Chemical mechanical polishing (CMP) serves as an indispensable process for achieving global planarization in semiconductor manufacturing, especially as integrated circuit (IC) technology advances to sub-7 nm nodes, where atomic-level surface flatness becomes crucial. Silica abrasives, which account for over 90% of the abrasive market in advanced CMP processes, operate not through simple mechanical grinding but through a key "chemical-mechanical synergistic" mechanism: chemically softening the wafer surface, then mechanically removing the softened layer to expose a new surface, which is further softened and removed, repeating this cycle to produce a smooth wafer. Despite their prevalence, conventional silica abrasives still face challenges, including relatively low material removal rate (MRR), a tendency to agglomerate, leading to poor dispersion and surface defects, and limitations in achieving ultimate surface uniformity. Significant progress has been made to address these issues. Development has progressed from simple spherical particles to complex structural designs (such as mesoporous, hollow, and raspberry-shaped structures) to enhance slurry transport and mechanical action. Surface chemical modifications (e.g., using amino or polymer groups) can improve dispersion stability and reduce scratching. Furthermore, composites with other materials (e.g., ceria, polymers) and precise control of particle size distribution are key to enhancing performance. These innovative approaches have yielded significant performance gains. State-of-the-art slurries have demonstrated the ability to achieve surface roughness below 0.1 nm rms. The development of silica abrasives is increasingly focused on sustainability and smart manufacturing. A prominent direction is the design of biodegradable abrasives that disintegrate after use, thereby simplifying post-chemical mechanical polishing (CMP) cleanup and minimizing environmental impact—an approach fully aligned with green manufacturing principles. This review systematically summarizes the progress of silica abrasives for CMP over the past 60 years. This summary provides theoretical insights and forward-looking strategies to overcome the current limitations of abrasive technology. We believe this review will be helpful in advancing the field of CMP abrasives towards next-generation semiconductor manufacturing.

The kinetics process and control process of chemical mechanical high precision finishing for material surfaces were studied. According to the experiments, the seven kinetics process for chemical mechanical polishing (CMP)was generalized.Through investigating the CMP process of ULSI silicon substrate，we found that the chemical process was the CMP control process under the same mechanical action condition, which was determined by emperature. The key factor influencing the chemical reactions was effectively settled, which will be advantageous for ireproving the CMP removal rate for other materials.

Fifteen periods of Si/Si_0.7Ge_0.3 multilayers (MLs) with various SiGe thicknesses are grown on a 200 mm Si substrate using reduced pressure chemical vapor deposition (RPCVD). Several methods were utilized to characterize and analyze the ML structures. The high resolution transmission electron microscopy (HRTEM) results show that the ML structure with 20 nm Si_0.7Ge_0.3 features the best crystal quality and no defects are observed. Stacked Si_0.7Ge_0.3 ML structures etched by three different methods were carried out and compared, and the results show that they have different selectivities and morphologies. In this work, the fabrication process influences on Si/SiGe MLs are studied and there are no significant effects on the Si layers, which are the channels in lateral gate all around field effect transistor (L-GAAFET) devices. For vertically-stacked dynamic random access memory (VS-DRAM), it is necessary to consider the dislocation caused by strain accumulation and stress release after the number of stacked layers exceeds the critical thickness. These results pave the way for the manufacture of high-performance multivertical-stacked Si nanowires, nanosheet L-GAAFETs, and DRAM devices.

The heterogeneous integration of III–V devices with Si-CMOS on a common Si platform has shown great promise in the new generations of electrical and optical systems for novel applications, such as HEMT or LED with integrated control circuitry. For heterogeneous integration, direct wafer bonding (DWB) techniques can overcome the materials and thermal mismatch issues by directly bonding dissimilar materials systems and device structures together. In addition, DWB can perform at wafer-level, which eases the requirements for integration alignment and increases the scalability for volume production. In this paper, a brief review of the different bonding technologies is discussed. After that, three main DWB techniques of single-, double- and multi-bonding are presented with the demonstrations of various heterogeneous integration applications. Meanwhile, the integration challenges, such as micro-defects, surface roughness and bonding yield are discussed in detail.

Memristors are now becoming a prominent candidate to serve as the building blocks of non-von Neumann in-memory computing architectures. By mapping analog numerical matrices into memristor crossbar arrays, efficient multiply accumulate operations can be performed in a massively parallel fashion using the physics mechanisms of Ohm’s law and Kirchhoff’s law. In this brief review, we present the recent progress in two niche applications: neural network accelerators and numerical computing units, mainly focusing on the advances in hardware demonstrations. The former one is regarded as soft computing since it can tolerant some degree of the device and array imperfections. The acceleration of multiple layer perceptrons, convolutional neural networks, generative adversarial networks, and long short-term memory neural networks are described. The latter one is hard computing because the solving of numerical problems requires high-precision devices. Several breakthroughs in memristive equation solvers with improved computation accuracies are highlighted. Besides, other nonvolatile devices with the capability of analog computing are also briefly introduced. Finally, we conclude the review with discussions on the challenges and opportunities for future research toward realizing memristive analog computing machines.

Aluminum scandium nitride (AlScN), an emerging Ⅲ-nitride semiconductor material, has attracted significant attention in recent years due to its exceptional piezoelectric properties, high thermal stability, tunable bandgap, and excellent compatibility with micro/nano fabrication. This paper systematically reviews the crystal structure, fundamental properties, and property modulation mechanisms of AlScN. It also summarizes recent progress in micro/nano fabrication technologies, including deposition, etching, and device integration. Furthermore, the applications of AlScN in diverse fields such as micro-electromechanical systems (MEMS), RF communications, energy conversion, optoelectronics and sensors are discussed. Finally, current challenges and promising future research directions for AlScN are outlined.