Evidence map›Paper›PMID 39545104›Full record

ArticleACS sustainable chemistry & engineering2024

Advancing Rare-Earth (4

Logan J Augustine, Yufei Wang, Sara L Adelman, Enrique R Batista, Stosh A Kozimor, Danny Perez, Joshua Schrier, Ping Yang

Abstract read
In one paragraph

Article in ACS sustainable chemistry & engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Design biology and mind-body health.Journal, genetic engineering & biotechnology · 2025
    Review
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

8 authors.

Logan J AugustineTheoretical Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.ORCID https://orcid.org/0000-0002-0830-0820
Yufei WangChemistry Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.ORCID https://orcid.org/0000-0002-5780-112X
Sara L AdelmanChemistry Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.
Enrique R BatistaTheoretical Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.ORCID https://orcid.org/0000-0002-3074-4022
Stosh A KozimorChemistry Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.ORCID https://orcid.org/0000-0001-7387-0507
Danny PerezTheoretical Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.
Joshua SchrierDepartment of Chemistry & Biochemistry, Fordham University, The Bronx, New York 10458, United States.ORCID https://orcid.org/0000-0002-2071-1657
Ping YangTheoretical Division, Los Alamos National Lab, Los Alamos, New Mexico 87545, United States.ORCID https://orcid.org/0000-0003-4726-2860

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying improved and sustainable alternatives to "classic" separation techniques is an active research field due to its potential widespread impact in fundamental and applied chemistry. As basic purification methodologies, like liquid-liquid extraction, undergo continuous refinement by chemists and engineers, identifying new conditions that outperform existing techniques can be difficult. A major contributor to this challenging problem is the need to explore a vast experimental space to identify the precise conditions that optimize the separation procedure. The advent of artificial intelligence and the advancement of robotic technologies offer the potential to shift the traditional design paradigm. Toward that end, we applied a combination of Bayesian Optimization and high-throughput robotic experiments on the liquid-liquid extraction of thorium (Th

Identifiers

PMID39545104
PMCPMC11558677

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.