Moore and More

Interview with Professor Jianhua Zhang, Editor-in-Chief of Moore and More

Lin Jiang, Yi Li, Jianhua Zhang

2025, 1(2): 99-101. DOI: 10.1007/s44275-024-00004-1

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Kun Du, Jiafeng Ying, Lixin Han, Jie Xue, Hanshen Xin, Jianhua Zhang, Haoyuan Li

2025, 1(2): 102-113. DOI: 10.1007/s44275-024-00002-3

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Extreme ultraviolet (EUV) photoresists have become the core materials in lithography with nanometer-sized patterns and are actively explored on the path to realizing smaller critical dimensions. These photoresists can be small molecule-, polymer-, or organic–inorganic hybrid-based, with the full molecular working mechanism under investigation. For the rational design of EUV photoresists, theoretical guidance using tools like first-principle calculations and multi-scale simulations can be of great help. Considering the extremely high standard of accuracy in EUV lithography, it is critical to ensure the adoption of the appropriate methodologies in the theoretical evaluation of EUV photoresists. However, it is known that density functionals and semi-empirical methods differ in accuracy and efficiency, without a universal rule across materials. This poses a challenge in developing a reliable theoretical framework for calculating EUV photoresists. Here, we present a benchmark investigation of density functionals and semi-empirical methods on the three main types of EUV photoresists, focusing on the ionization potential, a key parameter in their microscopic molecular reactions. The vertical detachment energies (VDE) and adiabatic detachment energies (ADE) were calculated using 12 functionals, including pure functionals, hybrid functionals, Minnesota functionals, and the recently developed optimally tuned range-separated (OTRS) functionals. Several efficient semi-empirical methods were also chosen, including AM1, PM6, PM7, and GFN1-xTB in the extended tight-binding theoretical framework. These results guide the accurate and efficient calculation of EUV photoresists and are valuable for the development of multi-scale lithography protocols.

Design and implementation of a scalable and high-throughput EEG acquisition and analysis system

Haifeng Liu, Zhenghang Zhu, Zhenyu Wang, Xi Zhao, Tianheng Xu, Ting Zhou, Celimuge Wu, Edison Pignaton De Freitas, Honglin Hu

2025, 1(2): 114-133. DOI: 10.1007/s44275-024-00017-w

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Recent advances in neuroscience, neuromorphic intelligence, and brain–computer interface (BCI) technologies have created a need for fast, efficient, and convenient electroencephalogram (EEG) data acquisition systems. However, the existing equipment was limited in its flexibility, restricting non-invasive studies to research or medical settings. To address this issue, low-cost, compact EEG acquisition devices have been developed, allowing for frequent and flexible brain data acquisition in various scenarios. This paper introduces a scalable and high-throughput EEG signal acquisition and analysis system based on field-programmable gate array (FPGA) technology. The proposed system offers electrode scalability, on-chip computing, and optional wireless functionality extension. These features are achieved through the design of a highly scalable underlying EEG acquisition module and an FPGA central module that enables software-defined high-throughput expansion and high-speed data exchange between software and hardware. The paper presents two implementation cases that demonstrate the potential of the proposed system. The first case introduces a wearable wireless EEG system, enabling the deployment of effective and user-friendly steady-state visual evoked potential (SSVEP)-BCI applications in consumer-grade scenarios. The second case integrates an FPGA central module with multiple basic EEG acquisition modules to construct a high-throughput BCI system for cost-effective and real-time EEG data acquisition and processing. This configuration allows for flexible deployment in research and clinical applications, including attention index, SSVEP, motor imagery (MI), and emotion recognition. This combination further demonstrates the potential of scalable EEG systems and emphasizes the need for further integration or chipization. These implementations validate the feasibility of compact and efficient EEG devices and highlight the promising applications of scalable BCI system in various fields.

Self-assembled organic monolayer functionalized MIL-88B for selective acetone detection at room temperature

Yuqing Du, Ning Lian, Wei Liu, Zhiheng Zhang, Jiahang Huo, Xin Chen, Junmeng Guo, Peng Cui, Lei Wei, Zuliang Du, Gang Cheng

2025, 1(2): 134-146. DOI: 10.1007/s44275-024-00014-z

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Acetone detection is crucial for diagnosing diseases such as diabetes and lung cancer. Therefore, it is essential to design a room-temperature acetone gas sensor with fast response and recovery times, high sensitivity, high selectivity, and a low detection limit. However, current acetone gas sensors face challenges in achieving high-selectivity detection at room temperature. This study primarily utilizes self-assembled organic monolayer functionalized MIL-88B to prepare selectivity acetone sensors. The results show that the detection sensitivity of the improved sensor to acetone is significantly improved. Compared with the MIL-88B sensor (0.1 ppm), the response value of the MIL-88B@3-aminopropyltrimethoxysilane (APTMS) sensor is increased by about 61.9%. The response to 10 ppm acetone is 83, and the selectivity is greatly improved at room temperature. This can be attributed to the chemical interactions between acetone molecules and APTMS on the sensor surface, which improves the sensor's specific recognition ability for acetone. Additionally, the sensor exhibits better stability and shorter response and recovery times. Consequently, the APTMS functionalization of MIL-88B presents an effective method for preparing room-temperature acetone sensors, combining high sensitivity and selectivity, and offering potential for non-invasive disease diagnosis.

Flexible neuromorphic transistors for neuromorphic computing and perception application

Shuo Ke, Yixin Zhu, Chuanyu Fu, Huiwu Mao, Kailu Shi, Lesheng Qiao, Qing Wan

2025, 1(2): 147-170. DOI: 10.1007/s44275-024-00009-w

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Emulating brain functionality with neuromorphic devices is an emerging field of research. It is extensively considered as the first step to overcome the limitations of conventional von Neumann systems and build artificial intelligent systems. Currently, most neuromorphic transistors are manufactured on rigid substrates, which are difficult to bend and cannot closely fit soft human skin, limiting their appliction scope. The emergence and evolution of flexible electronic devices address a plethora of application and scenario demands. Particularly, the introduction of flexible neuromorphic transistors injects fresh vitality into neuromorphic computing and perception, symbolizing a significant step towards overcoming the limitations of conventional computational models and fostering the development of more intelligent wearable devices. Herein, the recent developments in felxible neuromorphic transistors are summarized and their applications in neuromorphic computing and artificial perception systems are highlighted. The future prospects and challenges of felxible neuromorphic transistors are also discussed. We believe developments in felxible neuromorphic transistors will shed light on future advances in wearable artificial intelligent systems, humanoid robotics and neural repair technology.

Evaluating the potential of two-dimensional materials for innovations in multifunctional electrochromic biochemical sensors: a review

Nadia Anwar, Guangya Jiang, Yi Wen, Muqarrab Ahmed, Haodong Zhong, Shen Ao, Zehui Li, Yunhan Ling, Grégory F. Schneider, Wangyang Fu, Zhengjun Zhang

2025, 1(2): 171-194. DOI: 10.1007/s44275-024-00013-0

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In this review, the current advancements in electrochromic sensors based on two-dimensional (2D) materials with rich chemical and physical properties are critically examined. By summarizing the current trends in and prospects for utilizing multifunctional electrochromic devices (ECDs) in environmental monitoring, food quality control, medical diagnosis, and life science-related investigations, we explore the potential of using 2D materials for rational design of ECDs with compelling electrical and optical properties for biochemical sensing applications.

Manufacturing carbon nanotube transistors using lift-off process: limitations and prospects

Xilong Gao, Jia Si, Zhiyong Zhang

2025, 1(2): 195-198. DOI: 10.1007/s44275-024-00016-x

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Carbon nanotube field-effect transistors (CNT FETs) are regarded as promising candidates for next-generation energy-efficient computing systems. While research has employed the lift-off process to demonstrate the performance of CNT FETs, this method now poses challenges for enhancing individual FET performance and is not suitable for scalable fabrication. In this paper, we summarize the limitations of the lift-off process and point out that future advancements in manufacturing techniques should prioritize the development of etching processes.

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