Results 41 to 50 of about 72,345 (262)
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 +4 more
wiley +1 more source
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
Advanced Materials, EarlyView.A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu +5 more
wiley +1 more source
Assessment of CNN+XGBoost Performance for Image Classification [PDF]
, 2021 In the last few years, convolutional neural network (CNN) models have provided state-of-the-art results in visual recognition tasks. Similarly to CNNs, tree-based methods, in particular, gradient tree boosting (XGBoost) provided superior results in many ...
Turchenko, Andrii
core
Advanced Science, EarlyView.A biotin‐modified artificial insertion peptide functionalized three‐dimensional high‐curvature‐TiO2 nano‐interface was engineered in a microfluidic chip to improve the isolation efficiency of small extracellular vesicles (sEVs). This chip balanced affinity, releasability, and extendibility, enabling high‐throughput recovery of sEVs for downstream ...
Le Wang +7 more
wiley +1 more source
Fetal health classification with predictive algorithm by using Ensemble Model [PDF]
ITM Web of ConferencesFetal health assessment is essential for ensuring the well-being of both the mother and fetus during pregnancy. Cardiotocography (CTG) is a widely used technique that monitors fetal heart rate (FHR) patterns and uterine contractions, providing critical ...
Devi V. Sowmya +3 more
doaj +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
Advanced Science, EarlyView.This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
XGBoost performance metrics for each wave.
, 2022 XGBoost performance metrics for each wave.
Matthieu Ortala (12119384) +5 more
core +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source