Daniel To

631 citations
14 papers · 554 · h-index 12

Impact in

Papers in

Daniel To

14 papers receiving 542 citations

Peers

Daniel To
Comparison fields: 5 of 106
  • Pharmaceutical Science 194
  • Computational Mechanics 122
  • Food Science 59
  • Spectroscopy 52
  • Fluid Flow and Transfer Processes 18
Replace Laila J. Jallo with:
Laila J. Jallo United States
Vikram Karde United Kingdom
Marcos Llusá Austria
James V. Scicolone United States
Ariel R. Muliadi United States
Maxx Capece United States
Ingfried Zimmermann Germany
Enes Šupuk United Kingdom
Ge Bai United States
Daniel To relative to Laila J. Jallo United States Laila J. Jallo's profile →
Citations per field
00.5×1.5×
Laila J. Jallo · 1×
Citations per year

Countries citing papers authored by Daniel To

Since Specialization
Citations

This map shows the geographic impact of Daniel To'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 Daniel To with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel To more than expected).

Fields of papers citing papers by Daniel To

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel To. 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 Daniel To. The network helps show where Daniel To may publish in the future.

Co-authors

The 16 scholars most cited alongside Daniel To, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel To Line = papers co-authored together Daniel To links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2011146
2 201372
3 201261
4 201460
5 200953
6 201437
7 201126
8
5' untranslated sequences determine degradative pathway for alternate PDGF B/c-sis mRNA's.
199126
9 201521
10
Platelet-derived growth factor in renal development and disease.
199319
11 201918
12 201313
13
Deagglomeration and mixing via the rapid expansion of high pressure and supercritical suspensions
20111
14
Microporous Polymer Films for Enhancing Light Extraction of White Light Organic Light Emitting Diodes
20171

About Daniel To

Daniel To is a scholar working on Pharmaceutical Science, Materials Chemistry, Computational Mechanics, Biomedical Engineering and Molecular Biology, having authored 14 papers that have together received 554 indexed citations. Recurring topics across this work include Drug Solubulity and Delivery Systems (5 papers), Phase Equilibria and Thermodynamics (4 papers), Material Dynamics and Properties (4 papers), Granular flow and fluidized beds (3 papers), Protein purification and stability (2 papers), Microencapsulation and Drying Processes (2 papers), Crystallization and Solubility Studies (2 papers) and Fluid Dynamics and Heat Transfer (1 paper). The work is most often cited by research in Pharmaceutical Science (194 citations), Computational Mechanics (122 citations), Food Science (59 citations), Spectroscopy (52 citations) and Fluid Flow and Transfer Processes (18 citations). Daniel To has collaborated with scholars based in United States, Australia and India. Frequent co-authors include Rajesh N. Davé, Chinmay Ghoroi, Xi Han, Yuhua Chen, Laila J. Jallo, Sankaran Sundaresan, Xiaolong Yin, Catharina Knieke, Mohammad Azad and Maxx Capece. Their work appears in journals such as Powder Technology, International Journal of Pharmaceutics, Journal of Nanoparticle Research, AIChE Journal and Journal of Pharmaceutical Sciences.

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.

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