STAM, an open access journal of materials research
Science and Technology of Advanced Materials (STAM) is the leading open access, international journal for outstanding research articles across all aspects of materials science. Our audience is the international materials community across the disciplines of materials science, physics, chemistry, biology as well as engineering.
Citation metrics
- 7.4 (2023) Impact Factor
- Q1 Impact Factor Best Quartile
- 7.8 (2023) 5 year Impact Factor
Speed / acceptance
- 23 days avg. from acceptance to online publication
- 24% acceptance rate
Latest articles
Editor’s Choice
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Machine learning can predict the mechanical properties of polymers
August 23, 2024ARTICLE -
Dual-action therapy shows promise against aggressive oral cancer
July 31, 2024ARTICLE -
Kirigami hydrogels rise from cellulose film
April 22, 2024ARTICLE -
Sensing structure without touching
April 12, 2024ARTICLE
News
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Magnetic-anisotropy modulation in multiferroic heterostructures by ferroelectric domains from first principles -
Highly flexible and transparent colorless polyimide substrate sandwiched between plasma polymerized fluorocarbon and InGaTiO for high performance flexible perovskite solar cells -
Engineering the electronic properties of MoTe2 via defect control -
Developing poly(ethylene glycol)-b-poly(β-hydroxybutyrate)-based self-assembling prodrug for the management of cisplatin-induced acute kidney injury -
Structural analysis and transport properties of [010]-tilt grain boundaries in Fe(Se,Te) -
Improvement in CPP-GMR read head sensor performance using [001]-oriented polycrystalline half-metallic Heusler alloy Co2FeGa0.5Ge0.5 and CoFe bilayer electrode -
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis
STAM Methods
STAM Methods First issue!
STAM Methods was launched in January 2021 as a sister magazine of STAM. It is an English language academic journal specializing in methods for accelerating materials research including materials informatics, machine learning, and high-throughput synthesis/characterization. STAM Methods is a gold open access journal like STAM, that can be read by anyone online.
We look forward to your contributions!