Pejman Honarmandi

416 total citations
22 papers, 294 citations indexed

About

Pejman Honarmandi is a scholar working on Materials Chemistry, Mechanical Engineering and Automotive Engineering. According to data from OpenAlex, Pejman Honarmandi has authored 22 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Materials Chemistry, 12 papers in Mechanical Engineering and 7 papers in Automotive Engineering. Recurrent topics in Pejman Honarmandi's work include Additive Manufacturing Materials and Processes (8 papers), Machine Learning in Materials Science (7 papers) and Additive Manufacturing and 3D Printing Technologies (7 papers). Pejman Honarmandi is often cited by papers focused on Additive Manufacturing Materials and Processes (8 papers), Machine Learning in Materials Science (7 papers) and Additive Manufacturing and 3D Printing Technologies (7 papers). Pejman Honarmandi collaborates with scholars based in United States, Sweden and Iran. Pejman Honarmandi's co-authors include Raymundo Arróyave, Vahid Attari, M. Aghaie-Khafri, Alaa Elwany, Thien Duong, İbrahim Karaman, Lei Xue, Douglas Allaire, Marius Stan and Noah H. Paulson and has published in prestigious journals such as Acta Materialia, Materials & Design and Additive manufacturing.

In The Last Decade

Pejman Honarmandi

22 papers receiving 288 citations

Peers

Pejman Honarmandi

SPU

Jean-François Antoine France

M.L. Bouazizi Tunisia

Michel Mermet-Guyennet France

Jae‐Gil Lee South Korea

Αλέξανδρος Σολωμού United States

Brent Vela United States

Xavier Margueron France

Dongsheng Yuan China

Max Poech Germany

Jean-François Antoine France

Pejman Honarmandi

81 ×0.4

219 ×1.3

11 ×0.2

7 ×0.2

SPU

72 ×2.0

Citations per year, relative to Pejman Honarmandi Pejman Honarmandi (= 1×) peers Jean-François Antoine

Countries citing papers authored by Pejman Honarmandi

Since Specialization

Citations

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

Fields of papers citing papers by Pejman Honarmandi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pejman Honarmandi

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

All Works

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20 of 20 papers shown

Vela, Brent, et al.. (2025). High-throughput alloy and process design for metal additive manufacturing. npj Computational Materials. 11(1). 179–179. 1 indexed citations

Vela, Brent, et al.. (2024). An automated computational framework to construct printability maps for additively manufactured metal alloys. npj Computational Materials. 10(1). 1 indexed citations

Honarmandi, Pejman, Jiahui Ye, Chen Zhang, et al.. (2023). Uncertainty quantification and propagation across a multi-model computational framework for the tailored design of additively manufactured shape memory alloys. Additive manufacturing. 68. 103506–103506. 6 indexed citations

Sheikh, Sofia Z., Pejman Honarmandi, Brent Vela, et al.. (2022). An Automated Fully-Computational Framework to Construct Printability Maps for Additively Manufactured Metal Alloys. SSRN Electronic Journal. 5 indexed citations

Zhang, Chen, Lei Xue, K.C. Atli, et al.. (2022). Processing parameters and martensitic phase transformation relationships in near defect-free additively manufactured NiTiHf high temperature shape memory alloys. Materials & Design. 222. 110988–110988. 19 indexed citations

Honarmandi, Pejman, Vahid Attari, & Raymundo Arróyave. (2022). Accelerated materials design using batch Bayesian optimization: A case study for solving the inverse problem from materials microstructure to process specification. Computational Materials Science. 210. 111417–111417. 22 indexed citations

Honarmandi, Pejman, Mokarram Hossain, Raymundo Arróyave, & Theocharis Baxevanis. (2021). A Top-Down Characterization of NiTi Single-Crystal Inelastic Properties within Confidence Bounds through Bayesian Inference. Shape Memory and Superelasticity. 7(1). 50–64. 8 indexed citations

Honarmandi, Pejman, Lei Xue, Chen Zhang, et al.. (2021). A Differential Evaporation Model to Predict Chemistry Change of Additively Manufactured Metals. SSRN Electronic Journal. 1 indexed citations

Honarmandi, Pejman, Raiyan Seede, Lei Xue, et al.. (2021). A rigorous test and improvement of the Eagar-Tsai model for melt pool characteristics in laser powder bed fusion additive manufacturing. Additive manufacturing. 47. 102300–102300. 21 indexed citations

10.

Honarmandi, Pejman & Raymundo Arróyave. (2020). Uncertainty Quantification and Propagation in Computational Materials Science and Simulation-Assisted Materials Design. Integrating materials and manufacturing innovation. 9(1). 103–143. 41 indexed citations

11.

Honarmandi, Pejman, Noah H. Paulson, Raymundo Arróyave, & Marius Stan. (2019). Uncertainty quantification and propagation in CALPHAD modeling. Modelling and Simulation in Materials Science and Engineering. 27(3). 34003–34003. 16 indexed citations

12.

Honarmandi, Pejman. (2019). Materials Design Under Bayesian Uncertainty Quantification. OakTrust (Texas A&M University Libraries). 1 indexed citations

13.

Attari, Vahid, et al.. (2019). Uncertainty propagation in a multiscale CALPHAD-reinforced elastochemical phase-field model. Acta Materialia. 183. 452–470. 23 indexed citations

14.

Talapatra, Anjana, Pejman Honarmandi, Αλέξανδρος Σολωμού, et al.. (2019). Experiment Design Frameworks for Accelerated Discovery of Targeted Materials Across Scales. Frontiers in Materials. 6. 18 indexed citations

15.

Attari, Vahid, et al.. (2019). Uncertainty Propagation in a Multiscale CALPHAD-Reinforced Elastochemical Phase-Field Model. SSRN Electronic Journal. 1 indexed citations

16.

Honarmandi, Pejman, et al.. (2019). Uncertainty Propagation via Probability Measure Optimized Importance Weights with Application to Parametric Materials Models. AIAA Scitech 2019 Forum. 6 indexed citations

17.

Honarmandi, Pejman & Raymundo Arróyave. (2016). Using Bayesian framework to calibrate a physically based model describing strain-stress behavior of TRIP steels. Computational Materials Science. 129. 66–81. 11 indexed citations

18.

Duong, Thien, Robert Hackenberg, A. Landa, et al.. (2016). Revisiting thermodynamics and kinetic diffusivities of uranium–niobium with Bayesian uncertainty analysis. Calphad. 55. 219–230. 41 indexed citations

19.

Honarmandi, Pejman, et al.. (2015). Describing the deformation behaviour of TRIP and dual phase steels employing an irreversible thermodynamics formulation. Materials Science and Technology. 31(13). 1658–1663. 5 indexed citations

20.

Honarmandi, Pejman & M. Aghaie-Khafri. (2012). Hot Deformation Behavior of Ti–6Al–4V Alloy in β Phase Field and Low Strain Rate. Metallography Microstructure and Analysis. 2(1). 13–20. 20 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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