Results 101 to 110 of about 383,254 (264)
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
This study presents a reversible temperature sensor with high switching ratio, ∼103. The device is fabricated using PET‐ITO and carbon nanotube dispersions in alkane. Considering its application in cold chain logistics, a proof‐of‐concept with LED is showcased. Thus, a temperature drop below the threshold temperature (crystallization temperature of the
Sunil Kumar Behera +8 more
wiley +1 more source
ESTUDIO DEL DESARROLLO DEL NITRÓGENO AMINO LIBRE DURANTE EL MALTEADO DEL SORGO
En el proceso de fabricación de cervezas se utiliza la malta de cebada como materia prima principal. Uno de los cereales idóneos para sustituir la cebada es el sorgo ya que posee alto potencial nutritivo.
Yanet Boffill Rodríguez +2 more
doaj
This study explored how effective nickel aluminide coatings are obtained in providing oxidation resistance applied to the Inconel 738 alloy, modeling with diffusion models. In the present study, kinetics and thermal behavior of the Inconel 738 alloy were studied by the low‐temperature thermoreactive aluminizing process, which was carried out at 625°C ...
Gozde Celebi Efe +4 more
wiley +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky +5 more
wiley +1 more source
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Karl Popper and the Mechanisms of Hydrogen Embrittlement
Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley +1 more source
Identified through the use of statistical design of experiments and metallographic investigation, this study exposes the stochastic origins of intergranular cracks in blown powder laser beam directed energy deposition additive manufacturing of pure molybdenum. It further demonstrates a successful crack mitigation approach with direct correlation to the
Nathaniel J. Lies +2 more
wiley +1 more source

