Publication Newsletter

August 2026

Hi subscriber,

We are pleased to bring you the August edition of our Publication Newsletter. Each month, we highlight a selection of recently published research showcasing the many ways Thermo-Calc Software products are being used.

This edition features papers on additive manufacturing, machine learning combined with CALPHAD methods, and materials including steel, aluminum, copper, and high-entropy alloys. We hope these publications provide valuable insights and inspiration for your own research and development.

Additive Manufacturing

Precipitation Simulations of the O-Phase in Ti₂AlNb Alloys Processed by Laser Powder Bed Fusion

Silvana Tumminello, Joachim Gussone, Suzana G. Fries, Marcus Rackel, Andreas Stark, Norbert Schell, Jan Haubrich, and Guillermo Requena

Advanced Engineering Materials

Products Used: Precipitation Module (TC-PRISMA), Titanium and TiAl-based Alloys Databases

Anomalous grain growth as a pathway toward fully single-crystallization in IN738LC Ni-based superalloy fabricated by laser powder bed fusion

Masayuki Okugawa, Kazufumi Nose, Sei Hirooka, Sukeharu Nomoto, Yuheng Liu, Makoto Watanabe, Yuichiro Koizumi, and Takayoshi Nakano

Materials & Design

Products Used: Nickel-based Superalloys Databases, MICRESS with the TQ-Interface

Synergistic strengthening from chemical and dislocation cellular structures in LPBF-fabricated concentrated solid-solution alloys

Rijie Zhao, Weiyi Shen, Zongzheng Xie, Haoliang Wang, Tingting Yang, Chao Ding, 
Chenghao Song, and Zhenzhong Sun

Journal of Materials Research and Technology

Products Used: Nickel-based Superalloys Databases, Additive Manufacturing Module

Machine Learning

Accelerated discovery of Cr-based A2+B2 superalloys across 11 elements with a deep-learning CALPHAD surrogate

Mikko Tahkola, Lassi Linnala, Tom Blackburn, Simon Savukoski, Vincent Gagneur, Joni Kaipainen, Kan Ma, Alexander J. Knowles, Anssi Laukkanen, and Tatu Pinomaa

npj Computational Materials

Products Used: High Entropy Alloys Databases

Accelerating phase prediction via CALPHAD-informed machine learning and data augmentation

Caroline Binde Stoco, Guillaume Deffrennes, Yannick Champion, and Francisco Gil Coury

Computational Materials Science

Products Used: High Entropy Alloys Databases

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Steel

High-throughput design and characterization of an alumina-containing oxide-forming alloy with enhanced hydrogen uptake resistance

Guilherme Antonelli Martiniano, Jacob Steggo, Birhan Sefer, Steve W. Ooi, and Ehsan Ghassemali

Journal of Materials Research and Technology

Products Used: Steel and Fe-Alloys Databases

Aluminum

A process–structure–property ICME framework for additive friction stir deposition repair of aluminum alloys

Hamza Jabbar, Abigail Taylor, Farid Biniyazan, Jack Grubbs, Bryer Sousa, Sadie Beck, and Qiaofu Zhang 

Materials & Design

Products Used: Aluminium-based Alloys Databases, Precipitation Module (TC-PRISMA)

Copper

On the microstructural strategies adopted for achieving improved machinability in commercial brass alloys

Erfan Sharghivand, Luca Bazzana, Antonio Costetti, Nino Mori, Massimiliano Annoni, and Maurizio Vedani

Materials & Design

Products Used: Copper-based Alloys Databases

High-Entropy Alloys

Good enough is better: feasibility vs. Pareto-optimality in alloy design

Cayden Maguire, Christofer Hardcastle, Trevor Hastings, Raymundo Arróyave, and Brent Vela

Digital Discovery

Products Used: High Entropy Alloys Databases

Do you have a recently published paper you'd like us to include?

Please send us a link and we will consider it for the next Publication Newsletter. We also consider slide decks from presentations, videos of talks, and anything that may be of technical benefit to our broad user community.

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