ABSTRACT Based on first‐principles calculations and symmetry analysis, we report a magnetization‐orientation‐controlled topological phase transition and anomalous transport effects in hexagonal MnSb. Owing to its remarkably low magnetic anisotropy energy (0.465 meV), the magnetization direction in MnSb can be readily manipulated by external perturbations. Without spin‐orbit coupling (SOC), a symmetry‐protected Dirac point (DP) lies 9 meV below the Fermi level. Upon inclusion of SOC, this DP undergoes an evolution as a function of magnetization orientation: it opens a gap at θ = 0° (magnetization along the a ‐axis) due to the symmetry breaking, and transforms into four Weyl points at θ = 90° (magnetization along the c ‐axis). These topological transitions are accompanied by significant Berry curvature reconstruction, which profoundly influences the anomalous transport responses. Specifically, the anomalous Hall conductivity increases monotonically from –100.64 Ω −1 cm −1 at θ = 0° to a maximum of –754.72 Ω −1 cm −1 at θ = 90°, whereas the anomalous Nernst coefficient undergoes a sign reversal, changing from +0.50 Am −1 K −1 to –0.09 Am −1 K −1 as the magnetization rotates. Our work establishes a design principle for engineering magnetic topological materials, with MnSb serving as a representative example to explore the interplay between magnetic order and topology‐driven transport phenomena. These findings bridge magnetism, topology, and transport physics, opening a pathway toward novel spintronic devices through tunable magnetization direction.

Abstract Nitrogen dioxide sensors are important for environmental monitoring, and OFETs‐based devices feature high sensitivity, low production cost and power consumption. While transient pulsed saturation measurements are the most common approach to measure the sensor response, here we systematically compare it with the periodic transfer curves measurement method in both linear and saturation regimes for C8‐BTBT OFETs sensitive to NO 2 . We show that the sensitivity strongly depends on the measurement routine, governed by competition for deep trap sites between the electrically injected holes and NO 2 ‐induced doping. The transfer curves method reveals that mobility change dominates in the saturation regime, while threshold voltage shift dominates in the linear regime, confirming deep traps role as key sensing receptor sites. Pulsed measurements, especially in the linear regime, yielded the highest sensitivity (218 ± 18%/ppm) by combining low charge density with low duty cycle kinetics to maximize the initial deep trap availability. DFT calculations support preferential hole transfer from NO 2 to the trap states. Altogether confirming that minimizing trap filling by injected charge (i.e., lower current density operation) enhances OFET sensitivity. This dependence on the measurement routine persists even for OFETs containing metalloporphyrin receptor layers. These findings provide guidelines for optimizing OFET sensor design and operation.

Abstract Ferroelectric capacitors (Fe‐Caps) exhibiting memcapacitive behavior are emerging as a compelling platform for low‐power capacitive in‐memory computing (IMC). Their inherently open‐circuit nature suppresses static current and sneak paths, offering a distinct advantage over resistive IMC counterparts. In this work, an experimental demonstration is presented of a cross‐point Fe‐Cap array prototype, establishing capacitive IMC with non‐destructive readout characteristics. The devices exhibit robust reliability, sustaining more than 10 5 read cycles and 10 7 write cycles, with retention projected beyond 10 years without memory collapse. At the system level, a 4 × 2 array achieves 100% accuracy in 2‐pixel × 2‐pixel pattern‐recognition tasks, while scaling to a 16 × 4 array and letter‐recognition tasks highlights the outstanding scalability of Fe‐Cap‐based IMC platforms. These results not only validate the Fe‐Caps as both a functional and reliable IMC element but also provide an experimental framework for straightforward evaluation of IMC functionality, marking a milestone toward practical and energy‐efficient neuromorphic hardware.

Abstract To overcome Boltzmann thermal limitation, the study investigates isolated‐state field‐effect transistors based on armchair SnSe nanoribbons using first‐principles calculations and quantum transport simulations with various edge passivation strategies, particularly fluorine (‐F) passivation. The results show that ‐F passivation enabling sub‐60 mV decade −1 switching behavior. Key parameters including E sub‐Gap , E Gap , and Δ E play a crucial role in device performance improvement. By introducing asymmetric underlap (UL), the design achieves a steep subthreshold swing (SS) of 46 mV decade −1 and an ON‐state current of 502 µA µm −1 . Compared to symmetric UL, asymmetric UL designs enable better device integration and enhanced performance, thereby meeting the scaling requirements for advanced devices. Further performance enhancement is realized through strain engineering: a 2% uniaxial tensile strain reduces the carrier effective mass and improves band alignment, increasing ON‐state current to 644 µA µm −1 . Incorporating a gate‐all‐around FETs further boosts the current to 796 µA µm −1 without strain and up to 1019 µA µm −1 with strain, while maintaining SS below 60 mV decade −1 , satisfying the International Technology Roadmap for Semiconductors requirements for both high‐performance and low‐power devices. The findings provide theoretical guidance for MOSFET‐based devices with both steep SS and enhanced ON‐state currents, contributing to the advancement of electronic technologies.

Abstract Memristive physical unclonable function (PUF) is a recent entry to the list of security primitives, employing the intrinsic randomness of memristors. Although this represents a huge opportunity for memristors, all present memristive PUFs suffer from the problem of being device intensive because their entropies come exclusively from the spatial dimension. Here, a temporal PUF (TPUF) is reported, using the randomness of temporal dynamics of memristors as an entropy source. By exploiting temporal complexity, significant reduction of hardware overhead is achieved in the TPUF, from otherwise at least hundreds‐of‐memristors‐scale crossbar arrays to only a pair of memristors. This efficient and cheap TPUF can generate more than 10 37 64‐bit challenge–response pairs (CRPs), whose number is infinitely up‐scalable (in principle) without hardware resource restrictions. Experiments have demonstrated that the TPUF has nearly ideal uniformity, diffuseness, uniqueness, low bit error rate, and NIST‐standard‐quality randomness. In addition, its hard‐to‐learn CRP relationship, forbiddingly large number of CRPs, and the potential slow‐down of the read‐out process make it highly resistant to machine learning attacks. This work represents a new opportunity for memristors for encryption.

Abstract GaN‐based high electron mobility transistors (HEMTs) is demonstrated using an extremely thin (≈ 5 nm) h‐BN passivation layer and air spacer, for the first time. The h‐BN passivation layer is grown by metal–organic chemical vapor deposition on top of the AlGaN barrier, followed by GaN‐based HEMTs fabrication. To prohibit the loss and/or damage of the thin h‐BN passivation layer, the SiN is deposited as a protection layer during the device fabrication. When the device fabrication is finalized, the SiN protection layer is removed by buffered oxide etchant, introducing the air spacer under the head of the T‐gate electrode. The electrical properties of the GaN‐based HEMTs applying h‐BN passivation layer and air spacer are measured and compared to the h‐BN/SiN passivated and conventional SiN passivated GaN‐based HEMTs. The difference of the DC characteristics corresponding to the passivation layer in GaN‐based HEMTs is negligible. However, compared to the conventional SiN passivated GaN‐based HEMTs, the RF performance, such as current gain cut‐off frequency and maximum oscillation frequency is improved by 50.3% and 68.5%, respectively, since the parasitic capacitances is reduced by the air spacer formation in GaN‐based HEMTs using a thin h‐BN passivation layer.

Abstract The growth of topological insulator (TI) thin films of Bi 0.85 Sb 0.15 on Si/SiO 2 (100) substrates via a high target utilization sputtering (HiTUS) system is reported. From transport measurements, crystallography, and measurements of surface roughness, it is determined that these HiTUS‐deposited, annealed thin films have properties comparable to films grown via molecular beam epitaxy (MBE). In this study, 12 nm thick Bi 0.85 Sb 0.15 thin films are deposited and the sputtering energy and annealing conditions are varied across three generalized energy regimes: low energy, high energy, and high energy annealed. High‐energy films annealed at T = 175 ° C for 1 h crystallize into the trigonal R3M space group with a (003) surface orientation and exhibit robust weak antilocalization (WAL) at T = 3 K with a magnitude greater than reported in literature. The Dirac fermion model is used to fit to the WAL cusp and derive a Fermi velocity of 57.1 ± 0.2 km s −1 , in good agreement with what has been reported from angle resolved photoemission spectroscopy (ARPES) measurements of Bi 0.9 Sb 0.1 single crystals. Additionally, evidence of surface state transport in Bi 0.85 Sb 0.15 thin films grown without any annealing steps or heat added during growth is reported.

Abstract Programmable photonic circuits (PPCs) are recognized as building blocks for photonic neuromorphic devices and reconfigurable photonic neural networks (PNNs). While traditional PPCs are primarily made of inorganic materials, polymeric materials offer advantages such as mechanical flexibility and a rapid fabrication process at low cost. Here, we demonstrate a fully polymeric PPC constructed only from polydimethylsiloxane (PDMS) doped with the organic dye Rhodamine123. We initially fabricated a Y‐shaped all‐optical logic gate from PDMS and demonstrated its functionality as both an OR and NAND gate. Following this, we fabricated three distinct shapes of PDMS photonic structures and evaluated their performance by injecting amplitude‐modulated optical signals of varying wavelengths and measuring their resulting output signals. By doping one of the PDMS structures (in the shape of a hexagonal mesh) with Rhodamine123 at specific locations and heating the entire structure, we managed to control the intensities of the output optical signals, indicating that temperature serves as a programmable parameter that may regulate the ‘weights’ in a polymer‐organic PNN device. This dual control via doping concentration and temperature introduces a novel method for PPCs made of organic materials. Our findings suggest a promising route toward flexible, low‐cost, and biocompatible photonic neuromorphic hardware leveraging polymer‐organic platforms.

Abstract Efficient computing systems require low‐power and high‐density memory technologies capable of supporting advanced applications such as neuromorphic computing and artificial intelligence. Hafnium oxide (HfO 2 ) based resistive random‐access memory (RRAM) is a promising candidate to this end because of its Complementary Metal‐Oxide‐Semiconductor (CMOS) compatibility and reliable switching behavior. In this work, the effects of lanthanum (La) doping in hafnium oxide are assessed in connection with the memristor performance for neuromorphic applications. It shows that substitution of La stabilizes the cubic phase of (Hf,La)O 2 lowering the oxygen vacancies formation energy and, thereby, favoring their migration properties. La‐doped HfO 2 ‐based memristors show reduced forming and operating voltages, improved switching uniformity, and increased endurance. These memristors exhibit electric field‐driven resistive switching with low voltage variability and most important linear conductance modulation under ultra‐fast pulsed stimulation. These improvements indicate that La‐doped HfO 2 memristors offer significant advantages for energy efficient and reliable analog computing as compared to undoped devices. These findings suggest that La‐doped HfO 2 RRAM has the potential to be a key technology for future analog neuromorphic applications in next‐generation computing architectures.