Hasan Kaan Kucukerdem^*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074188 - 30 January 2026

Abstract Root-zone temperature (RZT) strongly affects plant growth, nutrient uptake and tolerance to environmental stress, making its regulation a key challenge in greenhouse cultivation in cold climates. This study aimed to assess the potential of passive techniques, namely black polyethylene mulch and row covers, for modifying RZT dynamics in lettuce (Lactuca sativa L.) production and to evaluate the predictive performance of the eXtreme Gradient Boosting (XGBoost) algorithm. Experiments were conducted in Iğdır, Türkiye, over a 61-day period, with soil temperature continuously monitored at depths of 1–30 cm under mulched and non-mulched conditions, alongside measurements of greenhouse air… More >

Zuokun Yang¹, Jun Li^1,2,*, Xin Lai^1,2, Lisheng Liu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075980 - 29 January 2026

Abstract Peridynamics (PD) demonstrates unique advantages in addressing fracture problems, however, its nonlocality and meshfree discretization result in high computational and storage costs. Moreover, in its engineering applications, the computational scale of classical GPU parallel schemes is often limited by the finite graphics memory of GPU devices. In the present study, we develop an efficient particle information management strategy based on the cell-linked list method and on this basis propose a subdomain-based GPU parallel scheme, which exhibits outstanding acceleration performance in specific compute kernels while significantly reducing graphics memory usage. Compared to the classical parallel scheme,… More >

Rayeesa Mehmood^*, Sergei Koltcov, Anton Surkov, Vera Ignatenko

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072735 - 12 January 2026

Abstract Activation pruning reduces neural network complexity by eliminating low-importance neuron activations, yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search. We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric. Phase-transition–like phenomena in the free-energy profile—such as extrema, inflection points, and curvature changes—yield reliable estimates of the critical pruning threshold, providing a theoretically grounded means of predicting sharp accuracy degradation. To further enhance efficiency, we propose a renormalized free energy technique that More >

Alexander V. Savin^1,2, Elena A. Korznikova^3,4, Sergey V. Dmitriev^5,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.072786 - 09 December 2025

Abstract Due to their chiral structure, carbon nanosprings possess unique properties that are promising for nanotechnology applications. The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules (graphene helicoids and spiral nanoribbons) are analyzed using molecular dynamics simulations. The interatomic interactions are described by a force field including valence bonds, bond angles, torsional and dihedral angles, as well as van der Waals interactions. While the tension/compression of such nanosprings has been analyzed in the literature, this study investigates other modes of deformation, including bending and twisting. Depending… More >

Chen-Xi Hu¹, Wu-Gui Jiang^1,*, Jin Wang¹, Tian-Yu He²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.068655 - 10 November 2025

Abstract THE mechanical response and deformation mechanisms of pure nickel under nanoindentation were systematically investigated using molecular dynamics (MD) simulations, with a particular focus on the novel interplay between crystallographic orientation, grain boundary (GB) proximity, and pore characteristics (size/location). This study compares single-crystal nickel models along [100], [110], and [111] orientations with equiaxed polycrystalline models containing 0, 1, and 2.5 nm pores in surface and subsurface configurations. Our results reveal that crystallographic anisotropy manifests as a 24.4% higher elastic modulus and 22.2% greater hardness in [111]-oriented single crystals compared to [100]. Pore-GB synergistic effects are found More >

Shuai Xu¹, Congfei Zang¹, Yiming Zhang², Chun Li^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.011525

Abstract The development of novel spintronic devices based on spin manipulation in magnetic nanostructures is crucial for achieving higher speed and miniaturization in future computing technologies. As a unique type of graphene quantum dot, triangulene nanoflakes (TNFs) exhibit nontrivial magnetic properties and excellent extensibility, making them highly promising for the design and application of spin logic units. In this study, we employ first-principles calculations to investigate experimentally synthesizable TNFs, in which transition metal (TM) atoms —namely Fe, Co, Ni, and Cu— are individually introduced at π-conjugated doping sites. The effects of different dopants and doping positions… More >

Yingxin Zhang^1,2, Shuai Mo^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.011038

Abstract To accurately describe the dynamic behavior of a gear-rotor-bearing system, it is essential to consider the interplay between thermal effects and dynamics. Therefore, this study develops a real-time coupling model that integrates thermal and dynamic aspects of the gear-rotor-bearing system, which captures the combined effects of various nonlinear factors, including dynamic clearances caused by thermal deformation, thermoelastic coupling stiffness, non-uniform load distribution in bearings, and multi-meshing state of gear. Building on this model, the study introduces a stepwise coupled thermodynamic and dynamic joint solution method, which is used to evaluate the effects of thermal influences More >

Rui Yang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.010698

Abstract This study employs molecular dynamics (MD) simulations to comparatively investigate the mechanical enhancement mechanisms of glass fiber-reinforced concrete (GFRC) and basalt fiber-reinforced concrete (BFRC). Amorphous models of glass fiber (GF) and basalt fiber (BF), along with calcium silicate hydrate (C-S-H), were constructed using the ClayFF force field in LAMMPS. The interfacial transition zone (ITZ), atomic bonding characteristics, stress distribution, and tensile failure processes were systematically analyzed. Key findings reveal that BF exhibits a denser atomic network structure with higher coordination numbers, driven by the bridging role of Fe and Mg atoms. BFRC demonstrates significantly stronger More >

Yan Li^1,2,*, Yibin Wu^1,2, Bo Zhang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 2905-2925, 2025, DOI:10.32604/fdmp.2025.072979 - 31 December 2025

Abstract Traditional Computational Fluid Dynamics (CFD) simulations are computationally expensive when applied to complex fluid–structure interaction problems and often struggle to capture the essential flow features governing vortex-induced vibrations (VIV) of floating structures. To overcome these limitations, this study develops a hybrid framework that integrates high-fidelity CFD modeling with deep learning techniques to enhance the accuracy and efficiency of VIV response prediction. First, an unstructured finite-volume fluid–structure coupling model is established to generate high-resolution flow field data and extract multi-component time-series feature tensors. These tensors serve as inputs to a Squeeze-and-Excitation Convolutional Neural Network (SE-CNN), which… More >

Zhengqing Zhang^1,2,3,*, Xiaojun Yuan², Hui Wu²

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 2927-2943, 2025, DOI:10.32604/fdmp.2025.071115 - 31 December 2025

Abstract Frost accumulation on the evaporator fins of air source heat pumps (ASHPs) severely degrades heat transfer performance and overall system efficiency. To address this, the present study employs computational fluid dynamics (CFD) to investigate how fin spacing influences frosting behavior, emphasizing the coupled evolution of frost thickness, density, airflow, and temperature distribution within fin channels. Results reveal that fin spacing is a key parameter governing both the extent and rate of frost growth. Wider fin spacing enhances frost accumulation, with a final frost mass of 6.41 g at 12 mm, about 71.8% higher than at More >