Results 71 to 80 of about 42,506 (260)

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Triple Junctions as Dislocation‐Like Defects: The Role of Grain Boundary Crystallography Revealed by Experiment and Atomistic Simulation

Advanced Engineering Materials, EarlyView.
Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink, Saba Saood, Peter Schweizer, Jörg Neugebauer, Gerhard Dehm   +4 more
wiley   +1 more source

Identification of recurring patterns in fractionated atrial electrograms using new transform coefficients

BioMedical Engineering OnLine, 2012
Background Identification of recurrent patterns in complex fractionated atrial electrograms (CFAE) has been used to differentiate paroxysmal from persistent atrial fibrillation (AF).
Ciaccio Edward J, Biviano Angelo B, Whang William, Garan Hasan   +3 more
doaj   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

A stochastic space-time rainfall forecasting system for real time flow forecasting II: Application of SHETRAN and ARNO rainfall runoff models to the Brue catchment [PDF]

Hydrology and Earth System Sciences, 2000
Key issues involved in converting MTB ensemble forecasts of rainfall into ensemble forecasts of runoff are addressed. The physically-based distributed modelling system, SHETRAN, is parameterised for the Brue catchment, and used to assess the impact of ...
D. Mellor, J. Sheffield, P. E. O’Connell, P. E. O’Connell, A. V. Metcalfe   +4 more
doaj  

Ensemble Averaging and Mean Squared Error

Journal of Climate, 2016
Abstract In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often outperforms at least half of the ensemble members in mean squared error (measured with respect to observations). In fact, as demonstrated in the
openaire   +3 more sources

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Topological quantization of ensemble averages [PDF]

Journal of Physics A: Mathematical and Theoretical, 2009
16 pages, 2 ...
openaire   +2 more sources

Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys

Advanced Engineering Materials, EarlyView.
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma, Sarath Menon, Fritz Körmann, Thomas Hammerschmidt, Ralf Drautz   +4 more
wiley   +1 more source

Irradiation‐Induced Spin Bath Evolution and as‐Grown Hydrogen Defects in CVD Diamond Revealed by NV‐Based DEER Spectroscopy

Advanced Functional Materials, EarlyView.
Here, we provide the reader with the current state of the art in the fabrication of high‐T2‐coherence diamond, optimized through the use of double electron–electron resonance (DEER) spectroscopy. We reveal the main as well as yet unidentified spin defects, the reduction of which is essential for reducing the spin bath and fabricating materials for ...
Olga Rubinas, Jeroen Prooth, Michael Petrov, Remy Vandebosch, Emilie Bourgeois, David Chvátil, Milos Nesladek   +6 more
wiley   +1 more source