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Chakraborty, Dwaipayan

Publications and source records attributed to Chakraborty, Dwaipayan.

Connecting Interfacial Mechanical Adhesion, Efficiency, and Operational Stability in High Performance Inverted Perovskite Solar Cells

Carbazole-based self-assembled monolayers (SAMs) at the interface between the metal-halide perovskite (MHP) and the transparent conducting oxide (TCO) serve the function of hole-transport layers in p-i-n "inverted" perovskite solar cells (PSCs). In this report we show that the use of an iodine-terminated carbazole-based SAM increases the interfacial mechanical adhesion dramatically (2.6-fold) and that this is responsible for substantial improvements in the interfacial morphology, photocarrier transport, and operational stability. While the improved morphology and optoelectronic properties impart high efficiency (up to 25.39%) to the PSCs, the enhanced adhesion suppresses nucleation and propagation of pores/cracks during PSC operation, resulting in the retention of 96% of the initial efficiency after 1000 h of continuous-illumination testing at the maximum power-point. This demonstrates the strong connection between judicious interfacial adhesion toughening and simultaneous enhancement in the efficiency and operational stability of p-i-n PSCs, with broader implications for the reliability and durability of perovskite photovoltaics before they can be commercialized.

14 SOLAR ENERGY↗

A Hierarchical Task Scheduler for Heterogeneous Computing

Heterogeneous computing is one of the future directions of HPC. Task scheduling in heterogeneous computing must balance the challenge of optimizing the application performance and the need for an intuitive interface with the programming run-time to maintain programming portability. The challenge is further compounded by the varying data communication time between tasks. This paper proposes RANGER, a hardware-assisted task-scheduling framework. By integrating RISC-V cores with accelerators, the RANGER scheduling framework divides scheduling into global and local levels. At the local level, RANGER further partitions each task into fine-grained subtasks to reduce the overall makespan. At the global level, RANGER maintains the coarse granularity of the task specification, thereby maintaining programming portability. The extensive experimental results demonstrate that RANGER achieves a 12.7× performance improvement on average, while only requires 2.7% of area overhead.

Miniskar, Narasinga Rao↗