Projects per year
Personal profile
Personal Statement
I am a PhD researcher and research assistant in Chemistry, focusing on accelerating the discovery of high-performance organic semiconductors through machine learning and computational modelling. My work combines data-driven methods with materials chemistry to advance the design of next-generation electronic materials. I completed an MChem in Pure and Applied Chemistry in 2024, where I first developed an interest in the intersection of computational chemistry and materials discovery. My research aims to apply modern data science to real-world challenges in sustainable and functional materials design.
Academic / Professional qualifications
Sep 2019 - Jun 2024 Master's Degree in Pure and Applied Chemistry at the University of Strathclyde
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Dive into the research topics where Malin Zollner is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Functional Materials Discovery Using Artificial Intelligence
Zollner, M. (Researcher), Nematiaram, T. (Principal Investigator) & Moshfeghi, Y. (Principal Investigator)
1/10/24 → 30/09/27
Project: Research - Studentship
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BenchmarkSet1500: High-Accuracy Excited-State Reference Data for Organic Semiconductors (PSDI)
Zollner, M. (Researcher) & Nematiaram, T. (Principal Investigator)
1/11/25 → 31/03/26
Project: Research
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A multireference excited state database for correlation-aware screening of organic semiconductors in excitonic energy-materials discovery
Zollner, M. & Nematiaram, T., 2 Jun 2026. 1 p.Research output: Contribution to conference › Poster
Open AccessFile2 Downloads (Pure) -
Learning the limits: how data, diversity, and representation control machine-learning predictions of reorganisation energy
Zollner, M., Moshfeghi, Y. & Nematiaram, T., 16 Apr 2026, In: Journal of Materials Chemistry. C . 14, 14, p. 5999-6011 13 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Downloads (Pure)
Datasets
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Data for "Learning the limits: how data, diversity, and representation control machine-learning predictions of reorganisation energy"
Zollner, M. (Creator), Nematiaram, T. (Contributor) & Moshfeghi, Y. (Contributor), University of Strathclyde, 12 Feb 2026
DOI: 10.15129/fbb78cbc-64e5-4c24-983a-d258a1e92367
Dataset
Prizes
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Hamilton Barrett Prize
Zollner, M. (Recipient), Nematiaram, T. (Recipient) & Moshfeghi, Y. (Recipient), Feb 2026
Prize: Prize (including medals and awards)
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Images of Collaboration
Zollner, M. (Recipient), 26 Feb 2026
Prize: Prize (including medals and awards)
Activities
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9th Materials & Computational Chemistry Section Away Day
Zollner, M. (Participant)
25 Jun 2026Activity: Presenting or Organising an Event › Participation in conference
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A Multireference Excited State Database for Correlation-Aware Screening of Organic Semiconductors in Excitonic Energy-Materials Discovery
Zollner, M. (Speaker) & Nematiaram, T. (Contributor)
16 Jun 2026Activity: Talk or Presentation › Oral presentation