Magnonics addresses the physical properties of spin waves and utilizes them for data processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency range, utilization of nonlinear and nonreciprocal phenomena, and compatibility with CMOS are just a few of many advantages offered by magnons. Although magnonics is still primarily positioned in the academic domain, the scientific and technological challenges of the field are being extensively investigated, and many proof-of-concept prototypes have already been realized in laboratories. This roadmap is a product of the collective work of many authors, which covers versatile spin-wave computing approaches, conceptual building blocks, and underlying physical phenomena. In particular, the roadmap discusses the computation operations with the Boolean digital data, unconventional approaches, such as neuromorphic computing, and the progress toward magnon-based quantum computing. This article is organized as a collection of sub-sections grouped into seven large thematic sections. Each sub-section is prepared by one or a group of authors and concludes with a brief description of current challenges and the outlook of further development for each research direction.

In the post-CMOS scenario, field coupled nanotechnologies represent an innovative and interesting new direction for electronic nanocomputing. Among these technologies, nanomagnet logic (NML) makes it possible to finally embed logic and memory in the same device. To fully analyze the potential of NML circuits, design tools that mimic the CMOS design-flow should be used for circuit design. We present, in this paper, the latest and improved version of Torino Politecnico Nanotechnology (ToPoliNano), our design and simulation framework for field coupled nanotechnologies. ToPoliNano emulates the top-down design process of CMOS technology. Circuits are described with a VHSIC hardware description language netlist and layout is then automatically generated considering in-plane NML (iNML) technology. The resulting circuits can be simulated and performance can be analyzed. In this paper, we describe several enhancements to the tool itself, like a circuit editor for custom design of field coupled nanodevices, improved algorithms for netlist optimization and new algorithms for the place and route of iNML circuits. We have validated and analyzed the tool by using extensive metrics, both by using standard circuits and ISCAS'85 benchmarks. This contribution highlights the improvements of ToPoliNano, which is now a innovative and complete tool for the development of iNML technology.

Notwithstanding the increasing interest in Molecular Quantum-Dot Cellular Automata (MQCA) as emerging devices for computation, a characterization of their behavior from an electronic standpoint is not well-stated. Devices are typically analyzed with quantum physics-based approaches which are far from the electronic engineering world and make it difficult to design, simulate and fabricate molecular devices. In this work, we define new figures of merits to characterize the molecules, which are based on the post-processing of results obtained from ab initio simulations. We define the Aggregated Charge (AC), the electric-field generated at the receiver molecule (EFGR), the Vin–Vout and Vin–AC transcharacteristics (VVT and VACT), the Vout maps (VOM) and the MQCA cell working zones (CWZ). These quantities are compatible with an electronic engineering point of view and can be used to analyze the capability of molecules to propagate information. We apply and verify the methodology to three molecules already proposed in the literature for MQCA and we state to which extent these molecules can be effective for computation. The adopted methodology provides the quantitative characterization of the molecules necessary for digital designers, to design digital circuits, and for technologists, to the future fabrication of MQCA devices.

The post-CMOS scenario poses many challenges to researchers. Innovative solutions must be found to further improve electronic circuits. Exploiting the potential offered by the third dimension is clearly one of the best possibilities available. However, due to the lack of a simple and straightforward methodology it is difficult to analyze and compare beyond- CMOS technologies. We tackle this challenge by presenting a framework that enables the design of 3D circuits based on field-coupled technologies. The tool is called MagCAD and is part of the ToPoliNano design suite, created to design and simulate circuits based on emerging technologies by applying a top-down methodology. Right now, MagCAD supports the two main implementations of Nano Magnetic Logic (NML), the in-plane NML (iNML) and the perpendicular NML (pNML). However it is designed to be easily extended to other beyond- CMOS technologies. Researchers can design pNML circuits by using MagCAD, which embeds design rules, physical models and technological parameters. The compact model and the physical properties of these cells are based on experimental results. After the design phase, a Register-Transfer-Level (RTL) model of the circuit is automatically extracted by MagCAD. The model is written in VHSIC Hardware Description Language (VHDL) and has been validated through experiments. The extracted model can be simulated with fast HDL-simulators; this makes it possible to verify the behavior and extract the performance of the designed circuit. With MagCAD, designers have the possibility to easily design, simulate and compare 3D NML circuits, exploring the advantages provided by the third dimension freely.

Beekeeping plays an essential role in maintaining ecosystems through pollination and enhancing biodiversity. The presence of the queen bee inside the hive is an important indicator for the health of the bee colony. Monitoring the health of honeybees and their hives is crucial not only for bees but also for the entire ecosystem. This article introduces a Tiny Machine Learning application for edge computing in Internet of Things (IoT) systems, designed to predict the queen bee’s presence. The solution, implemented on a low-power microcontroller, listens to the sound produced by honeybees and aids beekeepers by automating health assessments of the colony. The system utilizes audio recordings of honeybees combined with Artificial Intelligence techniques, while the second focuses on optimizing a feature extraction algorithm from these recordings to minimize latency and energy use in the IoT setup. The findings show that despite the implementation of a simpler Machine Learning (ML) model and audio preprocessing with lower computational precision, the final metrics remain comparable to those analyzed, with only a limited reduction.

Field‐coupled nanocomputing represents one of the possible proposals for the post‐Complementary Metal Oxide Semiconductor (CMOS) scenario. Contrarily to standard technology, the information is not propagated using electron transport, but via field interactions among single elements. The molecular quantum‐dot cellular automata (QCA) is one of the most promising implementations; redox centres of oxidised molecules are used to concentrate charges. Coulomb interaction between redox centres enables the information propagation. The necessity for charge transport is overcome, entailing very low power consumption notwithstanding the nanometric size and the very high expected operating frequency. Nevertheless, as the Coulomb interaction strongly depends on the distance between charges, the position of each molecule plays a relevant role in the interaction. This work investigates the information propagation of a possible molecular wire thiolated on a non‐ideal gold surface, where the intermolecular distance may vary due to the surface roughness and possible defects introduced in the formation of the molecular wire. The efficiency of the information transfer is analysed with the aim of providing significant constrains and suggestions for future fabrication steps.