Reliability and reproducibility of data and analysis issues are impacting most areas of modern science, including those of importance to the AVS. In 2020, JVST A published a special topic collection on Reproducibility Challenges and Solutions with a Focus on XPS. As a follow up to the first collection of papers, a second collection will be published that expands into other areas of surface analysis.
This special topic collection will include issues related to AES, SIMS, LEIS, Ellipsometry and Scanning Probe methods, as well as XPS topics not fully covered in the first collection. The intent is to include papers that identify important challenges faced by analysts that often lead to incomplete or erroneous results and to identify useful protocols and other solutions.
Papers are also encouraged that address issues and opportunities raised by the introduction of new technologies and modern analysis methods including machine learning and AI. Papers may focus on specific techniques or application areas, data collection and/or analysis, or appropriate reporting for reliable and reproducible data and analysis. Examples of research approaches, establishing expectations, protocols, workflows, method validation, checklists, and other efforts to address reproducibility issues are welcome.
To learn what guides and protocols are under development or to participate in their development, contact Don Baer (firstname.lastname@example.org) or Ian Gilmore (Ian.Gilmore@NPL.co.uk). This collection will complement a Biointerphases Special Collection including tutorials for ToF-SIMS, guest edited by Dan Graham (University of Washington, USA).
The range of papers published in the first reproducibility collection may be a useful guide to some of the types of papers that may be relevant, but other types of papers focusing on computation and data mining are encouraged. We are particularly interested in papers that target the challenges faced by new analysts having little expertise with surface analysis methods.
Topics covered include, but are not limited to reproducibility challenges and solutions related to:
- Surface sensitive analysis methods (e g. AES, SIMS, LEIS, Ellipsometry, Scanning Probe Microscopy)
- XPS topics not fully covered in the first collection (e.g., sample damage, HAXPES, NAP-XPS, analytical uncertainties, and advanced XPS peak-fitting software)
- Advanced analysis approaches including expert systems, machine learning, and AI
- Application areas such as energy storage and conversion or biomaterials
- Research approaches, expectations, protocols, workflows, method validation and comparison studies, checklists, reporting, and other efforts to address reproducibility issues
Don Baer, Pacific Northwest National Laboratory (emeritus) (USA)
Ian Gilmore, National Physical Laboratory (UK)
Guest Associate Editors
Satoka Aoyagi, Seikei University (Japan)
Kateryna Artyushkova, Physical Electronics-Phi (USA)
Chris Easton, Commonwealth Scientific and Industrial Research Organisation – CSIRO (Australia)
Alberto Herrera Gómez, Cinvestav (Mexico)
Matthew Linford, Brigham Young University (USA)
George Orji, National Institute of Standards Technology (USA)
Alexander Shard, National Physical Laboratory (UK)
Gustavo F. Trindade, National Physical Laboratory (UK)
Manuscript Details & Submission