Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Mechanism of Molybdenum Nitrogenase
19961.5k citationsBarbara K. Burgess, David Loweprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of David Lowe's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Lowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Lowe more than expected).
This network shows the impact of papers produced by David Lowe. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Lowe. The network helps show where David Lowe may publish in the future.
Co-authorship network of co-authors of David Lowe
This figure shows the co-authorship network connecting the top 25 collaborators of David Lowe.
A scholar is included among the top collaborators of David Lowe based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with David Lowe. David Lowe is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Welz, Oliver, Arkke J. Eskola, Leonid Sheps, et al.. (2014). Rate coefficients of Criegee Intermediate (CH2OO and CH3CHOO) reactions with formic and acetic acid are close to their collision limit: Direct kinetics measurements and atmospheric implications. Angewandte Chemie International Edition. 126(18). 4635–4638.12 indexed citations
Lindsay, Euan, et al.. (2008). Factors that impact learning outcomes in both simulation and remote laboratories.. UTS ePRESS (University of Technology Sydney). 2008(1). 6251–6258.12 indexed citations
Lindsay, Euan, Dikai Liu, Steven R. Murray, & David Lowe. (2007). Remote Laboratories in Engineering Education: Trends in Students' Perceptions. eSpace (Curtin University).27 indexed citations
Alexander, Shirley, et al.. (2006). Towards a mapping of the field of e-learning. EdMedia: World Conference on Educational Media and Technology. 2006(1). 1636–1642.8 indexed citations
Moulton, Bruce & David Lowe. (2005). Engineering students' perceptions of the importance of personal abilities in relation to career performance, and their perceptions of the extent to which their courses focus on personal abilities. UTS ePRESS (University of Technology Sydney). 1064.5 indexed citations
12.
Lowe, David, et al.. (2004). Development of a decision support system (DSS) for the contractor's decision to bid: regression and neural networks solutions. Journal of Financial Management of Property and Construction. 9(1). 27–42.2 indexed citations
13.
Harding, Anthony, et al.. (2000). The cost of procurement: a neural network approach. Research Explorer (The University of Manchester). 428–438.3 indexed citations
14.
Davey, Caroline L., David Lowe, A. Roy Duff, & Stephen O. Ogunlana. (1999). Harmony and Profit in SMEs: The Possibilities and Limitations of Building Partnerships. Research Explorer (The University of Manchester). 15–24.2 indexed citations
15.
Lowe, David & Will Hughes. (1998). Effective feedback and systematic reflection in design cost estimating. Research Explorer (The University of Manchester). 78–87.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.