Evidence map›Paper›PMID 40097579›Full record

ArticleCommunications engineering2025

Sewage sludge hydrochar characterization and valorization via hydrothermal processing for 3D printing.

Sabrina C Shen, Branden Spitzer, Damian Stefaniuk, Shengfei Zhou, Admir Masic, Markus J Buehler

Abstract read
In one paragraph

Article in Communications engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Sabrina C ShenLaboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, Cambridge, MA, USA.
Branden SpitzerLaboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, Cambridge, MA, USA.
Damian StefaniukDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Shengfei ZhouLaboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-2144-2567
Admir MasicDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Markus J BuehlerLaboratory for Atomistic and Molecular Mechanics (LAMM), Massachusetts Institute of Technology, Cambridge, MA, USA. mbuehler@mit.edu.ORCID http://orcid.org/0000-0002-4173-9659

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sewage sludge, a biosolid product of wastewater processing, is an often-overlooked source of rich organic waste. Hydrothermal processing has shown promise in converting sewage sludge into valorized materials with potential application in biofuels, asphalt binders, and bioplastics. Here we characterize the physicochemical properties of hydrochar, the carbonaceous solid phase product of hydrothermal processing, and investigate its use as bio-based filler in additive manufacturing. We find that the presence of metallic and metalloid dopants in sewage sludge, which are not typically found in biomass wastes, yields unusual results in organic material processing such as decreased graphitic ordering after thermal activation. We further find that addition of hydrochar generally decreases mechanical performance of additive manufacturing composites, however, some properties such as toughness can be recovered with nature-inspired architecting into gyroid microstructures. These findings demonstrate that more investigation is required to optimally valorize sewage sludge and similarly disordered waste streams.

Identifiers

PMID40097579
PMCPMC11914255

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Registered trials

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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.