Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
A physics-guided temporal convolutional learning with XGBoost integration for degradation-aware and robust electric vehicle range prediction. [PDF]
Esakkiappan K +6 more
europepmc +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Adaptive deep Q-networks for accurate electric vehicle range estimation. [PDF]
Khekare U, Vedaraj I S R.
europepmc +1 more source
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj +4 more
wiley +1 more source
Review of the Gate Structure for Normally Off p-GaN High-Electron-Mobility Transistors Towards High Performances. [PDF]
Pu T, Li X, Li L, Ao JP.
europepmc +1 more source
Highly Stabilized Ni‐Rich Cathodes Enabled by Artificially Reversing Naturally‐Formed Interface
The application of Ni‐rich cathode materials is obstructed by interfacial and structural instability. This work proposes a facile and cost‐effective Al‐based vapor‐phase surface reaction strategy on Ni‐rich cathode to maintain its structural integrity from near‐surface to bulk.
Jinjin Ma +11 more
wiley +1 more source
Innovative fuzzy reinforcement learning based energy management for smart homes through optimization of renewable energy resources with starfish optimization algorithm. [PDF]
Hamedani MMK +3 more
europepmc +1 more source
Hybrid fuzzy-MPC based multi-objective control strategy for fast charging of electric vehicles with advanced battery thermal management and renewable grid support. [PDF]
Yadav IC, Bajpai RS, Gupta S, Shukla A.
europepmc +1 more source
Integration of AI and ML in regenerative braking for electric vehicles: a review. [PDF]
Prakash Z.
europepmc +1 more source

