ANNLab Research
Graphene Nanoribbon Transistors
Building the Next Generation of Computing Hardware
Modern computing hardware, from mobile devices to large-scale data centers, relies almost entirely on silicon-based transistors. While silicon technology has advanced remarkably over the past several decades, it is now approaching fundamental physical and practical limits. Continued device scaling is becoming increasingly difficult, and improvements in energy efficiency are slowing. At the same time, the rapid expansion of artificial intelligence (AI) workloads is placing unprecedented demands on computational throughput and power consumption, making these limitations more consequential. Our work explores graphene nanoribbons (GNRs) as a potential alternative channel material for next-generation electronics. GNRs are quasi-one-dimensional carbon structures with atomically precise widths and edge configurations, synthesized through bottom-up chemical approaches on surfaces. This synthesis method enables a level of structural control that is difficult to achieve with conventional top-down lithography. Because their electronic band structure depends sensitively on their width and edge geometry, GNRs can be engineered to exhibit semiconducting behavior suitable for transistor applications. In addition, they offer high carrier mobility and exhibit excellent electrostatic properties at very small dimensions. Our research is focused on several key challenges: forming low-resistance electrical contacts to GNRs, integrating high-quality dielectric layers without degrading their properties, and developing scalable fabrication strategies compatible with wafer-level processing. Addressing these issues is essential for translating the intrinsic advantages of GNRs into practical device architectures. Our goal is to enable transistor technologies that extend beyond the limits of silicon, offering improved performance and energy efficiency for future computing systems.
Topological Acoustic Wave Devices
Robust Signal Processing for Next-Generation Wireless
As wireless systems move toward 6G and higher frequencies, the requirements on radio-frequency (RF) components are becoming more stringent. Devices need to operate with greater precision, lower loss, and improved tolerance to variability. Surface acoustic wave (SAW) devices are already a key part of RF front-end systems, widely used for filtering and sensing. However, conventional SAW designs can be sensitive to fabrication imperfections and material defects, which can degrade performance, especially as device dimensions shrink and frequencies increase. Our work looks at SAW devices from a different perspective, inspired by concepts from topological physics. The central idea is to design acoustic waveguides where propagation is inherently robust, meaning that small defects or disorder in the structure do not significantly affect how the wave travels. Rather than relying solely on geometric precision, the goal is to encode robustness directly into the physical behavior of the system. We implement these concepts on piezoelectric substrates such as lithium niobate, using patterned electrodes and periodic structures to shape the acoustic band structure. By carefully engineering these patterns, we can guide surface acoustic waves along predefined paths with reduced scattering and loss. This opens the possibility of building RF components that maintain stable performance even in the presence of fabrication variability. A key direction in our research is adding reconfigurability to these platforms. By dynamically tuning boundary conditions or material responses, the same device can adapt its filtering or routing characteristics in real time. This type of adaptability could be particularly useful in emerging communication systems, where hardware needs to respond to changing environments, as well as in intelligent sensing applications that integrate closely with AI-driven signal processing. Overall, we aim to develop acoustic devices that are not only high-performance, but also inherently robust and adaptable, qualities that are to be essential for next-generation RF technologies.
Semiconducting Behavior of Chalcopyrite
Connecting Semiconductor Physics to Sustainable Mining
Chalcopyrite (CuFeS₂) is the most abundant copper-bearing mineral and a primary source of copper for modern industry, including electrical infrastructure and renewable energy technologies. Despite its importance, it remains one of the most difficult sulfide minerals to process. Its resistance to dissolution limits extraction efficiency and increases both energy consumption and environmental impact during mining. An aspect that is often overlooked is that chalcopyrite is also a semiconductor. Its electrical behavior depends strongly on composition, defect density, and crystal structure. These electronic properties can influence interfacial charge transfer and surface reactions, which are central to leaching processes. We hypothesize that variability in these properties helps explain why some chalcopyrite samples dissolve relatively readily, while others are far more resistant. In our work, we investigate the electrical transport properties of chalcopyrite samples sourced from different geological environments. Using Hall effect measurements, we extract key parameters such as carrier concentration, mobility, and dominant carrier type. These measurements are then correlated with microstructural features and compositional variations, including defect distributions and impurity content. Our goal is to link semiconductor behavior with leaching performance at a mechanistic level. By establishing these connections, our objective to inform more selective and efficient extraction strategies, approaches that could reduce chemical usage, lower energy demand, and improve overall sustainability in copper production.
Emerging Ideas & Out-of-the-Box Science
Exploring New Directions at the Boundaries of What We Know
In addition to our core research areas, we pursue a set of exploratory projects that do not yet align with established themes. These efforts are often motivated by unexpected experimental results or by recognizing conceptual links between fields that do not typically intersect. We treat this space as deliberately open-ended. Early-stage ideas are allowed to develop without being constrained by predefined outcomes, which makes it easier to test unconventional hypotheses or directions that carry some uncertainty. In many cases, this flexibility is what allows promising ideas to surface in the first place. When an idea begins to show traction, through preliminary data, external interest, or potential applications, it can transition into a more structured line of work. This process often leads not only to new research directions, but also to tangible outcomes such as novel device concepts, intellectual property, and, in some cases, entirely new technological approaches.