Evidence map›Paper›PMID 41012398›Full record

ReviewToxics2025

Review of Health Hazards in High-Entropy Alloy Processing Under Laboratory Conditions and Risk Assessment Using a Simple Risk Scoring Model.

Sheetal Kumar Dewangan

Abstract readReview
In one paragraph

Review in Toxics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

1 author.

Sheetal Kumar DewanganDepartment of Materials Science and Engineering, Ajou University, Suwon 16499, Republic of Korea.ORCID 0000-0002-9856-6488

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Certain metal powders used in the synthesis and processing of high-entropy alloys (HEAs) pose significant health hazards, as many of these metals are toxic substances with no biological role in the human body. These metals can mimic essential elements or interfere with metabolic processes (the chemical reactions in living organisms that sustain life), leading to detrimental health effects. While some metals, such as aluminum, can be eliminated from the body through natural biological processes, others tend to accumulate, causing chronic illnesses over time. This review examines the toxicity mechanisms and health impacts of metals used in HEA synthesis, focusing on laboratory-scale processing. It also identifies potential health risks associated with occupational exposure in laboratory environments, including the inhalation of toxic metal powders and nanoparticles. A simple risk scoring model is introduced to systematically assess and quantify these risks based on factors such as toxicity levels, exposure limits, and carcinogenic potential (the ability of a substance to cause cancer) as given by the Occupational Safety and Health Administration (OSHA) and the National Institute for Occupational Safety and Health (NIOSH) standards. The proposed model can be applied to evaluate the relative hazards of commonly used HEA constituent powders (e.g., Ni, Co, Cr, and Al), offering practical guidance for safer laboratory handling and material selection. By integrating this risk assessment framework, this review aims to enhance workplace safety, guide the development of better material handling practices, and assist researchers in mitigating health risks associated with HEA processing.

Indexed as

health hazardhigh-entropy alloymetal powder processingpowder metallurgyrisk scoring model

Identifiers

PMID41012398
PMCPMC12474114

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.