Nanomaterials

23 pages, 4799 KB

Open AccessArticle

A Three-Dimensional Interlocked Heterojunction Photoanode for Sustainable Metal Corrosion Control in Marine Environments

by Xiaoyan Liu, Chuchu Chen, Yumei Zhang, Xilong Liu, Xiurui Zhang and Leiying Han

Nanomaterials 2026, 16(11), 652; https://doi.org/10.3390/nano16110652 (registering DOI) - 22 May 2026

Abstract

The development of highly efficient and stable photoanodes is essential for advancing photoelectrochemical cathodic protection towards practical applications. Herein, a novel ternary sulfide heterojunction was engineered through the construction of a three-dimensional interlocked architecture of ZnIn₂S₄ on SnIn₄S [...] Read more.

The development of highly efficient and stable photoanodes is essential for advancing photoelectrochemical cathodic protection towards practical applications. Herein, a novel ternary sulfide heterojunction was engineered through the construction of a three-dimensional interlocked architecture of ZnIn₂S₄ on SnIn₄S₈ nanosheets via a sequential hydrothermal synthesis. This unique three-dimensional interlocked configuration creates an intimate interface and continuous charge transfer highways, effectively addressing the slow electron movement and poor interfacial contact that plague conventional photoelectrodes. Spectroscopic and electrochemical analyses verified the formation of a Type-II band alignment, which drives the directional migration of photogenerated electrons from ZnIn₂S₄ to SnIn₄S₈ under an intrinsic built-in electric field. Upon coupling with 304 stainless steel, the ZnIn₂S₄/SnIn₄S₃ heterojunction exhibited outstanding photoelectrochemical cathodic protection performance. It delivered impressive photocurrent densities of 15.22, 19.76, and 72.27 μA·cm⁻² in 3.5 wt% NaCl, 0.1 M Na₂S₂O₃, and 0.1 M Na₂S/NaOH electrolytes, respectively, along with a prominent 720 mV cathodic potential shift in the Na₂S/NaOH system. Most importantly, its good activity and stability in the scavenger-free 3.5 wt% NaCl solution and natural seawater highlight the strong practical potential of this 3D interlocked photoanode for sustainable marine metal corrosion control. Through a strategic multi-electrolyte assessment, the underlying protection mechanisms were decoupled, revealing that the synergy between the heterojunction-induced charge separation enabled by the three-dimensional interlocked structure and electrolyte-specific hole scavenging is key to the enhanced performance. Full article

(This article belongs to the Section Nanoelectronics, Nanosensors and Devices)

21 pages, 9662 KB

Open AccessArticle

Machine Learning Models for Predicting Key Performance Characteristics of High-Temperature THz Quantum Cascade Lasers

by Mihailo Stojković, Novak Stanojević, Aleksandar Milićević, Nikola Vuković, Dušan Topalović, Milan Ignjatović, Aleksandar Demić, Dragan Indjin and Jelena Radovanović

Nanomaterials 2026, 16(11), 651; https://doi.org/10.3390/nano16110651 (registering DOI) - 22 May 2026

Abstract

In this work, we applied Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN) to predict key performance characteristics of quantum cascade lasers (QCLs), including material gain, current density, and emission frequency. By developing a machine learning-based surrogate modeling framework [...] Read more.

In this work, we applied Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN) to predict key performance characteristics of quantum cascade lasers (QCLs), including material gain, current density, and emission frequency. By developing a machine learning-based surrogate modeling framework that replaces computationally expensive simulations of QCLs, we enable orders-of-magnitude-faster evaluation and optimization of a high-dimensional configuration space. The training dataset was generated using a numerical simulator based on the density-matrix transport model. By combining physics simulations with machine learning, we achieved reliable predictions of device characteristics, with standardized RMSE values ranging from 0.21 to 0.55 for RF, 0.16 to 0.51 for XGBoost, and 0.04 to 0.22 for the ANN model, demonstrating the superior predictive performance of the ANN across all investigated performance characteristics. The ANN was subsequently used to analyze the full configuration space defined by possible layer thicknesses and electric fields. Approximately 44 million configurations were evaluated in about five minutes, achieving a speedup of approximately 90,000 times over the numerical simulator for a single configuration. This approach allowed the identification of designs with improved material gain and facilitated the efficient optimization of key parameters while maintaining high prediction reliability. Full article

(This article belongs to the Special Issue TERA-MIR Photonics, Materials and Devices)

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42 pages, 4221 KB

Open AccessReview

Application of Machine Learning in Predicting the Properties of Two-Dimensional Semiconductor Materials

by Jia Yang, Lingli Tang, Yunlong Wang, Jie Wen and Wenyuan Chen

Nanomaterials 2026, 16(11), 650; https://doi.org/10.3390/nano16110650 - 22 May 2026

Abstract

The rapid evolution of next-generation electronics urgently demands high-performance functional materials. Two-dimensional (2D) semiconductors, characterized by tunable bandgaps, magnetic properties, and excellent optical and electronic properties, hold significant potential for applications in nanoelectronic devices, magnetic storage, and optoelectronics. However, the high computational cost [...] Read more.

The rapid evolution of next-generation electronics urgently demands high-performance functional materials. Two-dimensional (2D) semiconductors, characterized by tunable bandgaps, magnetic properties, and excellent optical and electronic properties, hold significant potential for applications in nanoelectronic devices, magnetic storage, and optoelectronics. However, the high computational cost of traditional Density Functional Theory (DFT) severely restricts large-scale high-throughput screening. Meanwhile, problems such as insufficient datasets and non-uniform data quality remain prevalent. Against this background, machine learning (ML), which captures intricate nonlinear correlations and accelerates the discovery of novel materials, has emerged as an efficient technical approach. This review systematically summarizes recent advances in ML-driven property prediction for 2D semiconductors. It first elaborates the fundamental properties and classifications of 2D semiconductors, and then compares traditional computational simulations with ML algorithms, clarifying the distinct advantages of data-driven approaches. Subsequently, this work focuses on the latest progress in predicting critical properties, including bandgap, magnetism, and other physical characteristics. For bandgap prediction, classical algorithms such as random forests are compared with deep learning models represented by graph neural networks. The results demonstrate that deep learning performs much better in low-data regimes and complex material systems. For magnetic property prediction, the impact of feature engineering strategies on model accuracy and efficiency is systematically analyzed. In addition, the research progress of other physical property prediction tasks is briefly summarized. Finally, future research directions for machine learning, including standardized materials databases, physics-informed machine learning, multimodal modeling, and the integration of machine learning with experimental and theoretical methods, are outlined to address challenges in data quality, model interpretability, and cross-system generalization ability. This work aims to provide a systematic theoretical foundation and methodological guidance for research on two-dimensional semiconductor materials assisted by machine learning. Full article

(This article belongs to the Section 2D and Carbon Nanomaterials)

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19 pages, 34548 KB

Open AccessArticle

Cs₂NaBi_0.6Er_0.4Cl₆ Double-Perovskite Nanoparticles for Hygroscopicity-Assisted Latent Fingerprint Development on Frosted Non-Porous Substrates

by Runkai Hu, Fang Zhou, Yue Zhou, Shangqi Feng, Ziyin Zhang, Yujing Zhao and Li Liu

Nanomaterials 2026, 16(11), 649; https://doi.org/10.3390/nano16110649 - 22 May 2026

Abstract

Latent fingerprint development on rough non-porous substrates using fingerprint powders remains challenging because surface microstructures reduce particle-adhesion selectivity and weaken the contrast between ridges and the background. In this study, Cs

_{2}

NaBi

_{0.6}

Er

_{0.4}

Cl

_{6}

double-perovskite [...] Read more.

Latent fingerprint development on rough non-porous substrates using fingerprint powders remains challenging because surface microstructures reduce particle-adhesion selectivity and weaken the contrast between ridges and the background. In this study, Cs

_{2}

NaBi

_{0.6}

Er

_{0.4}

Cl

_{6}

double-perovskite nanoparticles were prepared by a solvothermal method and investigated as fingerprint-development particles for latent fingerprints on frosted plastic substrates. Structural characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS) indicated that Er

^{3 +}

was incorporated into the host matrix and that the product consisted of spherical nanoparticles with smooth surfaces, relatively uniform particle-size distribution, and good dispersibility. Comparative experiments involving 40 categories of latent fingerprint samples showed that the Cs

_{2}

NaBi

_{0.6}

Er

_{0.4}

Cl

_{6}

nanoparticles outperformed conventional powders in developing fingerprints on frosted plastic substrates. Quantitative grayscale analysis using Image J 1.53K and Origin 2024 further showed that the development contrast, expressed as the D value, reached 51.21 for sebum-rich fingerprints and 35.87 for oil-contaminated model fingerprints, both of which were higher than those obtained with the other three powders. Because the fluorescence of Cs

_{2}

NaBi

_{0.6}

Er

_{0.4}

Cl

_{6}

under UV excitation was weaker than that of the commercial red fluorescent powder, we attribute the improved development performance mainly to selective adhesion of the particles to fingerprint residues rather than to fluorescence intensity alone. In addition, the material maintained good performance for aged fingerprints within 10 days and for developed fingerprints stored for up to 8 days. These results suggest that selective residue-affinitive adhesion, possibly assisted by the hydrophilic or moisture-affinitive nature of the ionic double-perovskite particles, plays an important role in improving fingerprint development on rough non-porous substrates. This study provides a physical perspective for latent fingerprint development on rough non-porous substrates and broadens the forensic-science application of lead-free double-perovskite nanomaterials. Full article

(This article belongs to the Section Synthesis, Interfaces and Nanostructures)

17 pages, 8754 KB

Open AccessArticle

Highly Transparent Phase Change Smart Windows Enabled by Refractive-Index-Matched n-Octadecane@SiO₂ Microcapsule Composites

by Fusen Yang, Zhixing Zhang, Yiyu Feng, Mengmeng Qin and Wei Feng

Nanomaterials 2026, 16(11), 648; https://doi.org/10.3390/nano16110648 - 22 May 2026

Abstract

The development of phase change materials (PCMs) for window applications with both high optical transparency and effective temperature regulation is crucial for passive energy saving. However, liquid leakage during phase transition and enhanced interfacial light scattering often cause fluctuations in optical transmittance and [...] Read more.

The development of phase change materials (PCMs) for window applications with both high optical transparency and effective temperature regulation is crucial for passive energy saving. However, liquid leakage during phase transition and enhanced interfacial light scattering often cause fluctuations in optical transmittance and deterioration of image clarity. To address these challenges, a highly transparent phase change composite was constructed via a microencapsulation strategy. Submicron core–shell microcapsules were fabricated using n-octadecane as the core and silica as the shell, enabling effective encapsulation of the liquid PCM component. The resulting microcapsules exhibited a high melting enthalpy of 155.3 J g⁻¹. They were subsequently homogeneously dispersed within a refractive-index-matched polymer matrix, mitigating light scattering during phase transition by reducing interfacial refractive index mismatch. The composite exhibited favorable thermal energy storage capability and transmittance performance, with a visible light transmittance of 83.75% and a transmittance fluctuation of only ~5% before and after phase transition. After 100 thermal cycles, the optical attenuation remained as low as 0.35%, demonstrating excellent cycling stability. This work provides a new strategy for balancing optical transparency and phase change function, with potential applications in smart windows and flexible electronics. Full article

(This article belongs to the Special Issue Advanced Polymer Nanocomposites for Thermal Management and Energy Storage)

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17 pages, 5337 KB

Open AccessArticle

First-Principles Investigation of Interfacial Bonding, Stability, and Electronic Properties at the Fe(111)/Ti₃SiC₂(0001) Interface

by Xiangdong Wang, Wentao Li, Zhiwen Peng, Xiaoyu Yang and Mingjie Wang

Nanomaterials 2026, 16(11), 647; https://doi.org/10.3390/nano16110647 - 22 May 2026

Abstract

A systematic first-principles density functional theory (DFT) study was performed using the Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA) functional combined with ultrasoft pseudopotentials (USPPs), as implemented in the CASTEP code. The PBE-GGA functional was chosen because it provides a well-balanced description of both [...] Read more.

A systematic first-principles density functional theory (DFT) study was performed using the Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA) functional combined with ultrasoft pseudopotentials (USPPs), as implemented in the CASTEP code. The PBE-GGA functional was chosen because it provides a well-balanced description of both metallic and covalent bonding characteristics at the Fe/Ti₃SiC₂ interface. To elucidate the interfacial bonding mechanisms and heterogeneous nucleation behavior of Ti₃SiC₂ particles in iron-based composites. The structural stability, work of adhesion, interfacial energy, and electronic properties of the Fe(111)/Ti₃SiC₂(0001) interface were comprehensively investigated. A total of eighteen interface models were constructed, encompassing six distinct Ti₃SiC₂(0001) terminations: C(TiC), C(TiSi), TiC(TiC), TiC(TiSi), TiSi, and Si, and three stacking sequences (OT, MT, and HCP). The results demonstrate that the C(TiC)-terminated interface with HCP stacking exhibits the highest work of adhesion (9.25 J·m⁻²) and the lowest interfacial energy, thus representing the most thermodynamically stable configuration. Analysis of the partial density of states (PDOS) and charge density difference reveals that this exceptional stability originates from strong covalent bonding between Fe 3d and C 2p orbitals at the interface, accompanied by pronounced charge accumulation in the interfacial region. Furthermore, the work of adhesion of this interface substantially exceeds that of the fcc-Fe/fcc-Fe melt interface, confirming the high potency of Ti₃SiC₂ particles as heterogeneous nucleation substrates for Fe grains. These findings provide an atomistic framework for understanding the enhanced nucleation and robust interfacial cohesion observed in Fe/Ti₃SiC₂ composite coatings, and offer theoretical guidance for the design of advanced iron-based MAX phase composites. Full article

(This article belongs to the Section Theory and Simulation of Nanostructures)

20 pages, 4844 KB

Open AccessArticle

Green Synthesis of Gold Nanoparticles with Good Photothermal Properties and Antibacterial Activity from Black Corncob Extract

by Yingwei Li, Fangsu Liu and Zhiguo Liu

Nanomaterials 2026, 16(11), 646; https://doi.org/10.3390/nano16110646 (registering DOI) - 22 May 2026

Abstract

Green synthesis of gold nanoparticles is an effective approach to create biocompatible nanomaterials. In this study, gold nanoparticles (BC-AuNPs) were prepared by reducing chloroauric acid with black corncob (BC) extract at relatively low temperatures. The optimal preparation conditions were obtained through a single-factor [...] Read more.

Green synthesis of gold nanoparticles is an effective approach to create biocompatible nanomaterials. In this study, gold nanoparticles (BC-AuNPs) were prepared by reducing chloroauric acid with black corncob (BC) extract at relatively low temperatures. The optimal preparation conditions were obtained through a single-factor experiment, which included 5 mL of black corncob extract and 0.12 mL of 3% HAuCl₄ solution at a pH of 5.0, and the reaction was carried out at 50 °C in a water bath for 3 h. The prepared BC-AuNPs were characterized by ultraviolet–visible (UV-Vis) spectroscopy, Fourier-transform infrared (FTIR) analysis, transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), dynamic light scattering (DLS), and Zeta-potential measurement, which showed that they were dispersed spherical particles with an average size of approximately 23.0 nm and their surfaces were covered with various black corncob active components. The photothermal performance test indicated a good photothermal effect with a conversion efficiency of 41.3%. Antibacterial experiments revealed that BC-AuNPs had excellent antibacterial activity. The minimum inhibitory concentrations (MICs) for E. coli and Salmonella were 25.00 and 50.00 µg/mL, respectively. Overall, this study proved a potential application for gold nanoparticles in photothermal antibacterial fields. Full article

(This article belongs to the Section Synthesis, Interfaces and Nanostructures)

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58 pages, 4701 KB

Open AccessReview

Magnetic Cellulose Nanocrystal Composites: Synthesis, Properties, Applications, and Opportunities

by Mohammad Jahid Hasan, Kishore Chand, Esteban E. Ureña-Benavides and Erick S. Vasquez-Guardado

Nanomaterials 2026, 16(11), 645; https://doi.org/10.3390/nano16110645 - 22 May 2026

Abstract

Cellulose nanocrystals (CNCs) are abundant, renewable, biodegradable, non-toxic, and cost-effective nanomaterials with exceptional properties, making them highly appealing for nanocomposite material fabrication. Recognized for their sustainability, CNCs are emerging as promising substrates for the fabrication of functional, stimuli-responsive nanomaterials. This review highlights nanocomposites [...] Read more.

Cellulose nanocrystals (CNCs) are abundant, renewable, biodegradable, non-toxic, and cost-effective nanomaterials with exceptional properties, making them highly appealing for nanocomposite material fabrication. Recognized for their sustainability, CNCs are emerging as promising substrates for the fabrication of functional, stimuli-responsive nanomaterials. This review highlights nanocomposites comprising magnetic nanoparticles with various forms of cellulose-based materials, with a primary focus on magnetic cellulose nanocrystal (MCNC) composites, yielding materials capable of controlled, on-demand responses to external magnetic fields. The magnetic properties of these nanocomposites can be precisely tuned by adjusting the magnetic nanoparticle content on CNC surfaces. At the nanoscale, magnetic CNCs exhibit remarkable properties, including facile and rapid magnetic separation, which holds great potential for numerous applications. This review examines the latest synthesis and modification methods for CNCs functionalized with various magnetic nanoparticles, as well as their applications in the biological, packaging, environmental, and biomedical fields. Full article

(This article belongs to the Special Issue Progress in Magnetic Nanoparticles: From Synthesis to Applications)

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10 pages, 2400 KB

Open AccessArticle

Boosting the Performance of Visible/Near-Infrared Organic Photodetectors via Hole Interface Engineering

by Yijing Fan, Junquan Luo, Lan Liu, Qiao He, Jiahui Lu, Zhimin Shao, Zhensheng Xu, Zhe Liu, Yun Xia, Xuanye Li and Lintao Hou

Nanomaterials 2026, 16(11), 644; https://doi.org/10.3390/nano16110644 - 22 May 2026

Abstract

When poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is employed as the hole transport layer in visible/near-infrared photodetectors, the extraction and transport of holes are hindered by the accumulation of the PSS insulating phase at the interface. This accumulation results in an increase in contact resistance [...] Read more.

When poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is employed as the hole transport layer in visible/near-infrared photodetectors, the extraction and transport of holes are hindered by the accumulation of the PSS insulating phase at the interface. This accumulation results in an increase in contact resistance and creates a potential barrier for hole injection. This study introduces a self-assembled monolayer, (2-(9H-carbazol-9-yl)ethyl)phosphonic acid (2PACz), to modify PEDOT:PSS, effectively optimizing the interface of the hole transport layer. Such improvements lead to a reduction in recombination losses during charge transfer, a lower dark current, and improved energy level alignment in the device, thereby boosting the performance of visible/near-infrared photodetectors. The fabricated double hole layer photodetector exhibits a low dark current of (1.4 ± 0.6) × 10⁻⁵ A at −1 V bias and a switching ratio of up to 7.62 × 10⁵ at 0 V bias. The device achieves a responsivity of 0.31 A/W and a high specific detection rate of 3.23 × 10¹² Jones at a wavelength of 780 nm, which corresponds to the peak responsivity, showcasing enhanced detection capabilities. In comparison to a reference device based on PEDOT:PSS, the response speed, cutoff frequency, and linear dynamic range of the double hole layer device have been enhanced by 400%, 213%, and 81%, respectively, thereby better aligning with practical application requirements. This research presents a novel approach for the development of high-performance organic visible/near-infrared photodetectors. Full article

(This article belongs to the Section Nanophotonics Materials and Devices)

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16 pages, 10272 KB

Open AccessArticle

Nanoscale Phase Evolution, Substitution Mechanism, and Aqueous Durability of CaZr_1−xGd_xTi_2−xNb_xO₇ (x = 0.1–1.0) Defect-Fluorite-Derived Ceramics

by Baolong Ma, Shixi Chen, Shiyin Ji, Chuanhang Zhao and Tian Chen

Nanomaterials 2026, 16(11), 643; https://doi.org/10.3390/nano16110643 - 22 May 2026

Abstract

The safe immobilization of high-level waste (as actinide) remains a critical bottleneck in the disposal of high-level radioactive waste worldwide. Moreover, the higher specific surface area and surface energy of nano-scale powders enable the production of ceramic materials featuring denser crystal structures and [...] Read more.

The safe immobilization of high-level waste (as actinide) remains a critical bottleneck in the disposal of high-level radioactive waste worldwide. Moreover, the higher specific surface area and surface energy of nano-scale powders enable the production of ceramic materials featuring denser crystal structures and superior strength, hardness, and toughness. Therefore, in this study, Gd³⁺ was used as a surrogate for actinides, and Nb⁵⁺ was introduced as a high-valence charge-compensating cation. Nano-scale powders of CaCO₃, ZrO₂, Gd₂O₃, TiO₂, and Nb₂O₅ were employed to prepare a series of defect-fluorite-derived ceramics, CaZr_1-xGd_xTi_2-xNb_xO₇ (x = 0.1–1.0), via a high-temperature solid-state reaction method, aiming to investigate the atomic substitution mechanisms, phase evolution, and chemical stability under high-valence charge compensation. Laboratory X-ray diffraction (XRD), synchrotron X-ray diffraction (SXRD), and backscattered scanning electron microscopy with energy-dispersive X-ray spectroscopy (BSEM-EDX) confirmed a phase evolution sequence from zirconolite-2M to zirconolite-4M and finally to pyrochlore. This behavior is consistent with that reported for other Ln³⁺-Nb⁵⁺ co-doped zirconolite systems. Rietveld refinement of the SXRD data further revealed, for the first time, the site-occupancy mechanism of Gd and Nb in zirconolite-4M. In both zirconolite-2M and zirconolite-4M, Gd preferentially occupies the Ca sites, whereas Nb substitutes at the Ti sites. In the pyrochlore structure, Ca, Zr, and Gd occupy the 16d sites, while Ti and Nb occupy the 16c sites. Static leaching tests following the MCC-1 protocol showed that pyrochlore exhibits the highest leaching resistance, whereas zirconolite-2M shows the lowest. After 28 days, the highest Gd leaching rate was 1.92(1) × 10⁻⁵ g m⁻² d⁻¹. These results provide new insights into actinide immobilization behavior and compositional design in zirconolite-based waste forms. Full article

(This article belongs to the Special Issue Multiscale Modeling and Characterization Techniques of Advanced Nanostructured Materials for Extreme Service, 2nd Edition)

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24 pages, 968 KB

Open AccessReview

Use of Micro/Nanorobots In Vivo for the Eradication of Bacterial Biofilm: A Review of Challenges and Strategies

by Ondrej Musil and Karel Klíma

Nanomaterials 2026, 16(11), 642; https://doi.org/10.3390/nano16110642 - 22 May 2026

Abstract

The term bacterial biofilm refers to a complex community of microorganisms embedded within a self-produced matrix of extracellular polymeric substances. This structural organization creates an environment that, when present in an infectious context within a living organism, limits the effectiveness of conventional antibiotic [...] Read more.

The term bacterial biofilm refers to a complex community of microorganisms embedded within a self-produced matrix of extracellular polymeric substances. This structural organization creates an environment that, when present in an infectious context within a living organism, limits the effectiveness of conventional antibiotic therapy. Consequently, such conditions substantially promote the development of antibiotic resistance. The decline in the discovery of novel antibiotic agents, coupled with a concurrent increase in the prevalence of multidrug-resistant microorganisms, has intensified the search for alternative strategies to combat such infections. At the same time, advances in nanoscience have stimulated substantial research into the use of micro/nanorobots for the eradication of bacterial biofilms. These devices, engineered at the micro- to nanoscale, are capable of targeted intervention in otherwise inaccessible sites. However, the development of such “microscopic therapeutic agents” is still at an early stage. To date, the vast majority of available data has been derived from in vitro studies, while evidence regarding their feasibility, safety, and therapeutic effects in living organisms remains limited. This review discusses their antimicrobial mechanisms and critically evaluates the current evidence concerning their in vivo applications. Full article

(This article belongs to the Section Biology and Medicines)

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2 pages, 140 KB

Open AccessCorrection

Correction: Barani et al. Nanomaterials in the Management of Gram-Negative Bacterial Infections. Nanomaterials 2021, 11, 2535

by Mahmood Barani, Mahira Zeeshan, Davood Kalantar-Neyestanaki, Muhammad Asim Farooq, Abbas Rahdar, Niraj Kumar Jha, Saman Sargazi, Piyush Kumar Gupta and Vijay Kumar Thakur

Nanomaterials 2026, 16(11), 641; https://doi.org/10.3390/nano16110641 - 22 May 2026

Abstract

In the original publication [...] Full article

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Nanomaterials, Volume 16, Issue 11 (June-1 2026) – 12 articles

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