Evidence map›Paper›PMID 39391634›Full record

ArticleComputational and structural biotechnology journal2024

PEPR DIADEM: Priority equipment and research program on the development of innovative materials using artificial intelligence.

Fernando Lomello, Lucie Bard, Mario Maglione, Frédéric Schuster

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 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. Article
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

4 authors.

Fernando LomelloUniversité Paris-Saclay, CEA, DRF/IRFU/DIS, Gif-sur-Yvette 91191, France.
Lucie BardUniversité de Bordeaux, CNRS, Bordeaux INP, ICMCB, UMR 5026, Pessac F-33600, France.
Mario MaglioneUniversité de Bordeaux, CNRS, Bordeaux INP, ICMCB, UMR 5026, Pessac F-33600, France.
Frédéric SchusterUniversité Paris-Saclay, CEA, Cross-Cutting Program on Materials and Processes Skills, Gif-sur-Yvette 91191, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The quest to develop efficient, sustainable materials from non-critical, non-toxic resources is one of today's most formidable challenges in the current context of energy, transport, digital or healthcare transitions. In response, France launched the pioneering Priority Equipment and Research Program (PEPR) DIADEM in 2022. This innovative initiative, focused on DIscovery Acceleration for the Deployment of Emerging Materials (DIADEM), leverages Artificial Intelligence (AI) to accelerate the innovation chain from conception to realization, revolutionizing Materials Science sustainably. With a strategic emphasis on scientific synergy, PEPR DIADEM aims to expedite the discovery and development of novel materials essential for contemporary and future societal challenges. To achieve this, the program seeks to catalyze breakthroughs in areas ranging from energy efficiency to transportation, digitalization, and healthcare, covering a broad spectrum of materials from metallic alloys to functional nanostructures. Aligned with the Green Deal framework's ambitious targets, PEPR DIADEM addresses the urgent need for accelerated sustainable materials research. By utilizing cutting-edge technologies like rapid synthesis and characterization tools, automation, digital simulations, data management, AI, additive manufacturing, and thin film engineering, the program is set to significantly reshape the materials science landscape. As PEPR DIADEM embarks on its journey of innovation, it not only advances scientific knowledge but also holds the promise of addressing current global challenges and paving the way for a more sustainable and prosperous future.

Indexed as

Artificial Intelligence (AI)Data-driven materials scienceDigital simulationHigh-throughput synthesisMaterials discoverySustainable materials

Identifiers

PMID39391634
PMCPMC11464244

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.