Wenjun Tong

Mr. Wenjun Tong


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 June 2026 in Micromachines
Verified
Journal Article
Open access
PDF file
YZYongou Zhang
Yongou Zhang
KZKeke Zhang
Keke Zhang
Yapeng XuYapeng Xu
Yapeng Xu
WTWenjun Tong
Wenjun Tong
JWJunfeng Wang
Junfeng Wang
Wuyi MingWuyi Ming
Wuyi Ming
As semiconductor packaging technology evolves from two-dimensional to three-dimensional integration, the through-glass via (TGV) technique, as a core interconnect method in advanced packaging, is emerging as a strong candidate to replace through-silicon vias (TSVs) and plated through-holes (PTHs) in organic substrates. Glass substrates offer excellent electrical insulation, low dielectric loss, tunable thermal expansion coefficients, and the potential for large-scale panel-level manufacturing. However, issues related to TGV hole quality, metallization uniformity, and thermomechanical reliability remain key bottlenecks limiting their large-scale industrialization. This investigation provides a comparative review of non-laser and laser machining for TGVs to address the above problems. First, the technical background and core advantages of TGVs are outlined. Second, this study details non-laser processing methods, including sandblasting erosion, mechanical drilling, the photosensitive glass method, electrochemical discharge machining (ECDM), deep reactive ion etching (DRIE), and others. Third, laser processing methods, covering laser ablation drilling, laser-induced deep etching (LIDE), femtosecond laser-assisted wet etching and others, are given focus. Moreover, this study analyzes typical applications of TGVs in 3D/2.5D packaging, MEMS devices, optoelectronic integration, and others. In addition, the machining processes of non-laser and laser-based TGVs, such as mechanical machining, ECDM, and LIDE, are compared, and key process challenges, technical trade-offs, and reliability failure mechanisms are discussed. Finally, this review looks ahead to future trends, aiming to provide a systematic technical reference for researchers in the TGV field.

20 June 2026 in Materials
Verified
Journal Article
Open access
PDF file
RWRuili Wang
Ruili Wang
HWHongyan Wang
Hongyan Wang
NXNa Xiao
Na Xiao
ZHZihao Hu
Zihao Hu
WTWenjun Tong
Wenjun Tong
WMWuyi Ming
Wuyi Ming
The automotive panoramic roof exhibits a large-size and thin-wall geometry, with a length-to-thickness ratio approaching the thousand level. This geometric feature makes its forming quality highly sensitive to forming conditions. During the glass molding process, variations in temperature evolution, loading, and cooling parameters may lead to residual stress accumulation and springback deformation, thereby affecting dimensional accuracy and final forming quality. In this study, a full-process finite element model was established and combined with an L16(4^5) orthogonal design to investigate the effects of five key process parameters—heating temperature, holding time, quenching air velocity, quenching air pressure, and quenching time—on the mean residual stress and mean springback displacement in the glass molding process (GMP). The results showed that, within the given parameter ranges, heating temperature, holding time, and quenching time had relatively pronounced effects on the mean residual stress; the mean residual stress was relatively low when the heating temperature was 680 °C, the holding time was 3 s, and the quenching time was 12 s. Heating temperature, quenching air velocity, and quenching time had relatively pronounced effects on the mean springback displacement; the mean springback displacement was relatively low when the heating temperature was 677.5 °C, the quenching air velocity was 13 m/s, and the quenching time was 10 s. Based on the orthogonal analysis, regression models for the mean residual stress and mean springback displacement were further developed, and parameter combinations were screened using the NSGA-III method. Experimental validation showed that the relative error of the mean residual stress was controlled within 15%, indicating that the established model could, to some extent, capture the relationship between process parameters and forming quality indicators, thereby providing guidance for precision forming and process optimization of large-scale thin-walled automotive panoramic roofs.