Sharlotte Kramer

2.9k total citations · 1 hit paper
33 papers, 2.1k citations indexed

About

Sharlotte Kramer is a scholar working on Mechanical Engineering, Mechanics of Materials and Materials Chemistry. According to data from OpenAlex, Sharlotte Kramer has authored 33 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Mechanical Engineering, 12 papers in Mechanics of Materials and 8 papers in Materials Chemistry. Recurrent topics in Sharlotte Kramer's work include Additive Manufacturing Materials and Processes (5 papers), Model Reduction and Neural Networks (5 papers) and Metal Forming Simulation Techniques (5 papers). Sharlotte Kramer is often cited by papers focused on Additive Manufacturing Materials and Processes (5 papers), Model Reduction and Neural Networks (5 papers) and Metal Forming Simulation Techniques (5 papers). Sharlotte Kramer collaborates with scholars based in United States, United Kingdom and Italy. Sharlotte Kramer's co-authors include Nancy R. Sottos, Scott R. White, Jeffrey S. Moore, Ben Blaiszik, Solar C. Olugebefola, Brett A. Beiermann, David A. McIlroy, Martha E. Grady, Douglas A. Davis and Craig M. Hamel and has published in prestigious journals such as Advanced Materials, Advanced Functional Materials and Journal of Materials Chemistry.

In The Last Decade

Sharlotte Kramer

31 papers receiving 2.0k citations

Hit Papers

Self-Healing Polymers and Composites 2010 2026 2015 2020 2010 250 500 750 1000

Peers

Sharlotte Kramer
Andrew Hamilton United Kingdom
Sungmin Park South Korea
Jeffery W. Baur United States
Young‐Hoon Lee South Korea
Joonmyung Choi South Korea
Yiqi Mao China
Andrew Hamilton United Kingdom
Sharlotte Kramer
Citations per year, relative to Sharlotte Kramer Sharlotte Kramer (= 1×) peers Andrew Hamilton

Countries citing papers authored by Sharlotte Kramer

Since Specialization
Citations

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

Fields of papers citing papers by Sharlotte Kramer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sharlotte Kramer

This figure shows the co-authorship network connecting the top 25 collaborators of Sharlotte Kramer. A scholar is included among the top collaborators of Sharlotte Kramer 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 Sharlotte Kramer. Sharlotte Kramer 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
2.
Jones, Elizabeth M. C., et al.. (2024). Digital image correlation and infrared thermography data for seven unique geometries of 304L stainless steel. Scientific Data. 11(1). 1101–1101. 3 indexed citations
3.
Vlassis, Nikolaos N., et al.. (2023). Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter. Computational Mechanics. 72(1). 95–124. 14 indexed citations
4.
Hamel, Craig M., Sharlotte Kramer, & Kevin Long. (2023). Calibrating Constitutive Models with Full-Field Data via Physics Informed Neural Networks. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
5.
Echlin, McLean P., Craig M. Hamel, Sharlotte Kramer, et al.. (2023). Perspective: Machine learning in experimental solid mechanics. Journal of the Mechanics and Physics of Solids. 173. 105231–105231. 42 indexed citations
6.
Madison, Jonathan D, Andrew Polonsky, H. Jin, et al.. (2023). Toward accurate prediction of partial-penetration laser weld performance informed by three-dimensional characterization – Part II: μCT based finite element simulations. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2. 100007–100007. 2 indexed citations
7.
Hamel, Craig M., Sharlotte Kramer, & Kevin Long. (2022). Calibrating Constitutive Models with Full Field Data via Physics Informed Neural Networks.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations
8.
Hamel, Craig M., et al.. (2022). Machine learning constitutive models of elastomeric foams. Computer Methods in Applied Mechanics and Engineering. 391. 114492–114492. 32 indexed citations
9.
Ogoke, Francis, et al.. (2022). Deep-learned generators of porosity distributions produced during metal Additive Manufacturing. Additive manufacturing. 60. 103250–103250. 8 indexed citations
10.
Park, Taejoon, Hojun Lim, Benjamin Reedlunn, et al.. (2021). The impact of heterogeneous microstructural features on crystal plasticity modeling of plastic anisotropy. Modelling and Simulation in Materials Science and Engineering. 29(7). 75004–75004. 9 indexed citations
11.
Bolintineanu, Dan, et al.. (2021). Anisotropy evolution of elastomeric foams during uniaxial compression measured via in-situ X-ray computed tomography. Materialia. 18. 101112–101112. 13 indexed citations
12.
Baldi, Antonio, Sharlotte Kramer, Fabrice Pierron, & John Considine. (2020). Residual Stress, Thermomechanics & Infrared Imaging and Inverse Problems, Volume 6. River Publishers eBooks. 1 indexed citations
13.
Kramer, Sharlotte, Jennifer L. Jordan, H. Jin, & Jay Carroll. (2018). Mechanics of Additive and Advanced Manufacturing, Volume 8. River Publishers eBooks. 3 indexed citations
14.
Jones, Elizabeth M. C., Jay Carroll, Sharlotte Kramer, et al.. (2018). Parameter covariance and non-uniqueness in material model calibration using the Virtual Fields Method. Computational Materials Science. 152. 268–290. 48 indexed citations
15.
Kramer, Sharlotte & Brad Boyce. (2016). Preface to the special volume on the second Sandia Fracture Challenge. International Journal of Fracture. 198(1-2). 1–3. 2 indexed citations
16.
Reu, Phillip L., et al.. (2016). Digital Volume Correlation for Materials Characterization.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
17.
Beiermann, Brett A., Sharlotte Kramer, Jeffrey S. Moore, Scott R. White, & Nancy R. Sottos. (2011). Role of Mechanophore Orientation in Mechanochemical Reactions. ACS Macro Letters. 1(1). 163–166. 100 indexed citations
18.
Blaiszik, Ben, Sharlotte Kramer, Martha E. Grady, et al.. (2011). Autonomic Restoration of Electrical Conductivity. Advanced Materials. 24(3). 398–401. 269 indexed citations
19.
Kramer, Sharlotte, G. Ravichandran, & Kaushik Bhattacharya. (2009). Transmission wavefront shearing interferometry for photoelastic materials. Applied Optics. 48(13). 2450–2450. 6 indexed citations
20.
Kramer, Sharlotte, M. Mello, G. Ravichandran, & Kaushik Bhattacharya. (2009). Phase Shifting Full-Field Interferometric Methods for Determination of In-Plane Tensorial Stress. Experimental Mechanics. 49(2). 303–315. 10 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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