Advanced Electronic Materials最新文献

Indium gallium zinc oxide (IGZO) thin film transistors (TFTs) with high stability are highly desired for future memory devices, which demand high stabilities. However, residual precursors inevitably present in the dielectric layers deposited by atomic layer deposition (ALD) introduce hydrogen contamination to the devices, thereby impairing their electrical stabilities. In this work, an effective approach is proposed: performing oxygen plasma treatment on the dielectric-channel interface to suppress hydrogen diffusion, thereby enhancing the electrical stability of IGZO TFTs. X-ray photoelectron spectroscopy (XPS) results confirm the suppression effect of oxygen treatment on hydroxyl groups, while time of flight secondary ion mass spectrometry (TOF-SIMS) revealed a 16.46% reduction in hydrogen content within the treated Al₂O₃ layer. The devices after treatment exhibited a field-effect mobility (µ_eff) of 17.4 cm²/V·s, a threshold voltage (V_TH) of −0.04 V, and a subthreshold swing (SS) of 84.7 mV/dec, with an optimized oxygen plasma power of 50 W. The positive bias temperature stability of the device is significantly promoted due to reduced hydrogen content. The V_TH shift (ΔV_TH) is merely 3.5 mV under a bias electric field of 2 MV/cm for 10 000 s. Such treatment provides a promising solution for the integration of IGZO TFTs with Si-based electronics.

The emulation of neuronal activity requires complex circuits that integrate multiple passive and active components, leading to a high circuit footprint. It is therefore apparent that developing a single device that can be used to emulate both synaptic and neuronal activity would allow less complexity and a much lower circuit footprint having significant impact on practical applications of neuromorphic systems. Herein, mixed halide perovskite-based transistors are demonstrated to exhibit volatile memristive behavior that responds to both light and electric fields, opening the path for optoelectronic control of neuron-like functions. Specifically, it is shown that by applying a low compliance current (I_CC) during drain current–voltage (I_D–V_D) measurements, volatile memristive switching behavior is reported. A set of volatile I_D–V_D curves is presented under various gate biases, indicating a gate-enabled shift of the low-resistance state set voltage to higher values. The volatile nature of the device operated at low I_CC allowed the demonstration of gate-tunable neuronal functions, including amplitude- and frequency-modulated spike firing. Furthermore, linear potentiation protocols and Leaky Integrate-and-Fire behavior is reported, while light pulses are shown to induce both photonic potentiation and graded optical neurons, opening the path for emulating neuron functions tunable by both light and electric fields.

Graphene flake dispersions can form conductive thin films via well-established, scalable deposition methods, such as spin-coating. These conductive graphene flake networks constitute sensing layers suitable for chemiresistive CMOS-compatible humidity sensors. Electrical noise is a parameter that affects sensor performance, and minimizing it requires thorough knowledge of the noise and its sources specific to the application. In this work, we present a phenomenological study of noise in resistive graphene sensors made from different graphene flake dispersions. We measured noise as a function of the graphene flake type, thickness of the graphene flake network, and sensor area. We conducted noise and sensitivity measurements to select the most suitable flake type for humidity sensing. We studied the influence of the temperature on the sensitivity and noise, and evaluated the humidity-dependent noise. Finally, a sensor operating mode is defined which enables humidity sensing well beyond the 1 % detection limit and with minimized resistance drift.

A comprehensive prediction of the electrical properties of graphene, independent of field-effect transistor (FET) fabrication, could accelerate the development of graphene wafers and electronic materials. Such a capability may also enable the implementation of in-line inspection techniques during production. In this study, as a preliminary step toward predicting electrical properties solely from images, the relationship between carrier mobility and graphene surface roughness using atomic force microscopy (AFM) is investigated. Although no correlation is observed between carrier mobility and conventional roughness metrics such as arithmetic mean roughness (S_a) and maximum height (S_z), persistent homology analysis—a mathematical framework that captures topological connectivity—revealed distinctly different persistence diagrams for samples with nearly identical S_a values but differing carrier mobilities. It is found that graphene structures conforming to pronounced substrate undulations, rather than convex features such as wrinkles or bubbles, led to decreased carrier mobility. This study serves as a foundational investigation, demonstrating the potential to predict the electrical properties of graphene using only surface morphology images, made possible through the application of persistent homology analysis.

Strong correlation effects in transition metal oxides and their sensitivity to external stimuli in driving phase transitions have been widely explored. However, the richness of the metastable and coexisting quantum states beyond the phase transition temperature is less explored. We employ a highly strained manganite film on a twinned substrate of $�{\mathrm{LaAlO}}_3$ and show that the cumulative effect of such structural disorder leads to temperature-driven subtleties in the orbital hybridization of the coexisting ground states. This drives the film to electrical instabilities and the associated non linear transport leads to oscillatory dynamics, mimicking neurons with frequencies that are within the range of frequencies associated with brain waves. Our findings open up possibilities for on-demand tailoring of such devices for applications in brain-computer interfacing.

The growing demand for artificial intelligence and high-performance computing accelerates concerns over leakage power in highly integrated semiconductor systems. Power gating can reduce the leakage power by disconnecting idle logic blocks from the power supply through a sleep transistor. However, conventional metal-oxide-semiconductor field-effect transistor-based sleep transistors exhibit significant leakage currents and area overhead. As promising alternatives for power gating devices, microelectromechanical systems (MEMS) switches have gained significant attention due to their near-zero off-state leakage current. Nevertheless, their practical use in power gating has been limited by a fundamental trade-off between low on-resistance and fast switching time. This study demonstrates that extreme minimization of the air gap is the key to simultaneously reducing on-resistance and switching time. By introducing a 20 nm nano air gap and high-stiffness structural design, we realize—for the first time—a MEMS switch that combines ultra-low on-resistance (0.95 Ω) with ultra-fast switching time (30 ns), while maintaining off-state leakage below 100 fA. All fabrication processes remain within the back-end-of-line thermal budget, enabling monolithic 3D integration with minimal area overhead. These results establish nano gap MEMS switches as strong candidates for power gating in next generation low-power semiconductor systems.

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide ($�{\mathrm{VO}}_2$), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

This study examines the effects of 5 MeV proton irradiation, applied at fluences of 1 × 10¹¹, 1 × 10¹², 1 × 10¹³, and 1 × 10¹⁴ cm⁻², on 20 nm thick SnO_2-x thin films and field-effect transistors (FETs) with Sn-doped In₂O₃ (ITO) electrodes. In the SnO_2-x films, both carrier concentration and mobility increased steadily with rising fluences. The irradiated ITO layers displayed higher carrier concentrations but reduced mobilities compared with their pristine counterparts. Higher conductivity of the constituent films resulted in a negative shift in threshold voltage (V_th) and an enhanced drain current (I_DS) in the SnO_2-x FETs. The greater the fluence, the more pronounced these changes became. Regardless of the fluence, the on/off ratios of the FETs remained stable at ∼10⁶, indicating minimal structural damage. Moreover, the irradiation-induced changes are not temporary. When the irradiated devices are stored in air for a month or annealed at 200 °C in air for 2 h, both I_DS and V_th became more stabilized. Collectively, these results demonstrate that SnO_2-x FETs offer radiation tolerance and electrical stability, making them strong candidates for radiation-hardened electronics in space environments.