Evidence map›Paper›PMID 34300469›Full record

ArticleSensors (Basel, Switzerland)2021

A Grain-Scale Study of Mojave Mars Simulant (MMS-1).

Sathwik S Kasyap, Kostas Senetakis

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sathwik S KasyapDepartment of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.
Kostas SenetakisDepartment of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0003-0190-4768

Funding

Donation fund 9220117Research Grants Council, University Grants Committee CityU 11210419Research Grants Council, University Grants Committee CityU 11214218
6 · The paper itself

Abstract

Space exploration has attracted significant interest by government agencies and the scientific community in recent years in an attempt to explore possible scenarios of settling of facilities on the Moon and Mars surface. One of the important components in space exploration is related with the understanding of the geophysical and geotechnical characteristics of the surfaces of planets and their natural satellites and because of the limitation of available extra-terrestrial samples, many times researchers develop simulants, which mimic the properties and characteristics of the original materials. In the present study, characterization at the grain-scale was performed on the Mojave Mars Simulant (MMS-1) with emphasis on the frictional behavior of small size samples which follow the particle-to-particle configuration. Additional characterization was performed by means of surface composition and morphology analysis and the crushing behavior of individual grains. The results from the study present for the first time the micromechanical tribological response of Mars simulant, and attempts were also made to compare the behavior of this simulant with previously published results on other types of Earth and extra-terrestrial materials. Despite some similarities between Mars and Moon simulants, the unique characteristics of the MMS-1 samples resulted in significant differences and particularly in severe damage of the grain surfaces, which was also linked to the dilation behavior at the grain-scale.

Indexed as

MoonSpace FlightEarth, PlanetEdible GrainExtraterrestrial Environmentfrictiongrain-scale mechanicsmars simulantmicro-scale experimentationspace explorationvesicular texture

Identifiers

PMID34300469
PMCPMC8309639

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.