QuesTek Innovations LLC’s Post

One week from today: Join QuesTek's Gary Whelan for a LIFT webinar on June 5 at 1 pm ET. 👉 Register now: https://lnkd.in/dPdNfAag Applications of Microstructure-Sensitive Fatigue Modeling Learn how Integrated Computational Materials Engineering (ICME) can be used to predict fatigue in real-world applications. QuesTek will describe the importance of microstructure analysis and focus on how it can improve alloy development, qualification, and sustainment activities. #fatigue #icme #icmd

Join QuesTek's Gary Whelan for a LIFT webinar on June 5 at 1 pm ET. Register now: https://lnkd.in/dPdNfAag Applications of Microstructure-Sensitive Fatigue Modeling Learn how Integrated Computational Materials Engineering (ICME) can be used to predict fatigue in real-world applications. QuesTek will describe the importance of microstructure analysis and focus on how it can improve alloy development, qualification, and sustainment activities. #fatigue #icme #icmd

Learn how Integrated Computational Materials Engineering (ICME) can be used to predict fatigue in real-world applications!!

Many of my recent conversations of materials challenges in industry have to do with fatigue: low fatigue life; high variability in fatigue performance, predicting fatigue life and improving fatigue life. With recent programs started / pending on space applications, agricultural components, medical devices and sporting goods. Take a look at my QuesTek Innovations LLC colleague Gary Whelan one of our experts on fatigue talk about these problems and our approach on June 5 webinar link below

Latest study at our Institute in close collaboration with IMWF Universität Stuttgart delves into the effects of 1.4 wt.% Cr and 1.4 wt.% Mo on pearlitic microstructures. Combining experimental techniques and phase field simulations, we leveraged tools like MATcalc, JMatPro®, and MICRESS by Access e.V. for accurate predictions of local microstructural evolution. Key findings reveal that Cr promotes a uniform microstructure with longer, thinner cementite lamellae, while Mo results in shorter, thicker lamellae, affecting morphology without enhancing homogeneity. Our semi-automatic microstructural analysis via Fiji ImageJ provides precise quantification to accurately understand how does chemistry, temperature and time affect local cementite morphology in studies alloys. For full access, visit the journal Materials MDPI, Volume 17, Issue 14, under the special issue "Numerical Simulation Methods for Analyzing Fatigue and Fracture Behavior in Metallic Materials." or https://lnkd.in/eAECMbHE If you want to know more about this work or are interested in collaborating in the future, please get in touch. #MaterialsScience #PearliticSteels #PhaseFieldSimulations #MicrostructureAnalysis #SteelAlloys #ResearchInnovation

K1-MET Press Release: What happens to materials at 1,700 degrees heat? JUST magazine interviewed Jeronimo Guarco (Postdoc in Area 3 Simulation & Data Analyses) of K1-MET GmbH. The article is about research into refractory materials that have to withstand extreme conditions in the steel and glass industry. These include temperatures of up to 1,700 degrees Celsius and corrosive environments, which require continuous research to minimise wear. Jerónimo Guarco has developed simulation models based on computational fluid dynamics (CFD) and carried out experimental studies as part of his dissertation at the COMET competence center K1-MET. The aim is to better understand and quantify physical-chemical and mechanical wear. Insights gained from this research should help make these processes more efficient in the future. Read the full German article: https://lnkd.in/dbTN-EtD source: Sirius Alexander Pansi (JUST Verlags GmbH) #K1MET #article #forschung #research #steelindustry #sustainability

BIG UPDATE! We acquired a Femtosecond laser with a 5 µm resolution through a Hercules project in collaboration with Plasmant, LADCA, A-Sense Lab, ORSY, EMAT, DuEL, BIMEF, InViLab.UAntwerp and the Product Development department. Ablation operations of metals, plastics, glass types, etc... enable the development of next generation components in various scientific fields. GDE and membrane modification, flow field micromachining, and catalyst layer alteration are just the tip of the iceberg we want to explore. Additionally, we provide this service to external parties to resolve your complex engineering problems. LASEA #Femtosecondlaser #Engineering #Materialscience #FWO #ServiceToIndustry #Micro #NextGenElectrochemistry

I feel extremely grateful and honored for my first #article, published with professors Davide Paolino, Andrea Tridello and Alberto Ciampaglia on the journal “Fatigue & Fracture of Engineering Materials & Structures” (#FFEMS, Wiley) entitled “Machine learning methods to predict the fatigue life of selectively laser melted Ti6Al4V components”. It explores the great capabilities of #neuralnetworks in linking the Selective Laser Melting (#SLM) #processparameters and #posttreatments, to the #fatigue performances of the most popular #additivemanufacturing #Titanium alloy. This innovative approach is one of the first attempts to predict the #fatiguelife, of the #Ti6Al4V alloy, before the specimens production, granting costs and testing time reduction. Once again, #machinelearning proves its effectiveness, even in traditional fields as mechanical fatigue failures, effectively paving the road for new fatigue life assessment methodologies. You can find the article at the following link: https://lnkd.in/giXTqC4A

Webinar: Polyvalent Machine-Learned Potential for Cobalt: from Bulk to Nanoparticles register: bit.ly/3PZbF27 In this webinar we describe the development of a highly accurate machine-learned potential (MLP) for Co, enabling simulations of large models of bulk material, surfaces, and nanoclusters over extended time scales across a wide range of temperatures and pressures. While non-magnetic itself, the #MLP is trained on several thousand spin-polarized ab initio computations performed using #MedeA #VASP. The resulting MLP closely reproduces the phonon dispersions of hexagonal close-packed (hcp) and face-centered cubic (fcc) Co, Co surface energies, and the relative stabilities of Co nanoparticles of various shapes. The thermal expansion coefficient and the melting temperature of Co computed with this MLP are close to experimental values. Furthermore, this MLP captures nuanced material properties such as vacancy formation energies on nanoparticle vertices. This accuracy and versatility make the potential suitable for a wide array of applications, including modeling the geometry of Co catalytic surfaces. #compchem #materialsdesign #materialsproperties #software #RD #MedeAsoftware #molecularmodeling #atomisticsimulation #molecularsimulation #machinelearnedpotentials #nanoparticles #nano #Cobalt #Polyvalent #properties #DFT #Forcefield #MLPG #Phonon #qSNAP #LAMMPS #fitSNAP #surfacescience #catalysis #materialsdesign #catalysts #catalystsindustry #energyindustry #chemicalindustry

✅ The latest issue of Chem. Prod. Process Model. (CPPM) was published by De Gruyter in February 2024 (Volume 19, Issue 1) (https://lnkd.in/evC_mvG9). CPPM is a quarterly journal published since 2006, covering theoretical and applied research on product and process modeling, simulation, and optimization. CPPM website: lnkd.in/eTdUDy4H | Submission page: lnkd.in/e4eYQ855✍ Editors-in-Chief: Rahmat Sotudeh-Gharebagh, Navid Mostoufi, Jamal Chaouki. #product #process #modeling #design #simulation #optimization #chemicalengineering