# Monte Carlo Simulations of Au <sub>38</sub> (SCH <sub>3</sub> ) <sub>24</sub> Nanocluster Using Distance-Based Machine Learning Methods

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/monte-carlo-simulations-of-au-sub-38-sub-sch-sub-3-sub-sub-24-sub-nanocluster/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Antti Pihlajamäki,Joonas Hämäläinen,Joakim Linja,P. Nieminen,Sami Malola,Tommi Kärkkäinen,Hannu Häkkinen |
| Citations | 50 |
| DOI | 10.1021/acs.jpca.0c01512 |
| Fields | Materials Science |
| Open Access | true |
| OA Status | green |
| OA URL | https://figshare.com/articles/Monte_Carlo_Simulations_of_Au_sub_38_sub_SCH_sub_3_sub_sub_24_sub_Nanocluster_Using_Distance-Based_Machine_Learning_Methods/12397985 |
| OpenAlex ID | https://openalex.org/W3025529011 |
| PMID | 32412747 |
| Type | article |
| Year | 2020 |

## Paper authors

- [P. Nieminen](https://scholariq.org/researchers/p-nieminen/)

## Paper primary topic

- [Nanocluster Synthesis and Applications](https://scholariq.org/topics/nanocluster-synthesis-and-applications/)

## Paper topics

- [Nanocluster Synthesis and Applications](https://scholariq.org/topics/nanocluster-synthesis-and-applications/)
- [Advanced Nanomaterials in Catalysis](https://scholariq.org/topics/advanced-nanomaterials-in-catalysis/)
- [Machine Learning in Materials Science](https://scholariq.org/topics/machine-learning-in-materials-science/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.