anirudh prabhu | Rensselaer Polytechnic Institute (original) (raw)
Papers by anirudh prabhu
Minerals
A survey of the average Mohs hardness of minerals throughout Earth’s history reveals a significan... more A survey of the average Mohs hardness of minerals throughout Earth’s history reveals a significant and systematic decrease from >6 in presolar grains to ~5 for Archean lithologies to <4 for Phanerozoic minerals. Two primary factors contribute to this temporal decrease in the average Mohs hardness. First, selective losses of softer minerals throughout billions of years of near-surface processing lead to preservational biases in the mineral record. Second, changes in the processes of mineral formation play a significant role because more ancient refractory stellar phases and primary igneous minerals of the Hadean/Archean Eon are intrinsically harder than more recently weathered products, especially following the Paleoproterozoic Great Oxidation Event and the production of Phanerozoic biominerals. Additionally, anthropogenic sampling biases resulting from the selective exploration and curation of the mineralogical record may be superimposed on these two factors.
AGU Fall Meeting Abstracts, Dec 1, 2017
Journal of the Royal Society Interface, Feb 1, 2023
The concepts that we generally associate with the field of data science are strikingly descriptiv... more The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The ‘information life cycle’, which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the ‘data–information–knowledge ecosystem’, developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.
American Mineralogist
Minerals are information-rich materials that offer researchers a glimpse into the evolution of pl... more Minerals are information-rich materials that offer researchers a glimpse into the evolution of planetary bodies. Thus, it is important to extract, analyze, and interpret this abundance of information to improve our understanding of the planetary bodies in our solar system and the role our planet’s geosphere played in the origin and evolution of life. Over the past several decades, data-driven efforts in mineralogy have seen a gradual increase. The development and application of data science and analytics methods to mineralogy, while extremely promising, has also been somewhat ad hoc in nature. To systematize and synthesize the direction of these efforts, we introduce the concept of “Mineral Informatics,” which is the next frontier for researchers working with mineral data. In this paper, we present our vision for Mineral Informatics and the X-Informatics underpinnings that led to its conception, as well as the needs, challenges, opportunities, and future directions of the field. The...
Geological Society of America Abstracts with Programs
Journal of Geophysical Research: Solid Earth, 2021
Diamond‐hosted majoritic garnet inclusions provide unique insights into the Earth's deep, and... more Diamond‐hosted majoritic garnet inclusions provide unique insights into the Earth's deep, and otherwise inaccessible, mantle. Compared with other types of mineral inclusions found in sub‐lithospheric diamonds, majoritic garnets can provide the most accurate estimates of diamond formation pressures because laboratory experiments have shown that garnet chemistry varies strongly as a function of pressure. However, evaluation using a compilation of experimental data demonstrates that none of the available empirical barometers are reliable for predicting the formation pressure of many experimental majoritic garnets and cannot be applied with confidence to diamond‐hosted garnet inclusions. On the basis of the full experimental data set, we develop a novel type of majorite barometer using machine learning algorithms. Cross validation demonstrates that Random Forest Regression allows accurate prediction of the formation pressure across the full range of experimental majoritic garnet com...
A. Boujibar, S. Zhang, S. Howell, A. Prabhu, S. Narkar, G. Hystad, A. Eleish, S. M. Morrison, N. ... more A. Boujibar, S. Zhang, S. Howell, A. Prabhu, S. Narkar, G. Hystad, A. Eleish, S. M. Morrison, N. Liu, T. Stephan, C. M. O'D. Alexander, R. M. Hazen, and L. R. Nittler, Geophysical Laboratory, Carnegie Institution for Science, Washington, DC, USA. Department of Physics, Washington College, Chestertown, MD, USA. Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, USA. Purdue University Northwest, Mathematics, Statistics and Computer Science, Hammond, IN, USA. Department of Physics, Washington University in St. Louis, St. Louis, MO, USA. Department of the Geophysical Sciences, The University of Chicago, Chicago, IL, USA. Chicago Center for Cosmochemistry, Chicago, IL, USA. Department of Terrestrial Magnetism, Carnegie Institution for Science, Washington, DC, USA. (aboujibar@carnegiescience.edu)
Geological Society of America Abstracts with Programs
Geological Society of America Abstracts with Programs
This chapter highlights the use of data-driven discovery to address remaining gaps in our underst... more This chapter highlights the use of data-driven discovery to address remaining gaps in our understanding of deep carbon
American Mineralogist, 2020
Information-rich attributes of minerals reveal their physical, chemical, and biological modes of ... more Information-rich attributes of minerals reveal their physical, chemical, and biological modes of origin in the context of planetary evolution, and thus they provide the basis for an evolutionary system of mineralogy. Part III of this system considers the formation of 43 different primary crystalline and amorphous phases in chondrules, which are diverse igneous droplets that formed in environments with high dust/gas ratios during an interval of planetesimal accretion and differentiation between 4566 and 4561 Ma. Chondrule mineralogy is complex, with several generations of initial droplet formation via various proposed heating mechanisms, followed in many instances by multiple episodes of reheating and partial melting. Primary chondrule mineralogy thus reflects a dynamic stage of mineral evolution, when the diversity and distribution of natural condensed solids expanded significantly.
PNAS Nexus
The locations of minerals and mineral-forming environments, despite being of great scientific imp... more The locations of minerals and mineral-forming environments, despite being of great scientific importance and economic interest, are often difficult to predict due to the complex nature of natural systems. In this work, we embrace the complexity and inherent “messiness” of our planet's intertwined geological, chemical, and biological systems by employing machine learning to characterize patterns embedded in the multidimensionality of mineral occurrence and associations. These patterns are a product of, and therefore offer insight into, the Earth's dynamic evolutionary history. Mineral association analysis quantifies high-dimensional multicorrelations in mineral localities across the globe, enabling the identification of previously unknown mineral occurrences, as well as mineral assemblages and their associated paragenetic modes. In this study, we have predicted (i) the previously unknown mineral inventory of the Mars analogue site, Tecopa Basin, (ii) new locations of uranium ...
Part of Anirudh Prabhu PhD Dissertation. Contains the results of running the text to rule convers... more Part of Anirudh Prabhu PhD Dissertation. Contains the results of running the text to rule conversion workflow described in chapter 5 of the dissertation. The dataset preview and its description can be found in Appendix E of the dissertation document.
Encyclopedia of Big Data, 2022
Encyclopedia of Big Data, 2022
A machine learning barometer (using Random Forest Regression) to calculate equilibration pressure... more A machine learning barometer (using Random Forest Regression) to calculate equilibration pressure for majoritic garnets<br>Updated 04/02/21 (21/01/21) (10/12/20):<br>******<br><b>The barometer code</b><br>The barometer is provided as python scripts (.py) and Jupiter Notebooks (.ipynb) files. These are completely equivalent to one another and which is used depends on the users preference. Separate instructions are provided for each.<br>data files included in this repository are:<br> • "<b>Majorite_database_04022021.xlsm</b>" (Excel sheet of literature majoritic garnet compositions - inclusions (up to date as of 04/02/2021) and experiments (up to date as of 03/07/2020). This data includes all compositions that are close to majoritic, but some are borderline. Filtering as described in paper accompanying this barometer is performed in the python script prior to any data analysis or fitting)<br> • "<b>...
Minerals
A survey of the average Mohs hardness of minerals throughout Earth’s history reveals a significan... more A survey of the average Mohs hardness of minerals throughout Earth’s history reveals a significant and systematic decrease from >6 in presolar grains to ~5 for Archean lithologies to <4 for Phanerozoic minerals. Two primary factors contribute to this temporal decrease in the average Mohs hardness. First, selective losses of softer minerals throughout billions of years of near-surface processing lead to preservational biases in the mineral record. Second, changes in the processes of mineral formation play a significant role because more ancient refractory stellar phases and primary igneous minerals of the Hadean/Archean Eon are intrinsically harder than more recently weathered products, especially following the Paleoproterozoic Great Oxidation Event and the production of Phanerozoic biominerals. Additionally, anthropogenic sampling biases resulting from the selective exploration and curation of the mineralogical record may be superimposed on these two factors.
AGU Fall Meeting Abstracts, Dec 1, 2017
Journal of the Royal Society Interface, Feb 1, 2023
The concepts that we generally associate with the field of data science are strikingly descriptiv... more The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The ‘information life cycle’, which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the ‘data–information–knowledge ecosystem’, developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.
American Mineralogist
Minerals are information-rich materials that offer researchers a glimpse into the evolution of pl... more Minerals are information-rich materials that offer researchers a glimpse into the evolution of planetary bodies. Thus, it is important to extract, analyze, and interpret this abundance of information to improve our understanding of the planetary bodies in our solar system and the role our planet’s geosphere played in the origin and evolution of life. Over the past several decades, data-driven efforts in mineralogy have seen a gradual increase. The development and application of data science and analytics methods to mineralogy, while extremely promising, has also been somewhat ad hoc in nature. To systematize and synthesize the direction of these efforts, we introduce the concept of “Mineral Informatics,” which is the next frontier for researchers working with mineral data. In this paper, we present our vision for Mineral Informatics and the X-Informatics underpinnings that led to its conception, as well as the needs, challenges, opportunities, and future directions of the field. The...
Geological Society of America Abstracts with Programs
Journal of Geophysical Research: Solid Earth, 2021
Diamond‐hosted majoritic garnet inclusions provide unique insights into the Earth's deep, and... more Diamond‐hosted majoritic garnet inclusions provide unique insights into the Earth's deep, and otherwise inaccessible, mantle. Compared with other types of mineral inclusions found in sub‐lithospheric diamonds, majoritic garnets can provide the most accurate estimates of diamond formation pressures because laboratory experiments have shown that garnet chemistry varies strongly as a function of pressure. However, evaluation using a compilation of experimental data demonstrates that none of the available empirical barometers are reliable for predicting the formation pressure of many experimental majoritic garnets and cannot be applied with confidence to diamond‐hosted garnet inclusions. On the basis of the full experimental data set, we develop a novel type of majorite barometer using machine learning algorithms. Cross validation demonstrates that Random Forest Regression allows accurate prediction of the formation pressure across the full range of experimental majoritic garnet com...
A. Boujibar, S. Zhang, S. Howell, A. Prabhu, S. Narkar, G. Hystad, A. Eleish, S. M. Morrison, N. ... more A. Boujibar, S. Zhang, S. Howell, A. Prabhu, S. Narkar, G. Hystad, A. Eleish, S. M. Morrison, N. Liu, T. Stephan, C. M. O'D. Alexander, R. M. Hazen, and L. R. Nittler, Geophysical Laboratory, Carnegie Institution for Science, Washington, DC, USA. Department of Physics, Washington College, Chestertown, MD, USA. Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, USA. Purdue University Northwest, Mathematics, Statistics and Computer Science, Hammond, IN, USA. Department of Physics, Washington University in St. Louis, St. Louis, MO, USA. Department of the Geophysical Sciences, The University of Chicago, Chicago, IL, USA. Chicago Center for Cosmochemistry, Chicago, IL, USA. Department of Terrestrial Magnetism, Carnegie Institution for Science, Washington, DC, USA. (aboujibar@carnegiescience.edu)
Geological Society of America Abstracts with Programs
Geological Society of America Abstracts with Programs
This chapter highlights the use of data-driven discovery to address remaining gaps in our underst... more This chapter highlights the use of data-driven discovery to address remaining gaps in our understanding of deep carbon
American Mineralogist, 2020
Information-rich attributes of minerals reveal their physical, chemical, and biological modes of ... more Information-rich attributes of minerals reveal their physical, chemical, and biological modes of origin in the context of planetary evolution, and thus they provide the basis for an evolutionary system of mineralogy. Part III of this system considers the formation of 43 different primary crystalline and amorphous phases in chondrules, which are diverse igneous droplets that formed in environments with high dust/gas ratios during an interval of planetesimal accretion and differentiation between 4566 and 4561 Ma. Chondrule mineralogy is complex, with several generations of initial droplet formation via various proposed heating mechanisms, followed in many instances by multiple episodes of reheating and partial melting. Primary chondrule mineralogy thus reflects a dynamic stage of mineral evolution, when the diversity and distribution of natural condensed solids expanded significantly.
PNAS Nexus
The locations of minerals and mineral-forming environments, despite being of great scientific imp... more The locations of minerals and mineral-forming environments, despite being of great scientific importance and economic interest, are often difficult to predict due to the complex nature of natural systems. In this work, we embrace the complexity and inherent “messiness” of our planet's intertwined geological, chemical, and biological systems by employing machine learning to characterize patterns embedded in the multidimensionality of mineral occurrence and associations. These patterns are a product of, and therefore offer insight into, the Earth's dynamic evolutionary history. Mineral association analysis quantifies high-dimensional multicorrelations in mineral localities across the globe, enabling the identification of previously unknown mineral occurrences, as well as mineral assemblages and their associated paragenetic modes. In this study, we have predicted (i) the previously unknown mineral inventory of the Mars analogue site, Tecopa Basin, (ii) new locations of uranium ...
Part of Anirudh Prabhu PhD Dissertation. Contains the results of running the text to rule convers... more Part of Anirudh Prabhu PhD Dissertation. Contains the results of running the text to rule conversion workflow described in chapter 5 of the dissertation. The dataset preview and its description can be found in Appendix E of the dissertation document.
Encyclopedia of Big Data, 2022
Encyclopedia of Big Data, 2022
A machine learning barometer (using Random Forest Regression) to calculate equilibration pressure... more A machine learning barometer (using Random Forest Regression) to calculate equilibration pressure for majoritic garnets<br>Updated 04/02/21 (21/01/21) (10/12/20):<br>******<br><b>The barometer code</b><br>The barometer is provided as python scripts (.py) and Jupiter Notebooks (.ipynb) files. These are completely equivalent to one another and which is used depends on the users preference. Separate instructions are provided for each.<br>data files included in this repository are:<br> • "<b>Majorite_database_04022021.xlsm</b>" (Excel sheet of literature majoritic garnet compositions - inclusions (up to date as of 04/02/2021) and experiments (up to date as of 03/07/2020). This data includes all compositions that are close to majoritic, but some are borderline. Filtering as described in paper accompanying this barometer is performed in the python script prior to any data analysis or fitting)<br> • "<b>...