Results 161 to 170 of about 74,370 (266)

Ameliorative effects of termite‐mediated soils and lime on soil acidity: Implication for barley (Hordeum vulgare) produce

open access: yesAgrosystems, Geosciences &Environment, Volume 8, Issue 4, December 2025.
Abstract Crop production is threatened by low soil fertility and soil acidity in high rainfall areas, while escalating lime and fertilizer costs call for alternative local materials. In this regard, the ameliorative effects of termite‐mediated soils (TMS) as a liming material and source of essential plant nutrients should be investigated.
Abinet Bekele   +3 more
wiley   +1 more source

Photothermal Polarimetric Nanoscopy: An Emerging Technique for Fingerprinting Minerals of Extraterrestrial Origin. [PDF]

open access: yesACS Earth Space Chem
Shay T   +6 more
europepmc   +1 more source

Oxychlorine Species on Mars: A Review

open access: yesReviews of Geophysics, Volume 63, Issue 4, December 2025.
Abstract Oxychlorine species (mainly perchlorate and chlorate) have been identified at multiple locations on the surface of Mars by both orbiter and in situ rovers. They have also been found in martian meteorites. Cl‐isotopes in meteoritic minerals suggest that an oxychlorine cycle has been operating on the martian surface for the last ∼4 billion years.
Kaushik Mitra
wiley   +1 more source

Coupling antigorite deformation and dehydration in high-pressure experiments. [PDF]

open access: yesContrib Mineral Petrol
Eberhard L   +6 more
europepmc   +1 more source

(Table 1) Geochemistry of olivine from Qeqertaa xenoliths

open access: green, 2013
Stefan Bernstein   +2 more
openalex   +2 more sources

Oxidation States of Fe in Constituent Minerals of a Spinel Lherzolite Xenolith from the Tariat Depression, Mongolia: The Significance of Fe3+ in Olivine [PDF]

open access: gold, 2018
Terumi Ejima   +7 more
openalex   +1 more source

EDS Analysis for Petrology: A Probabilistic Framework With GPyEDS

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.
Abstract Microtextural and chemical data from minerals in igneous rocks are critical for unpacking and developing understanding of processes in magmatic systems. Recent advancements leveraging unsupervised machine learning methods offer novel approaches for phase classification without requiring prior knowledge of phases or chemistry.
Norbert Toth   +3 more
wiley   +1 more source

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