Development of a two‐dimensional bipolar electrochemistry technique for high throughput corrosion screening

Materials Genome Engineering Advances, Journal Year: 2024, Volume and Issue: 2(3)

Published: July 19, 2024

Abstract Bipolar electrochemistry allows testing and analysing the crevice corrosion, pitting passivation, general cathodic deposition reactions on one sample after a single experiment. A novel two‐dimensional bipolar setup is designed using two orthogonal feeder electrode arrangements, allowing corrosion screening tests across far wider potential range with smooth gradient to be assessed. This was applied here simultaneously measure for simultaneous measurement of nucleation propagation under broad type 420 stainless steel, which has very short localised induction time. It reduces error from competition, all pits have no lacy cover. Results show can gain current density easier support its at different regions more easily than corrosion.

Language: Английский

---

Introduction to Predicting Properties of Organic Materials

Challenges and advances in computational chemistry and physics, Journal Year: 2025, Volume and Issue: unknown, P. 27 - 63

Published: Jan. 1, 2025

Language: Английский

---

Accelerating materials discovery for electrocatalytic water oxidation via center-environment deep learning in spinel oxides

Journal of Materials Chemistry A, Journal Year: 2024, Volume and Issue: 12(30), P. 19362 - 19377

Published: Jan. 1, 2024

Using DFT and machine learning, we evaluated 5329 spinel oxides identified 14 promising OER electrocatalysts. Experimentally, MoAg 2 O 4 showed superior performance, achieving 10 mA cm −2 at 284 mV overpotential, surpassing commercial RuO .

Language: Английский

---

Synergistic improvement of pitting and wear resistance of laser powder bed fusion 420 stainless steel reinforced by size-controlled spherical cast tungsten carbides

Corrosion Science, Journal Year: 2024, Volume and Issue: 237, P. 112342 - 112342

Published: Aug. 1, 2024

Language: Английский

---

Data mining accelerated the design strategy of high‐entropy alloys with the largest hardness based on genetic algorithm optimization

Materials Genome Engineering Advances, Journal Year: 2024, Volume and Issue: 2(2)

Published: June 1, 2024

Abstract This article proposed a design strategy that integrated machine learning models based on random forest and genetic algorithm (GA) for the rapid screening of hardness in AlCoCrCuFeMoNiTi high‐entropy alloys system. Through feature engineering modeling, valence electron concentration, atomic size difference ( δr ), Pauling electronegativity (Δ χ geometric parameters Λ Cr content were identified as five key features database. The GA was employed to search with superior guided synthesis. After three iterations, HEA Al 18 Co 21 23 Fe Mo 15 exhibiting highest predicted (868.8 HV) identified. alloy predominantly composed BCC, ordered B2, σ phases, an experimental 899.8 ± 9.9 HV, which approximately 5.38% greater than maximum observed original dataset. can also solve other regression problems pave way optimizing material performance various applications.

Language: Английский

---

The Effect of Different Nanoparticles Surface Plasmon Polariton (SPP) Grating on Ge, Si, InP, and GaAs Photodetectors Performance

Plasmonics, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 14, 2025

Abstract The photonics community is getting more involved in plasmonic detectors that detect light. Plasmonics permits lighting to be directed into microscopic areas metal frameworks; this feature might imitate further advancements the effectiveness of Plasmonic nanostructures may alter light at a subwavelength scale and have been seen as an effective way improve photoresponsiveness semiconductor components. A groove surface plasmon polaritons (SPPs) catapult which encircles novel germanium (Ge), silicon (Si), indium phosphide (InP), gallium arsenide (GaAs) photodetectors can applied detector’s photocurrent, responsivity, internal quantum efficiency detector. In study, we examine effect gold (Au) silver (Ag) SPP on Ge, Si, InP, GaAs photodetectors. Moreover, demonstrated recombination with photodetector presents higher responsivity (R) current density (J) than all examined maximum when using nanoparticles Ge achieves 250 W −1 , 150 40 25 GaAs. results also achieve high mA cm −2 SPP, 15 Si 3.6 InP 1.6 SPP. best performance photodetectors, better We utilize 3-D finite element method (FEM) COMSOL Multiphysics 6.1 simulation tool experiments results.

Language: Английский

---

Advancing perovskite photovoltaic technology through machine learning‐driven automation

InfoMat, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Abstract Since its emergence in 2009, perovskite photovoltaic technology has achieved remarkable progress, with efficiencies soaring from 3.8% to over 26%. Despite these advancements, challenges such as long‐term material and device stability remain. Addressing requires reproducible, user‐independent laboratory processes intelligent experimental preselection. Traditional trial‐and‐error methods manual analysis are inefficient urgently need advanced strategies. Automated acceleration platforms have transformed this field by improving efficiency, minimizing errors, ensuring consistency. This review summarizes recent developments machine learning‐driven automation for photovoltaics, a focus on application new transport discovery, composition screening, preparation optimization. Furthermore, the introduces concept of self‐driven Autonomous Material Device Acceleration Platforms (AMADAP) discusses potential it may face. approach streamlines entire process, discovery performance improvement, ultimately accelerating development emerging technologies. image

Language: Английский

---

Advances in high‐throughput experiments of polymer crystallization for developing polymer processing

Materials Genome Engineering Advances, Journal Year: 2025, Volume and Issue: unknown

Published: March 13, 2025

Abstract Polymer crystallization, an everlasting subject in polymeric materials, holds great significance not only as a fundamental theoretical issue but also pivotal basis for directing polymer processing. Given its multistep, rapid, and thermodynamic nature, tracing comprehending crystallization pose formidable challenge, particularly when it encounters practical processing scenarios that involve complex coupled fields (such temperature, flow, pressure). The advent of high‐time spatially resolved experiments paves the way situ investigations crystallization. In this review, we delve into strides studying under effects external via state‐of‐the‐art high‐throughput experiments. We highlight intricate setup these experimental devices, spanning from laboratory pilot levels to industrial level. individual combined on are discussed. By breaking away conventional “black box” research approach, special interest is paid crystalline behavior polymers during realistic Finally, underscore advancements outline promising development.

Language: Английский

---

Phase equilibrium of the Fe2O3-TiO2 system

Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113945 - 113945

Published: April 1, 2025

Language: Английский

---

Accelerated discovery of high-performance small-molecule hole transport materials via molecular splicing, high-throughput screening, and machine learning

Journal of Materials Informatics, Journal Year: 2025, Volume and Issue: 5(3)

Published: April 15, 2025

As the most representative and widely utilized hole transport material (HTM), spiro-OMeTAD encounters challenges including limited mobility, high production costs, demanding synthesis conditions. These issues have a notable impact on overall performance of perovskite solar cells (PSCs) based hinder its large-scale commercial application. Consequently, there exists strong demand for high-throughput computational design novel small-molecule HTMs (SM-HTMs) that are cost-effective, easy to synthesize, offer excellent performance. In this study, systematic iterative development process SM-HTMs is proposed, aiming accelerate discovery application high-performance SM-HTMs. A custom-developed molecular splicing algorithm (MSA) generated sample space 200,000 intermediate molecules, culminating in creation comprehensive database over 7,000 potential SM-HTM candidates. total, six promising HTM candidates were identified through MSA, density functional theory calculations screening. Furthermore, three machine learning algorithms, namely random forest, gradient boosting decision tree, extreme (XGBoost), employed construct predictive models key properties, recombination energy, solvation free maximum absorption wavelength, hydrophobicity. Among these, XGBoost-based model demonstrated best The MSA methodology combining prediction models, as introduced offers powerful universal toolkit optimization next-generation SM-HTMs, thereby paving way future advancements PSCs.

Language: Английский

---