

2014

Applied Thermal Engineering

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This paper presents a modeling approach of the condensate layer formation on the surface of printed circuit boards during Vapour Phase Soldering (VPS) process. The condensate layer formation model is an extension to a previously developed board level condensation model, which calculates the mass of the condensed material on the surface of the soldered printed circuit board. The condensate layer formation model applies combined transport mechanisms including convective mass transport due to the hydrostatic pressure difference in the layer and the gravity force; conductive and convective energy transport. The model can describe the dynamic formation and change of the condensate layer after the immersion of the soldered assembly into the saturated vapour space and can calculate the mass and energy transport in the formed condensate layer. This way the effect of the condensate layer changes on the heating of the soldered assembly can be investigated. It was shown that the numerical modeling of the VPS process becomes more accurate with application of dynamic condensate layer instead of a static description.

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“…Despite numerous studies investigating the theoretical fundamentals of components movements during reflow [1][2][3][4][5][6][7][8], there is no apparent justification to address practical challenges of the self-alignment in the real situation. On one side, there is no specific rule listed in the literature that recommends which control variables have a significant contribution in components movement in , -directions as well as rotation.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Prediction Model of Components Shift during Reflow Process in Surface Mount Technology

Parviziomran

Cao

Yang³

et al. 2019

Procedia Manufacturing

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In surface mount technology (SMT), mounted components on soldered pads are subject to move during reflow process. This capability is known as self-alignment and is the result of fluid dynamic behaviour of molten solder paste. This capability is critical in SMT because inaccurate self-alignment causes defects such as overhanging, tombstoning, etc. while on the other side, it can enable components to be perfectly self-assembled on or near the desire position. The aim of this study is to develop a machine learning model that predicts the components movement during reflow in and -directions as well as rotation. Our study is composed of two steps: (1) experimental data are studied to reveal the relationships between self-alignment and various factors including component geometry, pad geometry, etc. (2) advanced machine learning prediction models are applied to predict the distance and the direction of components shift using support vector regression (SVR), neural network (NN), and random forest regression (RFR). As a result, RFR can predict components shift with the average fitness of 99%, 99%, and 96% and with average prediction error of 13.47 (µ ), 12.02 (µ ), and 1.52 (deg.) for component shift in , , and rotational directions, respectively. This enhancement provides the future capability of the parameters' optimization in the pick and placement machine to control the best placement location and minimize the intrinsic defects caused by the self-alignment.

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Modelling the self-alignment of passive chip components during reflow soldering

Cited by 30 publications

References 18 publications

EGaIn–Metal Interfacing for Liquid Metal Circuitry and Microelectronics Integration

EGaIn–Metal Interfacing for Liquid Metal Circuitry and Microelectronics Integration

Numerical simulation of condensate layer formation during vapour phase soldering

Data-Driven Prediction Model of Components Shift during Reflow Process in Surface Mount Technology

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