Guilherme Migliato Marega

Monolayers of transition-metal dichalcogenides, such as MoS₂, have attracted significant attention for their exceptional electronic and optical properties, positioning them as ideal candidates for advanced optoelectronic applications. Despite their strong excitonic effects, the atomic-scale thickness of these materials limits their light absorption efficiency, necessitating innovative strategies to enhance light-matter interactions. Plasmonic nanostructures offer a promising solution to overcome those challenges by amplifying the electromagnetic field and also introducing other mechanisms, such as hot electron injection. In this study, we investigate the vibrational and optical properties of MoS₂ monolayer deposited on gold substrates and gratings, emphasizing the role of strain and plasmonic effects using conventional spectroscopic techniques. Our results reveal significant biaxial strain in the supported regions and a uniaxial strain gradient in the suspended ones, showing a strain-induced exciton and carrier funneling effect toward the center of the nanogaps. Moreover, we observed an additional polarization-dependent doping mechanism in the suspended regions. This effect was attributed to localized surface plasmons generated within the slits, as confirmed by numerical simulations, which may decay nonradiatively into hot electrons and be injected into the monolayer. Photoluminescence measurements further demonstrated a polarization-dependent trion-to-A exciton intensity ratio, supporting the hypothesis of additional plasmon-induced doping. These findings provide a comprehensive understanding of the strain-mediated funneling effects and plasmonic interactions in hybrid MoS₂/Au nanostructures, offering valuable insights for developing high-efficiency photonic devices and quantum technologies, including polarization-sensitive detectors and excitonic circuits.

The Nernst effect, a transverse thermoelectric phenomenon, has attracted significant attention for its potential in energy conversion, thermoelectrics and spintronics. However, achieving high performance and versatility at low temperatures remains elusive. Here we demonstrate a large and electrically tunable Nernst effect by combining the electrical properties of graphene with the semiconducting characteristics of indium selenide in a field-effect geometry. Our results establish a new platform for exploring and manipulating this thermoelectric effect, showcasing the first electrical tunability with an on/off ratio of 10³. Moreover, photovoltage measurements reveal a stronger photo-Nernst signal in the graphene/indium selenide heterostructure compared with individual components. Remarkably, we observe a record-high Nernst coefficient of 66.4 μV K⁻¹ T⁻¹ at ultralow temperatures and low magnetic fields, an important step towards applications in quantum information and low-temperature emergent phenomena.

Data-driven algorithms—such as signal processing and artificial neural networks—are required to process and extract meaningful information from the massive amounts of data currently being produced in the world. This processing is, however, limited by the traditional von Neumann architecture with its physical separation of processing and memory, which motivates the development of in-memory computing. Here we report an integrated 32 × 32 vector–matrix multiplier with 1,024 floating-gate field-effect transistors that use monolayer molybdenum disulfide as the channel material. In our wafer-scale fabrication process, we achieve a high yield and low device-to-device variability, which are prerequisites for practical applications. A statistical analysis highlights the potential for multilevel and analogue storage with a single programming pulse, allowing our accelerator to be programmed using an efficient open-loop programming scheme. We also demonstrate reliable, discrete signal processing in a parallel manner.

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector-matrix multiplications while avoiding the “von Neumann bottleneck.” Despite these promises, no single material platform meets all the requirements for the fabrication of this new processor technology. Recently, flash memories based on monolayer MoS ₂ have been shown to achieve ultra-fast operation, overcoming one of the main drawbacks of this memory type. Together with its other characteristics, this makes them a promising candidate for the base elements of this technology. However, the question remains of how to achieve large-area ultra-fast operation of MoS ₂ monolayer flash memories. In this work, we will compare large-area flash memories based on MoS ₂ used in past realizations of in-memory systems and analyze the improvements needed to achieve ultra-fast performance for in-memory applications.

The growing importance of applications based on machine learning is driving the need to develop dedicated, energy-efficient electronic hardware. Compared with von Neumann architectures, which have separate processing and storage units, brain-inspired in-memory computing uses the same basic device structure for logic operations and data storage^1,2,3, thus promising to reduce the energy cost of data-centred computing substantially⁴. Although there is ample research focused on exploring new device architectures, the engineering of material platforms suitable for such device designs remains a challenge. Two-dimensional materials^5,6 such as semiconducting molybdenum disulphide, MoS₂, could be promising candidates for such platforms thanks to their exceptional electrical and mechanical properties^7,8,9. Here we report our exploration of large-area MoS₂ as an active channel material for developing logic-in-memory devices and circuits based on floating-gate field-effect transistors (FGFETs). The conductance of our FGFETs can be precisely and continuously tuned, allowing us to use them as building blocks for reconfigurable logic circuits in which logic operations can be directly performed using the memory elements. After demonstrating a programmable NOR gate, we show that this design can be simply extended to implement more complex programmable logic and a functionally complete set of operations. Our findings highlight the potential of atomically thin semiconductors for the development of next-generation low-power electronics.

This paper presents a theoretical and experimental study of the effect of ballistic electrons on the optical response of MIM (Metal-Insulator-Metal) like hyperbolic metamaterial structures. The simulated model using standard parameters and the experimental optical transmission show a 20% peak difference due to the presence of ballistic transport in the metal. A semi-analytic approximation based on the Drude's model is used for accurately predicting the optical response of the hyperbolic substrate and plasmon damping in the fabricated metasurfaces.

Excellent mechanical properties and the presence of piezoresistivity make single layers of transition metal dichalcogenides (TMDCs) viable candidates for integration in nanoelectromechanical systems (NEMS). We report on the realization of electromechanical resonators based on single-layer MoS₂with both piezoresistive and capacitive transduction schemes. Operating in the ultimate limit of membrane thickness, the resonant frequency of MoS₂resonators is primarily defined by the built-in mechanical tension and is in the very high frequency range. Using electrostatic interaction with a gate electrode, we tune the resonant frequency, allowing for the extraction of resonator parameters such as mass density and built-in strain. Furthermore, we study the origins of nonlinear dynamic response at high driving force. The results shed light on the potential of TMDC-based NEMS for the investigation of nanoscale mechanical effects at the limits of vertical downscaling and applications such as resonators for RF-communications, force and mass sensors.