Daniel J. Griffin

661 total citations
21 papers, 289 citations indexed

About

Daniel J. Griffin is a scholar working on Materials Chemistry, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, Daniel J. Griffin has authored 21 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Materials Chemistry, 6 papers in Molecular Biology and 6 papers in Biomedical Engineering. Recurrent topics in Daniel J. Griffin's work include Crystallization and Solubility Studies (8 papers), Innovative Microfluidic and Catalytic Techniques Innovation (6 papers) and Lipid Membrane Structure and Behavior (3 papers). Daniel J. Griffin is often cited by papers focused on Crystallization and Solubility Studies (8 papers), Innovative Microfluidic and Catalytic Techniques Innovation (6 papers) and Lipid Membrane Structure and Behavior (3 papers). Daniel J. Griffin collaborates with scholars based in United States, Canada and Norway. Daniel J. Griffin's co-authors include Martha A. Grover, Ronald W. Rousseau, Yoshiaki Kawajiri, Xun Tang, Jason E. Hein, Sebastian Steiner, Lars P. E. Yunker, Scott A. Frank, Connor W. Coley and Louise C. Abbott and has published in prestigious journals such as Cancer Research, Industrial & Engineering Chemistry Research and Chemical Engineering Science.

In The Last Decade

Daniel J. Griffin

20 papers receiving 281 citations

Peers

Daniel J. Griffin
Gerard Capellades United States
John McGinty United Kingdom
Daniel B. Patience United States
Nicholas C. S. Kee United States
Samir Diab United Kingdom
Martin Wijaya Hermanto Singapore
Christopher J. Testa United States
Kati Pöllänen Finland
Patrick Zimmermann Germany
Des O’Grady Ireland
Gerard Capellades United States
Daniel J. Griffin
Citations per year, relative to Daniel J. Griffin Daniel J. Griffin (= 1×) peers Gerard Capellades

Countries citing papers authored by Daniel J. Griffin

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Griffin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel J. Griffin

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Griffin. A scholar is included among the top collaborators of Daniel J. Griffin 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 Daniel J. Griffin. Daniel J. Griffin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Griffin, Daniel J., et al.. (2024). A Continuous Process for Manufacturing Apremilast. Part II: Process Characterization to Establish a Parametric Control Strategy. Organic Process Research & Development. 28(5). 1385–1401. 4 indexed citations
2.
Gong, Huan, Daniel J. Griffin, Chad E. Groer, et al.. (2024). Abstract 3185: Glatiramer acetate enhances tumor retention and mitigates systemic toxicity of toll-like receptor 9 agonists as intratumoral immunotherapy. Cancer Research. 84(6_Supplement). 3185–3185. 1 indexed citations
3.
Hsieh, Hsiao‐Wu, et al.. (2024). PAT-Enabled Automated Feedforward Control: An Application to the Continuous Manufacture of Apremilast. Organic Process Research & Development. 28(7). 2844–2853. 3 indexed citations
4.
Griffin, Daniel J., Connor W. Coley, Scott A. Frank, Joel M. Hawkins, & Klavs F. Jensen. (2023). Opportunities for Machine Learning and Artificial Intelligence to Advance Synthetic Drug Substance Process Development. Organic Process Research & Development. 27(11). 1868–1879. 21 indexed citations
5.
Sato, Yusuke, Junliang Liu, Ikenna E. Ndukwe, et al.. (2023). Liquid/liquid heterogeneous reaction monitoring: Insights into biphasic Suzuki-Miyaura cross-coupling. Chem Catalysis. 3(7). 100687–100687. 4 indexed citations
6.
Griffin, Daniel J., et al.. (2023). Developing and Optimizing a Quench-Crystallization Operation in Drug Substance Manufacturing. Organic Process Research & Development. 27(8). 1499–1509. 1 indexed citations
7.
Parsons, Andrew T., et al.. (2022). Axial Chirality in the Sotorasib Drug Substance, Part 1: Development of a Classical Resolution to Prepare an Atropisomerically Pure Sotorasib Intermediate. Organic Process Research & Development. 26(9). 2629–2635. 14 indexed citations
8.
Zepel, Tara, Daniel J. Griffin, Sean Clark, et al.. (2021). Automated solubility screening platform using computer vision. iScience. 24(3). 102176–102176. 52 indexed citations
9.
Cherney, Alan H., Xiaofei Dong, Peter K. Dornan, et al.. (2020). Accelerated Development of a Scalable Ring-Closing Metathesis to Manufacture AMG 176 Using a Combined High-Throughput Experimentation and Computational Modeling Approach. Organic Process Research & Development. 25(3). 442–451. 10 indexed citations
10.
Maloney, Andrew J., Elçin Içten, Gerard Capellades, et al.. (2020). A Virtual Plant for Integrated Continuous Manufacturing of a Carfilzomib Drug Substance Intermediate, Part 3: Manganese-Catalyzed Asymmetric Epoxidation, Crystallization, and Filtration. Organic Process Research & Development. 24(10). 1891–1908. 26 indexed citations
11.
Grover, Martha A., et al.. (2020). Optimal feedback control of batch self-assembly processes using dynamic programming. Journal of Process Control. 88. 32–42. 21 indexed citations
12.
Grover, Martha A., Daniel J. Griffin, & Xun Tang. (2019). Control of Self-Assembly with Dynamic Programming. IFAC-PapersOnLine. 52(1). 1–9. 6 indexed citations
13.
Griffin, Daniel J., Yoshiaki Kawajiri, Ronald W. Rousseau, & Martha A. Grover. (2017). Using MC plots for control of paracetamol crystallization. Chemical Engineering Science. 164. 344–360. 17 indexed citations
14.
Griffin, Daniel J., Xun Tang, & Martha A. Grover. (2016). Externally directing self-assembly with dynamic programming. 3086–3091. 3 indexed citations
15.
Griffin, Daniel J., Martha A. Grover, Yoshiaki Kawajiri, & Ronald W. Rousseau. (2016). Data-Driven Modeling and Dynamic Programming Applied to Batch Cooling Crystallization. Industrial & Engineering Chemistry Research. 55(5). 1361–1372. 39 indexed citations
16.
Griffin, Daniel J., Martha A. Grover, Yoshiaki Kawajiri, & Ronald W. Rousseau. (2015). Mass–count plots for crystal size control. Chemical Engineering Science. 137. 338–351. 11 indexed citations
17.
Griffin, Daniel J., Martha A. Grover, Yoshiaki Kawajiri, & Ronald W. Rousseau. (2015). Combining ATR-FTIR and FBRM for feedback on crystal size. 60. 4308–4313. 4 indexed citations
18.
Griffin, Daniel J., Martha A. Grover, Yoshiaki Kawajiri, & Ronald W. Rousseau. (2014). Robust multicomponent IR-to-concentration model regression. Chemical Engineering Science. 116. 77–90. 12 indexed citations
19.
Griffin, Daniel J., Yoshiaki Kawajiri, Martha A. Grover, & Ronald W. Rousseau. (2014). Feedback Control of Multicomponent Salt Crystallization. Crystal Growth & Design. 15(1). 305–317. 12 indexed citations
20.
Alterman, Richard & Daniel J. Griffin. (1996). Improving case retrieval by remembering questions. National Conference on Artificial Intelligence. 678–683. 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.

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