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Record W4296381338 · doi:10.1021/acssuschemeng.2c03159

A Systems Approach to Chemistry Is Required to Achieve Sustainable Transformation of Matter: The Case of Ammonia and Reactive Nitrogen

2022· article· en· W4296381338 on OpenAlexaff
J. Marc Whalen, Stephen A. Matlin, Thomas A. Holme, Jaclyn J. Stewart, Peter G. Mahaffy

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsThe King's UniversityUniversity of British ColumbiaDalhousie University
FundersInternational Union of Pure and Applied Chemistry
KeywordsReactive nitrogenChemistryNitrogenAmmoniaBiochemical engineeringEnvironmental chemistryNanotechnologyOrganic chemistryMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Chemistry has played a central role over the past century in the large-scale anthropogenic transformation of matter into diverse materials that have improved the quality of life for many people on our planet. The lens of chemistry is fundamentally necessary to understand the resulting flux of chemical substances in Earth system processes, the unintended consequences of those transformations, impacts on food supply security, water and energy concerns, ways to mediate and adapt to climate change, loss of biodiversity, and how best to build and maintain resilient ecosystems. Reactive nitrogen compounds (Nr) such as ammonia from the industrial fixation of atmospheric nitrogen exemplify both the central importance of chemistry in providing food and meeting basic human needs for a global population of 8 billion people and the sustainability challenges arising from the intended and unintended consequences of large-scale human production and release of Nr. The chemistry profession can use systems thinking (ST) tools and the Planetary Boundaries framework to understand and address challenges facing the entire Earth system resulting from the altered biogeochemical flows of nitrogen. This analysis has compelling priority due to the roles Nr currently plays in global food production and ammonia’s potential role as an energy carrier for large-scale human activities in a future low carbon economy and as a domestic refrigerant while hydrofluorocarbons (HFCs) are being phased out. As this example illustrates, navigating the complex benefits and challenges large-scale human activity imposes on Earth system processes requires the convergence of chemistry research, industrial practice, and education. Since the chemical reactions and processes that transform matter are foundational to sustainability challenges, this perspective maps, through a chemistry for sustainability pyramid, ‘multiple levels at which chemistry can contribute toward the emergence of sustainability of the Earth system’. We conclude with recommendations for steps the profession of chemistry can take to make education relevant and engaging and to connect chemistry research and practice to cross-disciplinary sustainability challenges, thereby transforming the science of transformation of matter toward sustainability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.016
Scholarly communication0.0070.010
Open science0.0010.004
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.170
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2022
Admission routes1
Has abstractyes

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