Hsu-Chih Ni

Monolithic, three-dimensional (3D) integrated circuits promise advantages in packing density, energy consumption and interconnectivity bandwidth but require forming high-performance semiconductors and transistors on top tiers under the constraint of a limited thermal budget compatible with back-end-of-line integration^1,2. Back-end-of-line-compatible transistors have been built on laser-annealed polycrystalline silicon, metal-oxide semiconductors, carbon nanotubes and two-dimensional chalcogenides^3-5. However, their performance and reliability are much inferior to bottom-tier silicon metal-oxide-semiconductor field-effect transistors, which mask most of the improvements offered by monolithic 3D integration. Here we show that uniformly doped, ultrathin (≤10 nm) single-crystalline silicon nanomembranes can be vertically stacked using a roll-transfer-printing process that is scalable to wafer-scale and tolerant to substrate topology and surface roughness, enabling multi-tiers of complementary junctionless transistors to be sequentially fabricated on the same starting substrate under a processing temperature ≤400 °C. These devices achieve performance approaching that of front-end-of-line silicon metal-oxide-semiconductor field-effect transistors with current density above 650 µA µm^-1 and sub-10-nm inter-tier registration for high-density vertical integration. We vertically constructed logic gates, including inverters, NAND, NOR gates and static random-access memory cells, based on up to three-tier integration at transistor-level granularity. Our demonstrations provide a promising route towards silicon-based monolithic 3D circuits, especially for research and low-volume prototyping.

Quantitative convergent-beam electron diffraction (QCBED) enables the measurement of structure factors and other structural parameters with high accuracy using dynamical diffraction theory. To do this, rigorous diffraction simulations and iterative intensity refinement are required. We have developed PyExtal , a Python-based software package for QCBED. PyExtal supports refinement of both small- and large-unit-cell crystals through automated computation workflows and flexible data handling of convergent-beam electron diffraction (CBED) and large-angle CBED patterns. The performance of PyExtal is demonstrated by using silicon and yttrium iron garnet as benchmark systems, with refined silicon structure factors showing excellent agreement with previous experimental results. As a computational platform, PyExtal provides a direct basis for experimental mapping of electron charge density in crystals and facilitates broader applications of dynamical-diffraction-based quantitative crystallographic analysis.