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Phase transformations and crystallographic defects are two essential tools to drive innovations in materials. Bulk materials design via tuning chemical compositions has been systematized using phase diagrams. We show here that the same…

Accurate early prediction of software defects is essential to maintain software quality and reduce maintenance costs. However, the field of software defect prediction (SDP) faces challenges such as class imbalances, high-dimensional feature…

Software Engineering · Computer Science 2024-10-15 Jie Zhang , Dongcheng Li , W. Eric Wong , Shengrong Wang

Pulsed-laser deposition (PLD) is one of the most promising techniques for the formation of complex-oxide heterostructures, superlattices, and well-controlled interfaces. The first part of this paper presents a review of several useful…

Other Condensed Matter · Physics 2011-07-19 H. M. Christen , G. Eres

Properties of engineering materials are generally influenced by defects such as point defects (vacancies, interstitials, substitutional defects), line defects (dislocations), planar defects (grain boundaries, free surfaces/nanostructures,…

Materials Science · Physics 2016-05-27 Kamal Choudhary

This paper presents a new defect model for the mixed mobile ion effect. The essential physical concept involved is that simultaneous migration of two unlike mobile ions in mixed ionic glass is accompanied by expansion or contraction of the…

Materials Science · Physics 2009-11-11 Vladimir Belostotsky

Reliable anomaly detection in photovoltaic (PV) modules is critical for maintaining solar energy efficiency. However, developing robust computer vision models for PV inspection is constrained by the scarcity of large-scale, diverse, and…

Image and Video Processing · Electrical Eng. & Systems 2025-11-14 Shiva Hanifi , Sasan Jafarnejad , Marc Köntges , Andrej Wentnagel , Andreas Kokkas , Raphael Frank

Point defects affect material properties by altering electronic states and modifying local bonding environments. However, high-throughput first-principles simulations of point defects are costly due to large simulation cells and complex…

Within the framework of many-body perturbation theory (MBPT) integrated with density functional theory (DFT), a novel defect-subspace projection GW method, the so-called p-GW, is proposed. By avoiding the periodic defect interference…

Materials Science · Physics 2022-11-23 Guido Gandus , Youseung Lee , Leonard Deuschle , Mathieu Luisier , Daniele Passerone

Defects in semiconductor crystals can have significant detrimental effects on their performance as radiation detectors. Defects cause charge trapping and recombination, leading to lower signal amplitudes and poor energy resolution. We have…

Instrumentation and Detectors · Physics 2024-09-30 M. Väänänen , M. Kalliokoski , R. Turpeinen , M. Bezak , P. Luukka , A. Karjalainen , A. Karadzhinova-Ferrer

We formulate a model for a point defect embedded in a homogeneous multilattice crystal with an empirical interatomic potential interaction. Under a natural, phonon stability assumption we quantify the decay of the long-range elastic fields…

Analysis of PDEs · Mathematics 2016-10-03 Derek Olson , Christoph Ortner

Defects dictate the properties of many functional materials. To understand the behaviour of defects and their impact on physical properties, it is necessary to identify the most stable defect geometries. However, global structure searching…

Materials Science · Physics 2024-06-12 Irea Mosquera-Lois , Seán R. Kavanagh , Alex M. Ganose , Aron Walsh

Despite the exponential growth in computing resources and the availability of a myriad of different theoretical water models, an accurate, yet computationally efficient molecular level description of mesoscopic grain growth remains a grand…

This paper shows how data-driven machine learning approaches can improve growth control, reproducibility, and physical insight in the pulsed laser deposition (PLD) growth of correlated oxides. Despite well-known relationships between growth…

Transitions between distinct dynamical regimes are ubiquitous in nonequilibrium systems. As a prototypical example, deposition growth is often accompanied by irreversible morphological instabilities. Forecasting such transitions from…

Chemical Physics · Physics 2026-02-16 Hyunjun Jang , Chung Bin Park , Jeonghoon Kim , Jeongmin Kim

The Point Defect Model (PDM) describes the corrosion resistance properties of oxide films based on interfacial reactions and defect transport, which are affected by the electric field inside the oxide film. The PDM assumes a constant…

Chemical Physics · Physics 2023-08-11 Ingmar Bösing , Jorg Thöming , Fabio La Mantia

Distributed model predictive control (DMPC) is a flexible and scalable feedback control method applicable to a wide range of systems. While the stability analysis of DMPC is quite well understood, there exist only limited implementation…

Systems and Control · Electrical Eng. & Systems 2025-11-05 Gösta Stomberg , Henrik Ebel , Timm Faulwasser , Peter Eberhard

Defects in 2D materials are becoming prominent candidates for quantum emitters and scalable optoelectronic applications. However, several physical properties that characterize their behavior, such as charged defect ionization energies, are…

Materials Science · Physics 2018-12-26 Tyler J. Smart , Feng Wu , Marco Govoni , Yuan Ping

The ability to generate 3D multiphase microstructures on-demand with targeted attributes can greatly accelerate the design of advanced materials. Here, we present a conditional latent diffusion model (LDM) framework that rapidly synthesizes…

Correcting the optical aberrations and the manufacturing deviations of cameras is a challenging task. Due to the limitation on volume and the demand for mass production, existing mobile terminals cannot rectify optical degradation. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-05-11 Shiqi Chen , Ting Lin , Huajun Feng , Zhihai Xu , Qi Li , Yueting Chen

Machine-learning interatomic potentials (MLIPs) enable large-scale atomistic simulations at moderate computational cost while retaining ab initio accuracy. MLIPs trained on coupled-cluster data, particularly CCSD(T), have emerged as a…

Materials Science · Physics 2026-03-11 Yuji Ikeda , Axel Forslund , Pranav Kumar , Yongliang Ou , Jong Hyun Jung , Andreas Köhn , Blazej Grabowski