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Article

30 June 2026

High Temperature Fatigue Crack Growth Kinetics of a High Performance Ferritic (HiperFer) Steel

The fatigue crack propagation behavior of an experimental fully ferritic high-chromium steel HiperFer 17Cr2 was investigated at elevated temperatures of 650 °C and 675 °C at loading frequencies of 20, 5, and 0.05 Hz, motivated by the demand for advanced high-temperature materials capable of improving the thermodynamic efficiency of future thermal energy conversion systems and reducing greenhouse gas emissions. The widely used 9Cr-1Mo-V-Nb ferritic-martensitic steel P91 was examined in parallel at 650 °C for benchmarking purposes. Complementary microstructural analyses were performed to characterize frequency- and temperature-dependent damage mechanisms. At 650 °C, the stress intensity required for the initiation of crack propagation was substantially higher in HiperFer 17Cr2 than in P91 across all tested frequencies. Furthermore, crack growth rates were up to half an order of magnitude lower in HiperFer 17Cr2. At 675 °C, frequency-dependent damage mechanisms were identified, including dynamic recovery, subgrain formation, and pipe diffusion-assisted redistribution of Cr and Nb, promoting formation of the metastable C14 Cr2Nb Laves phase at grain and sub-grain boundaries. These precipitates effectively impeded crack progression, while crack-tip blunting reduced the local driving force for crack propagation. The results indicate that HiperFer 17Cr2 is suitable for continuous service at 675 °C under high-cycle fatigue conditions in the frequency range from 5 to 20 Hz.

Keywords: HiperFer; 9–12% Cr steel; Fatigue crack growth; Laves phase; Microstructural mechanisms
High-Temp. Mater.
2026,
3
(3), 10013; 
Open Access

Article

30 June 2026

Recombinant AnAFP Reveals Genetic Contributors to Antifungal Protein Tolerance and Fungal Development in Aspergillus flavus

Aspergillus flavus is an agriculturally important and aflatoxigenic fungus, underscoring the need for alternative antifungal strategies. Cysteine-rich antifungal proteins (AFPs) are promising bioactive molecules, yet their recombinant production and genetic determinants of fungal tolerance remain insufficiently characterized. Here, we investigated AnAFP, an antifungal protein from Aspergillus niger, and evaluated its activity against A. flavus. Bioinformatic analyses predicted an N-terminal signal peptide, a putative intrinsically disordered region, and a mature cysteine-rich domain structurally related to known fungal AFPs. Guided by these features, the predicted mature region of AnAFP was expressed in Escherichia coli and purified through Ni-NTA affinity chromatography, tag cleavage, cation-exchange chromatography, and size-exclusion chromatography. Purified AnAFP inhibited A. flavus growth, and comparison with PgAFP and AfAFP confirmed antifungal activity at micromolar concentrations. To identify genes associated with AFP tolerance, Δado1, Δdef1, and Δadk1 mutants were generated by homologous recombination. All three mutants showed increased sensitivity to AnAFP, PgAFP, and AfAFP relative to the wild-type strain, suggesting that ado1, def1, and adk1 may contribute to AFP tolerance. Deletion of these genes also affected colony growth, conidiation, sclerotial formation, stress responses, and aflatoxin production. These findings establish a recombinant production strategy for AnAFP and provide preliminary evidence linking ado1, def1, and adk1 to AFP sensitivity and fungal physiology more broadly in this pathogenic and aflatoxigenic species.

Keywords: Aspergillus flavus; AnAFP; Antifungal protein; Aflatoxin B1
Fungal Res.
2026,
1
(1), 10004; 
Open Access

Communication

30 June 2026

Lactononadecapeptide Upregulates Gene Expression of Neuroplasticity and Cholinergic Activation in Human iPSC-Derived Neurons

To clarify the underlying molecular mechanisms of lactononadecapeptide (LNDP), we examined its effects on the gene expression of memory-related neuroplasticity and cholinergic signaling in human induced pluripotent stem cell (hiPSC)-derived neurons, alongside a safety evaluation using PC12 cells. LNDP showed no cytotoxicity and significantly upregulated the expression of genes crucial for neuroplasticity (BDNF, TrkB, NGF) and cholinergic signaling (ChAT, CHRM1, NMDAR NR1) in hiPSC-derived neurons. These findings suggest that LNDP potentially modulates transcriptional pathways related to neural health, supporting its potential value as a functional food ingredient for cognitive decline.

Keywords: Lactononadecapeptide; Human iPSC-derived neurons; Memory; Gene expression
Food Res. Suppl.
2026,
1
(2), 10009; 
Open Access

Article

30 June 2026

Navigating Urban Deprivation in Nigeria: Evidence from Lagos-Ogun Border Conurbation and Implications for Ecological Civilization

Understanding how residents experience living conditions is essential for reducing inequality and advancing more sustainable cities. This study assessed multidimensional urban deprivation in border settlements forming the Lagos–Ogun conurbation, with the aim of generating evidence to improve living conditions and service delivery in the study area. Systematic sampling was used to select eligible respondents (n = 325). Residents rated the importance of, and satisfaction with, key settlement attributes, from which the Residents’ Importance Attached Index (RIAI) and Residents’ Satisfaction Derived Index (RSDI) were computed. Facility conditions were assessed using a Facility Condition Index (FCI). Findings show pronounced gaps between what residents consider important and what they experience in practice across physical, social, and economic domains, indicating multidimensional deprivation in both states’ border settlements. Facility condition ratings further indicate that many basic services and public facilities are in poor condition, reinforcing deprivation. The paper recommends a coordinated Lagos–Ogun border service strategy that prioritizes rehabilitation and maintenance of critical infrastructure, strengthens development control and service accountability across jurisdictions, and leverages well-regulated public–private partnerships to expand and sustain service provision.

Keywords: Urban deprivation; Border settlements; Neighbourhood; Facilities; Ecological civilization; Lagos-Ogun conurbation
Ecol. Civiliz.
2026,
3
(3), 10015; 
Open Access

Article

30 June 2026

A Study on Site Selection and Capacity Allocation of a Four-Energy Complementary Power Generation System in the Zhoushan Archipelago Based on the Analytic Hierarchy Process

Marine renewable energy (MRE) is a vital component of emerging energy systems, playing a key role in the low-carbon transition and enhancing energy self-sufficiency in coastal regions. The Zhoushan Archipelago possesses favorable conditions for wind, wave, tidal-current, and solar energy, providing a resource foundation for multi-energy complementary systems. However, due to resource intermittency, spatiotemporal heterogeneity, and marine-use constraints, single MRE sources cannot independently ensure the long-term stable power supply required for isolated island grids. This study develops a comprehensive decision-making framework for wind-wave-tidal-solar integration by combining logical veto screening, the Analytic Hierarchy Process (AHP), and capacity allocation optimization. First, a multi-level evaluation system is established across resource, natural-engineering, socio-economic, and environmental dimensions, utilizing exclusionary factors—such as nature reserves, cultural heritage, and existing marine engineering—as preliminary veto criteria. Second, a “four-energy complementarity–synergy index” is introduced to characterize temporal availability, ensuring that site selection accounts for the contribution of multi-energy combinations to supply stability. Third, AHP is applied to determine weights and rank candidate sites, while a minimum-variance model optimizes capacity ratios for preferred locations. Furthermore, the TOPSIS method is introduced as an alternative multi-criteria decision-making approach for comparative analysis, to test the sensitivity of the ranking results to the choice of evaluation method. Based on the shortlisted priority candidate sites, a minimum variance capacity allocation model is established to analyse the synergy relationships between different energy types. Results indicate that multi-criteria evaluation effectively reveals suitability differences that single-resource metrics miss. Additionally, optimized capacity allocation significantly reduces combined-output fluctuations and enhances supply stability. The proposed framework is structured, verifiable, and adaptable, providing a methodological reference for the siting and preliminary capacity planning of multi-energy offshore power stations.

Keywords: Marine renewable energy; Multi-energy complementary power generation systems; Site selection evaluation; Analytic hierarchy process; Capacity allocation; Logical veto; Zhoushan Archipelago
Mar. Energy Res.
2026,
3
(3), 10013; 
Open Access

Communication

29 June 2026

Machine Learning Enabled Smart Structural Materials Using Additive Manufacturing

This research study describes a machine learning (ML)-driven model for producing smart structural materials via additive manufacturing (AM) by extrusion. A 3D concrete printing system was used to make cementitious composites that were reinforced with carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs). Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN) models were used to undergo supervised learning on an experimental dataset consisting of 320 specimens to predict compressive strength, electrical conductivity, and print quality as dependent on process parameters and material composition. The highest R2 of compressive strength prediction of SVM was 0.946, whereas RF had the highest R2 of 0.987, which was used to predict electrical conductivity. Optimization of parameters guided by ML had a 61.8% enhancement of compressive strength and 30.5 times increase in electrical conductivity in comparison to non-optimized baselines. Nanomaterial networks were also found to be conductive, allowing individual networks to detect their strain levels through changes in current at a strain of 0.1%, which facilitates real-time structural health sensing. The artificial system showed a 31% decrease in CO2 emissions and a 58.8% decrease in material wastage compared with the usual way of building, proving to be a valid route towards intelligent and sustainable infrastructure.

Keywords: Machine learning; Additive manufacturing; Smart structural materials; Sustainable infrastructure; Structural health monitoring
Intell. Sustain. Manuf.
2026,
3
(2), 10015; 
Open Access

Article

29 June 2026

Sustainable Lignin-Epoxy Compatibilizer Enables Synergistic Strengthening and Toughening in PBAT/PLA Blends

Poly(butylene adipate-co-terephthalate) (PBAT) is a promising biodegradable polyester, but its low strength limits broader application. In principle, blending PBAT with polylactide (PLA) can combine toughness and stiffness, yet severe immiscibility usually leads to poor interfacial adhesion and unsatisfactory overall performance. Here, a bio-based lignin-epoxy composite compatibilizer (E-FL) was developed by premixing ethanol-fractionated lignin (FL) with a protocatechuic-acid-derived epoxy compound and introducing it into PBAT/PLA blends through reactive melt processing. Fractionation enriched lignin fractions with lower molecular weight and higher hydroxyl content, thereby improving reactivity and dispersibility. During melt blending, E-FL promoted interfacial reactions with PBAT and PLA end groups, increased melt torque and molecular weight, refined the dispersed PLA domains, and reduced the Tg gap between the two phases. At an E-FL loading of 3 wt%, the blend exhibited the best balance of performance, with a tensile strength of 36.1 MPa, an elongation at break of 1035%, and a fracture toughness of 238.3 MJ/m3. This work provides a sustainable strategy for converting lignin into a high-efficiency reactive compatibilizer and offers a practical route to high-performance PBAT-based biodegradable blends.

Keywords: Poly(butylene adipate-co-terephthalate); Polylactide (PLA); Lignin; Bio-based epoxy; Strengthening-toughening synergy
Sustain. Polym. Energy
2026,
4
(3), 10011; 
Open Access

Review

29 June 2026

Advances in Gastrodin Production: From Native to Engineered Biosynthesis

Gastrodin is a phenolic glycoside and the principal bioactive compound of Gastrodia elata. Owing to its potent neuroprotective, antioxidant, and therapeutic properties, gastrodin has attracted increasing attention and is now widely applied in the pharmaceutical, healthcare, and food industries. Traditional extraction of gastrodin is constrained by limited raw material availability and low yield, making it insufficient to meet the growing market demand. In recent years, microbial biosynthesis has become a preferred route for gastrodin production due to its sustainability, economic feasibility, and high safety. Therefore, developing metabolically engineered strains with enhanced genetic stability, high productivity, and efficient substrate utilization has become an urgent priority for achieving gastrodin biosynthesis. This review introduces the discovery and biosynthetic routes of gastrodin, summarizes its production methods, and discusses recent advances across various microbial chassis systems. It further highlights recent advances in pathway reconstruction and metabolic optimization, with an emphasis on strategies to enhance precursor flux, optimize UDP-glucose biosynthesis and regeneration, and improve glycosyltransferase catalytic activity through protein engineering. Overall, this review provides insights and future directions for developing efficient, genetically stable, and industrially scalable microbial cell factories for sustainable gastrodin production.

Keywords: Gastrodia elata; Gastrodin; Metabolic engineering; Biosynthetic pathway; Engineered strains
Synth. Biol. Eng.
2026,
4
(2), 10009; 
Open Access

Review

29 June 2026

Development of Novel 20Cr Ferritic Stainless Steels via Nanoscale G-Phase Dispersion Strengthening: A Brief Review

Extensive investigations have revealed the precipitation of nanometer-scale silicides, identified as G-phase, within the ferritic matrix of duplex stainless steels during prolonged thermal aging. These silicides typically exhibit a well-defined coherent orientation relationship with the ferrite matrix, specifically (100G//100F, 110G//110F, 111G//111F). Consequently, the authors and their research team proposed a novel concept in 2015: utilizing the G-phase as a primary strengthening phase. It was proposed that through strategic alloy design, these silicides—ordinarily considered deleterious in duplex stainless steels—could be used to develop a new generation of dispersion-strengthened ferritic stainless steels. This approach aims to significantly enhance the yield strength of the alloy while maintaining excellent tensile ductility. Over the past decade, the authors and their research team have focused on nanoscale G-phase dispersion-strengthened ferritic stainless steels. By combining first-principles calculations with thermodynamic database-driven alloy design, a series of new ferritic stainless steel systems based on G-phase strengthening has been developed. These efforts have yielded extensive fundamental results regarding the compositional control, microstructural design, and mechanical properties of silicide-strengthened 20Cr ferritic stainless steels. Based on a comprehensive review of the existing literature, this paper further summarizes the compositional design criteria and microstructural control strategies for G-phase strengthened steels. It is hoped that this work will encourage further fundamental research and industrial applications in this field.

Keywords: Silicide G-phase; Ferritic stainless steels; Precipitation strengthening; Strength-ductility synergy
High-Temp. Mater.
2026,
3
(2), 10012; 
Open Access

Communication

29 June 2026

Post-COVID SARS-CoV-2 Antigen Persistence: A Critical Review of Mass Spectrometry Methodology and the Confound of Vaccine-Derived Antigens

Persistent SARS-CoV-2 antigen has been proposed as a driver of post-COVID condition (PCC), with targeted mass spectrometry multiple reaction monitorin/selected reaction monitoring (MRM/SRM) increasingly invoked as quantitative evidence. We appraise the targeted-MS literature on SARS-CoV-2 antigen in genuine human clinical specimens and re-analyse a focal study, which reported spike and nucleocapsid “protein” concentrations in ng/µL from two proteotypic peptides per target with 13C/15N internal standards. These values are either physically impossible as intact protein or, more likely, raw peptide concentrations reported without the required ≈122-fold molecular-weight correction. Only 15 of 65 patients (26%) had cellular pellet spike above the authors’ own limit of quantification; nucleocapsid was essentially undetectable; and in those 15, the nucleocapsid: spike molar ratio was strongly inverted relative to intact virions, incompatible with a viral source. Critically, no targeted-MS method has ever quantified spike in human blood—the prior literature is nucleocapsid detection in respiratory specimens and spike quantification in vaccine or recombinant material—so the reported blood-spike values lack any validated precedent and exceed the most sensitive validated platform (single-molecule arrays) by several orders of magnitude, with no enrichment step. Finally, 77% of the cohort was vaccinated, and a measurable spike was concentrated among vaccinated individuals. The source’s own supplement inconsistently reports vaccination status. Their 2024 predecessor publication withheld it entirely. The MRM/SRM data, therefore, do not support persistent viral antigen as a general driver of PCC. Minimum standards are proposed: molar reporting, strict limit-of-quantification (LOQ) compliance, qualifier-ion confirmation, vaccine-discrimination peptides, stoichiometric cross-validation, and vaccination-status disclosure. We suggest that the cellular blood component, routinely discarded, warrants direct investigation in the context of spike persistence and PCC symptoms.

Keywords: Post-COVID condition; SARS-CoV-2 antigen persistence; Long COVID biomarkers; Targeted mass spectrometry; MRM/SRM; Spike protein quantification; Nucleocapsid protein detection; Quantitative proteomics
Immune Discov.
2026,
2
(2), 10005; 
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