Abstract I recently returned from a trip to India, where I met with the leadership of the SID India Chapter and the team at IIT Kanpur, home to one of India's largest display research institutes: the National Centre for Flexible Electronics (or FlexE).

The past few months have been very exciting for our society with interesting conferences and presentations that explore new display research and development.

The challenge of fabricating transparent and conductive (T/C) films and patterns for applications in flexible electronics, touch screens, solar cells, and smart windows remains largely unsolved. Traditional fabrication techniques are complex, costly, time‐consuming, and struggle to achieve the necessary precision and accuracy over electronic and optical properties. Here, hypersurface photolithography (HP), which integrates microfluidics, a digital micromirror device, and photochemical surface‐initiated polymerizations is used to create polymer brush patterns. The high‐throughput optimization enabled by HP provides conditions to fabricate patterns composed of cross‐linked polymer brushes containing Au‐binding 2‐vinylpyrrolidine (2VP) groups with precise control over the height and the composition at each pixel. Au nanoparticles (AuNPs) are incorporated into the polymer brush patterns through in situ reduction of Au ions, resulting in T/C composite AuNP/polymer brush patterns. The sheet resistance at 100 mA of a 2VP‐AuNP‐functionalized patterns on a glass substrate is 0.42 Ω sq −1 with 86% transmittance of visible light. Additional patterns demonstrate multiplexing by copatterning rhodamine B functionalized fluorescent polymer brushes and AuNP/polymer brush conductive domains. This work solves the challenge of creating T/C films by forming metal‐polymer composites from polymer brush patterns, offering a scalable solution for electronic and optical device development and fabrication.

In this paper, we introduce a sensor designed for robotic fingers which can provide information on the displacements induced by external forces. Our sensor uses LEDs to sense the displacement between two plates connected by a transparent elastomer; when a force is applied to the finger, the elastomer displaces and the LED signals change. We show that using LEDs as both light emitters and receivers in this context provides high sensitivity, allowing such an emitter and receiver pairs to detect very small displacements. We characterize the standalone performance of the sensor by testing the ability of a supervised learning model to predict complete force and torque data from its raw signals, and obtain a mean error between 0.05 and 0.07 N across the three directions of force applied to the finger. Our method allows for compact packaging (fitting at the base of a finger) with no amplification electronics, low cost manufacturing, easy integration into a complete hand, and high overload shear forces and bending torques, suggesting future applicability to complete manipulation tasks.

Recently, rare earth doped perovskites materials have demonstrated excellent photoluminescence characteristics and gained attention in the field of multifunctional optoelectronics applications. In this work, a crystalline Pr-doped lanthanum titanate (La2Ti2O7) thin film was prepared by using a radio frequency sputtering technique. The Pr-doped La2Ti2O7 film exhibited high transmittance of around 70% in the visible light region. Photoluminescence emission intensity depends on the concentration of Pr ions, which is attributed to f-f level transition Pr3+ ions. The Pr-doped La2Ti2O7 film on a mica substrate showed a remarkable relative PL intensity enhancement of around 658% under mechanical strain, which can be ascribed to strain-induced local distortion of the crystal symmetry due to the incorporation of Pr3+ ions. Furthermore, we report the Pr-doped La2Ti2O7 film was utilized in a piezoelectric nanogenerator that yielded an output voltage of around 1.8V when pressure was applied. These properties suggest that Pr-doped La2Ti2O7 is a promising flexible material for piezoelectric energy harvesting and highly sensitive luminescent device applications.

This paper investigates the dependence of effective carrier mobility on the channel length in oxide thin-film transistors (TFTs). Bottom-gate staggered TFTs fabricated with a sputtered indium-gallium-zinc-oxide channel exhibit a substantial increase in field-effect mobility with decreasing channel length, which is at variance with typical manifestation of contact resistance. An original model is thus proposed to describe the channel-length-dependent mobility in these TFTs. By decoupling local and intrinsic transport properties affecting the drain current, the model reproduces and rationalizes the observed phenomena. These results provide both a practical modeling tool and fundamental insights into the behaviors of oxide TFTs associated with the charge injection at their metal/semiconductor interface.

This issue of Information Display is exciting for several reasons. It is timed to be printed and circulated during Display Week 2025 and has content that can help make the most of your time at the conference and exhibition.

Neuromorphic computing [1], inspired by the energy-efficient and parallelized architecture of the human brain, represents a paradigm shift in computing. This approach not only drives innovative hardware designs but also inspires novel network architectures like spiking neural networks (SNNs), which process information as discrete spike events. However, scalability in neuromorphic systems is constrained by the large hardware footprint. Realizing multimodal functionality using the same set of hardware primitives can offer a promising solution to these limitations. In this work, we present a dual encoder-neuron circuit based on a nanoporous graphene (NPG) memristor device [2]. The graphene leaky integrate-and-fire (GLIF) circuit has a versatile multimodal design that combines the roles of a LIF neuron and a spike encoder within the same architecture. This design mimics the dual functionality of biological neurons, which encode and process signals locally. The spike encoding capability of the circuit is further revealed using single and double layer SNN networks for pattern recognition tasks using the Modified National Institute of Standards and Technology (MNIST) dataset. Inset of Figure 1(a) shows the schematic of the fabricated NPG device with a channel length of 100 µm. The device has a lateral structure with NPG channel and gold (Au) electrodes. Figure 1(a) shows the current-voltage (I-V) characteristics of the fabricated NPG device which shows a threshold switching behavior with a wide hysteresis window and a threshold voltage (V th ) of 4.9 V. A behavioral SPICE model is developed based on a voltage-controlled switch model. It is seen from Figure 1(a) that the I-V curves simulated using the SPICE model matches the experimentally observed device switching characteristics. This reveals that the simplified SPICE model can be a good substitute for complex Verilog based models. Based on the SPICE model, we designed a simple neuron circuit with a resistor (R s , 12 kΩ) in series with a parallel combination of a capacitor (C m , 10 nF) and the NPG device (SPICE model). Figure 1(b) shows the variation of the membrane potential (V m ) and the output spike current in response to the input pulse voltage (V in , 6 V). V m shows a clear leaky integration behavior and full reset to zero voltage after the spike response. These are essential attributes of a bioplausible LIF neuron circuit. In order to develop the multimodal GLIF circuit, the output spike frequency of the LIF neuron circuit is plotted as a function of the R s values. This mapping allows pixel values from MNIST input images to be directly translated into normalized conductance values (G/G 0 ). Hence, each pixel is represented as a normalized conductance value, establishing a clear correlation between pixel intensity and spike frequency. This core idea is further used to develop the GLIF encoder based on the same neuron circuit as before. Based on the dual encoder-neuron circuit, we designed a single layer SNN for recognising the handwritten digits from the MNIST dataset. Figure 1(c) shows the spike-encoded images for the MNIST digits “2” and “5”. The probability of spiking in each timestep is proportional to the spiking frequency. The spike encoded images at each time step reveal the contours of the original input images using sparse representation. These sparse matrices highlight the energy efficiency and computational advantages of the GLIF system. The performance of the dual encoder-neuron system is evaluated by training the single layer SNN using both the GLIF encoder and neuron circuit as integral components. The single layer SNN recorded a high pattern recognition accuracy of 90.77% which is comparable to the purely software-based implementation (92.69%). To explore the scalability of the GLIF system, we implemented a double-layer SNN using the GLIF system, achieving a high recognition accuracy of 97.37%. The GLIF circuit exemplifies how reconfigurable primitive components can drive the development of scalable neuromorphic hardware. References [1] Udaya Mohanan, K. Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations. Nanomaterials 2024, 14, 527. [2] Mohanan, K. U.; Sattari-Esfahlan, S. M.; Cho, E.-S.; Kim, C.-H. Optimization of Leaky Integrate-and-Fire Neuron Circuits Based on Nanoporous Graphene Memristors. IEEE Journal of the Electron Devices Society 2024, 12, 88–95. Image Caption: Figure 1: (a) NPG device I-V characteristics showing the threshold switching behavior for both the experimental and SPICE simulation fit. The inset shows the schematic for the device with NPG channel and gold (Au) electrodes. (b) Variation of the membrane potential with the input voltage. The corresponding output spike pattern is also shown. (c) Encoded spike patterns of two different input images from the MNIST dataset for different time steps. Figure 1

The rapid development of wearable artificial intelligence devices based on memristor crossbar arrays has increased the demand for flexible electronics. However, fabricating crossbar arrays on flexible substrates faces inherent challenges, notably due to the complex fabrication process at low temperatures. Moreover, ensuring the stability and reliability of memristor device remains a crucial issue. To address these issues, this study introduced N-doped TaOx (N:TaOx) as a flexible memristor crossbar array fabricated via atomic layer deposition directly on a flexible substrate at an exceptionally low temperature (150 °C). The flexible PET/ITO/N:TaOx/TiN memristor device exhibited forming-less bipolar resistive switching properties with analog memory characteristics. This was accomplished by increasing the nitrogen doping concentration and effectively reducing oxygen-related defects in TaOx. The amorphous-phase flexible N:TaOx memristor demonstrated remarkable stability, enduring 500 switching cycles and retaining its state for 24 h during bending tests involving 104 bending cycles at 2.5 mm bending radius. Furthermore, a 6 × 6 flexible memristor crossbar array was fabricated successfully, with all 36 devices exhibiting well-defined memristor behavior and minimal variation attributed to the film's uniformity achieved through ALD process. Additionally, by programming the tunable conductance of each device in the array, characters of desired shapes can be formed and read. Regarding their synaptic behavior via long-term potentiation and depression, the proposed flexible memristor device showed an outstanding accuracy of 96.44 % in image recognition tasks under extreme bending conditions, employing the MNIST and Fashion-MNIST datasets. The N:TaOx memristor deposited at low temperatures thus exhibits significant potential for use in wearable neuromorphic hardware applications due to its high density, high performance, reliability, and precise image recognition.

In this work, we use MEMS microphones as vibration sensors to simultaneously classify texture and estimate contact position and velocity. Vibration sensors are an important facet of both human and robotic tactile sensing, providing fast detection of contact and onset of slip. Microphones are an attractive option for implementing vibration sensing as they offer a fast response and can be sampled quickly, are affordable, and occupy a very small footprint. Our prototype sensor uses only a sparse array (8-9 mm spacing) of distributed MEMS microphones (<$1, 3.76 x 2.95 x 1.10 mm) embedded under an elastomer. We use transformer-based architectures for data analysis, taking advantage of the microphones' high sampling rate to run our models on time-series data as opposed to individual snapshots. This approach allows us to obtain 77.3% average accuracy on 4-class texture classification (84.2% when excluding the slowest drag velocity), 1.8 mm mean error on contact localization, and 5.6 mm/s mean error on contact velocity. We show that the learned texture and localization models are robust to varying velocity and generalize to unseen velocities. We also report that our sensor provides fast contact detection, an important advantage of fast transducers. This investigation illustrates the capabilities one can achieve with a MEMS microphone array alone, leaving valuable sensor real estate available for integration with complementary tactile sensing modalities.

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Three-dimensional (3D) polycrystalline perovskite is emerging as a promising candidate for high -brightness light -emitting applications. However, 3D perovskite light -emitting diodes (PeLEDs) are difficult to achieve high brightness, efficiency, and stability simultaneously, as they are limited by the trade-off between the advanced external quantum efficiency (EQE) and the inevitable roll -off. Here, we develop a 3D FAPbI 3 perovskite material system that enables high brightness, efficiency, and long device lifetime simultaneously, engineered by an alkyl -chain -length -dependent ammonium salt molecule modulation strategy. We elucidate the roles of alkylammonium salts on crystal orientation management, grain size control, non -radiative recombination suppression, and thus device performances. Consequently, we simultaneously obtain efficient, ultra -bright, and stable PeLEDs with a high EQE of 23.2%, a record radiance of 1,593 W sr - 1 m - 2 and a record lifetime of 227 h (at a high current density of 100 mA cm - 2 ), representing the best performance for the DC -drive near -infrared (NIR) PeLEDs at high -brightness levels.

Organic electronics is an enabler of future wearable and intelligent technologies. However, the majority of researches on organic devices employ vacuum-evaporation methods for their metallization, blurring the manufacturing advantages of solution-processable semiconductors. We present a combined experimental and theoretical investigation into the suitability of silver inkjet-printing as a fast, low-cost, low-temperature, and ambient processing option to produce high-quality contacts for field-effect transistors. Printing steps are carefully optimized to solve wettability, film-delamination, and charge-injection issues, for yielding p-type transistors with a soluble diketopyrrolopyrrole polymer as a channel material. Drift-diffusion simulation is carried out in parallel to reproduce the terminal characteristics of the fabricated transistors, revealing fundamental insights into charge traps, carrier mobility, electrode energy, and doping. Finally, resistor- and transistor-loaded digital inverters were operated on a circuit simulator under various conditions to address their applicability.

We demonstrate a new implementation of structured illumination microscopy, in which a tunable electrowetting prism is incorporated in the microscope to “wobulate” the structured illumination on the sample. Optical sectioning is demonstrated with fluorescent beads.

Monitoring urban green spaces (UGSs) is crucial for achieving sustainable urban development and ecological resilience. Leveraging LoRaWAN technology, a wireless environmental sensing system was developed and implemented to monitor soil moisture dynamics across seven diverse UGSs over a year. Analyses revealed notable variations in soil moisture influenced by vegetation types, soil conditions and physical settings. Seasonal trends indicated lower summer soil moisture in some UGSs resulting from increased evapotranspiration, while others maintained higher soil moisture due to more frequent irrigation. The soil moisture response to rainfall was quantitatively modeled, demonstrating the increase in soil moisture is highly positively dependent on rainfall amount and negatively dependent on initial moisture level. Both factors were significant (p<0.001) in most cases, and the models’ adjusted R2 values were all above 0.65 except for one node. The findings also unveiled more dynamic ranges of UGS runoff coefficients than government guideline values, especially high runoff coefficients (0.4 to 1.0) for rainfall events above 50 mm. Therefore, although existing UGSs can help absorb smaller storms, proactive drainage systems are needed for UGSs to handle extreme events. The study highlights LoRaWAN's efficacy in urban environmental monitoring and provides valuable insights for managing and optimizing UGSs, especially in stormwater management.

We present a method of monolithically integrating GaN microLEDs with an IGZO TFT backplane to produce an activematrix microdisplay. After discussion of the fabrication process, individual LEDs, TFTs, and the integrated system are characterized. Results demonstrate a 32x32 pixel, 78.4 PPI microdisplay with luminance exceeding 1500 nits. This type of monolithic microdisplay forges the path forward for future high luminance integrated displays to enable augmented and mixed reality applications.

Objective:We present the "UmboMic," a prototype piezoelectric cantilever microphone designed for future use with totally-implantable cochlear implants. Methods:The UmboMic sensor is made from polyvinylidene difluoride (PVDF) because of its low Young's modulus and biocompatibility. The sensor is designed to fit in the middle ear and measure the motion of the underside of the eardrum at the umbo. To maximize its performance, we developed a low noise charge amplifier in tandem with the UmboMic sensor. This paper presents the performance of the UmboMic sensor and amplifier in fresh cadaveric human temporal bones. Results:When tested in human temporal bones, the UmboMic apparatus achieves an equivalent input noise of 32.3 dB SPL over the frequency range 100 Hz to 7 kHz, good linearity, and a flat frequency response to within 10 dB from about 100 Hz to 6 kHz. Conclusion:These results demonstrate the feasibility of a PVDF-based microphone when paired with a low-noise amplifier. The reported UmboMic apparatus is comparable in performance to a conventional hearing aid microphone. Significance:The proof-of-concept UmboMic apparatus is a promising step towards creating a totally-implantable cochlear implant. A completely internal system would enhance the quality of life of cochlear implant users.

We report the first demonstration of displays driven by embedded transistors that were additively manufactured entirely by aerosol jet printing. The backplanes of the liquid crystal displays (LCDs) consist of transistors printed from graphene, carbon nanotubes, and crystalline nanocellulose onto a glass substrate with prepatterned indium tin oxide electrodes. We addressed challenges of integrating fully printed devices into both the crossbar array structure and layered vertical structure required for an LCD, showing successful pixel switching at up to 60 Hz. As these thin-film transistors are printed exclusively from carbon-based recyclable materials, without high temperatures or vacuum processing, they offer a promising means for reducing waste in future display technologies.

This letter proposes a novel electrochemical spectroscopic technique for selective detection of glucose in solution using NiWO4 nanostructured receptor layers deposited on interdigitated structures to fabricate two terminal resistive devices. On exposing the device to glucose in solution (10-50 mmol/L) in a cell configuration with the sensor as the working electrode and analyzing the second derivative of the obtained I-V plot, four monotonically increasing peaks were observed, respectively, at 0.2, 1.2, 1.4, and 2.4 V in the second-harmonic (d(2)I/dV(2) versus V) plot. The spectrum obtained was very specific to glucose, and the peaks were attributed to glucose solution over potential, electrolytic potentials of water and glucose solution, and hydroperoxy intermediate formation resulting from the NiWO4-glucose and NiWO4-H2O interactions. The device response was calculated from the monotonic variations of the peak intensities in the positive voltage range and current in the negative voltage range with positive voltage peak responses of 28.6 and 5.05 times at 0.3 and 2.5 V, respectively, positive voltage peak inversion responses of -3.9 and -5.34 times at 1.1 and 1.4 V, respectively, and negative voltage response of 2.1 times for 50 mmol/L of glucose. When exposed to a mixed solution, the sensor presented a spectrum specific to glucose. Thus, the proposed technique and the device propose a novel solution for a practically usable ultraselective sensor and solve the selectivity issues of conventional conductometric sensors.