In a conventional chip-on-board (COB) LED circuit, multiple LED dies are mounted on a common platform to achieve dense LED integration, improved heat-sinking, and lower production costs. Nevertheless, the COB LED is still driven by a conventional power supply. In this work, the extended-chip-on-board (e-COB) LED lighting system is proposed, whereby apart from the LEDs, the electronic driving circuit is also integrated into the same platform. Integration with both the linear regulated power supply (LRPS) and switch-mode power supply (SMPS) are explored. The result of such integration is a reduction in circuit footprint, which is more pronounced in the LRPS systems than the SMPS system due to its necessity for bulky inductors. For the LRPS systems, a fourfold reduction in footprint has been demonstrated, for an e-COB circuit comprising 10 LEDs in an annular arrangement. The e-COB system also operates cooler by ∼ 12 . 4 % at the driving voltage of 5 V, due to the direct thermal pathway between the heat source (LED, IC, etc.) to the heat sink (PCB), without having to route through the package. The e-COB packaging approach represents a solution for taking LED lighting system efficiency and compactness to the next level, which can readily be extended to non-lighting systems, especially where electrical and thermal efficiency is valued.

In multigigahertz integrated-circuit design, the extra energy loss caused by conductor surface roughness in metallic interconnects and packagings is more evident than ever before and demands explicit consideration for accurate prediction of signal integrity and energy consumption. Existing techniques based on analytical approximation, despite simple formulations, suffer from restrictive valid ranges, namely, either small or large roughness/frequencies. In this paper, we propose a robust and efficient numerical-simulation methodology applicable to evaluating general surface roughness, described by parameterized stochastic processes, across a wide frequency band. Traditional computation-intensive electromagnetic simulation is avoided via a tailored scalar-wave modeling to capture the power loss due to surface roughness. The spectral stochastic collocation method is applied to construct the complete statistical model. Comparisons with full wave simulation as well as existing methods in their respective valid ranges then verify the effectiveness of the proposed approach.