In today’s semiconductor verification field, SystemVerilog Assertions (SVAs) are one of the most important methodologies for functional verification. A representative verification technique is Universal Verification Methodology (UVM)-based verification, which utilizes a SystemVerilog class library. On the other hand, Assertion-Based Verification (ABV) using SVA allows hardware designs to be verified without requiring knowledge of SystemVerilog’s Object-Oriented Programming (OOP) concepts or UVM. Its syntax is intuitive and concise, enabling rapid detection of RTL (Register Transfer Level) bugs during the design and verification phases. This methodology significantly enhances productivity by drastically reducing the time required for semiconductor development. This paper proposes an ABV verification environment using SVA that is reusable in other verification environments for verifying the main functions of the Inter-Integrated Circuit (I2C), one of the serial synchronous communication protocols. Finally, through the development of the RTL design and simulation of the core functionalities of I2C, the key characteristics of I2C were verified using ABV with SVA.

Artificial neural networks (ANNs) are attracting attention for their high performance in various fields, because increasing the network size improves its functioning. Since large-scale neural networks are difficult to implement on custom hardware, a two-dimensional (2D) structure is applied to an ANN in the form of a crossbar. We demonstrate a synapse crossbar device from recent research by applying a memristive system to neuromorphic chips. The system is designed using two-dimensional structures, graphene quantum dots (GQDs) and graphene oxide (GO). Raman spectrum analysis results indicate a D-band of 1421 cm−1 that occurs in the disorder; band is expressed as an atomic characteristic of carbon in the sp2 hybridized structure. There is also a G-band of 1518 cm−1 that corresponds to the graphite structure. The G bands measured for RGO-GQDs present significant GQD edge-dependent shifts with position. To avoid an abruptly-formed conduction path, effect of barrier layer on graphene/ITO interface was investigated. We confirmed the variation in the nanostructure in the RGO-GQD layers by analyzing them using HR-TEM. After applying a negative bias to the electrode, a crystalline RGO-GQD region formed, which a conductive path. Especially, a synaptic array for a neuromorphic chip with GQDs applied was demonstrated using a crossbar array.

The use a stabilized lithium structure as cathode material for batteries could be a fundamental alternative in the development of next-generation energy storage devices. However, the lithium structure severely limits battery life causes safety concerns due to the growth of lithium (Li) dendrites during rapid charge/discharge cycles. Solid electrolytes, which are used in high-density energy storage devices and avoid the instability of liquid electrolytes, can be a promising alternative for next-generation batteries. Nevertheless, poor lithium ion conductivity and structural defects at room temperature have been pointed out as limitations. In this study, through the application of a low-dimensional graphene quantum dot (GQD) layer structure, stable operation characteristics were demonstrated based on Li+ ion conductivity and excellent electrochemical performance. Moreover, the device based on the modified graphene quantum dots (GQDs) in solid state exhibited retention properties of 95.3% for 100 cycles at 0.5 C and room temperature (RT). Transmission electron microscopy analysis was performed to elucidate the Li+ ion action mechanism in the modified GQD/electrolyte heterostructure. The low-dimensional structure of the GQD-based solid electrolyte has provided an important strategy for stably-scalable solid-state lithium battery applications at room temperature. It was demonstrated that lithiated graphene quantum dots (Li-GQDs) inhibit the growth of Li dendrites by regulating the modified Li+ ion flux during charge/discharge cycling at current densities of 2.2–5.5 mA cm, acting as a modified Li diffusion heterointerface. A full Li GQD-based device was fabricated to demonstrate the practicality of the modified Li structure using the Li–GQD hetero-interface. This study indicates that the low-dimensional carbon structure in Li–GQDs can be an effective approach for stabilization of solid-state Li matrix architecture.

Resource allocation that is both energy-efficient and fair remains a persistent challenge in 5G, beyond-5G, and emerging 6G networks, where users with heterogeneous service requirements compete for limited radio resources. Although rate-splitting multiple access (RSMA) is commonly investigated through physical-layer models, service-level datasets often contain demand indicators without channel matrices, beamforming variables, or stream-level power parameters. We develop and evaluate a QoS-driven allocation framework based on three allocation-inspired models: an RSMA-inspired balanced model, a NOMA-inspired signal-strength-aware model, and an OFDMA proportional-fair reference model. Four metaheuristic optimizers—Genetic algorithm(GA), simulated annealing (SA), particle swarm optimization (PSO), and ant colony optimization (ACO)—are applied to the same QoS demand profile, resource budget, constraints, feasibility-repair procedure, and performance measures, producing 12 model–optimizer combinations. The input comprises 400 user records, including 393 records with positive bandwidth requirements and seven records with zero bandwidth. Each method was evaluated over 30 independent runs. Under this QoS-level abstraction, RSMA-PSO produced the highest mean fitness and energy-efficiency values, whereas RSMA-GA achieved the strongest composite balance across fitness, energy efficiency, fairness, and satisfaction. The mean fitness of RSMA-GA was 9.32% higher than that of NOMA-GA and 18.00% higher than that of OFDMA-PF-GA. These results characterize allocation behavior under a shared QoS profile and should not be interpreted as full physical-layer validation of RSMA, NOMA, or OFDMA transmission.