Targeting the vector of arboviruses Aedes aegypti with nanoemulsions based on essential oils: a review with focus on larvicidal and repellent properties

• Laryssa Ferreira do Nascimento Silva,
• Douglas Dourado,
• Thayse Silva Medeiros,
• Mariana Alice Gonzaga Gabú,
• Maria Cecilia Queiroga dos Santos,
• Daiane Rodrigues dos Santos,
• Mylena Lemos dos Santos,
• Gabriel Bezerra Faierstein,
• Rosângela Maria Rodrigues Barbosa and
• Fabio Rocha Formiga

Beilstein J. Nanotechnol. 2025, 16, 1894–1913, doi:10.3762/bjnano.16.132

Beyond the bilayer: multilayered hygroscopic actuation in pine cone scales

• Kim Ulrich,
• Max David Mylo,
• Tom Masselter,
• Fabian Scheckenbach,
• Sophia Fischerbauer,
• Martin Nopens,
• Silja Flenner,
• Imke Greving,
• Linnea Hesse and
• Thomas Speck

Beilstein J. Nanotechnol. 2025, 16, 1695–1710, doi:10.3762/bjnano.16.119

• more apical (right) based on the original position along the central cone axis. (C) Single frame of the first scale row during the automated point tracking for calculating the bending angle. Geometries used for finite element analysis. (A) Bilayer. (B) Trilayer. (C) Trilayer with uniform fibers. (D

Nanotechnology-based approaches for the removal of microplastics from wastewater: a comprehensive review

• Nayanathara O Sanjeev,
• Manjunath Singanodi Vallabha and
• Rebekah Rubidha Lisha Rabi

Beilstein J. Nanotechnol. 2025, 16, 1607–1632, doi:10.3762/bjnano.16.114

• evaluation. Current sampling and pre-processing methods face limitations such as complexity, inconsistent outputs, and time inefficiency, which intelligent sampling tools and cloud-based platforms aim to overcome through real-time optimization. Automated systems will enhance reagent selection and streamline

Automated collection and categorisation of STM images and STS spectra with and without machine learning

• Dylan Stewart Barker and
• Adam Sweetman

Beilstein J. Nanotechnol. 2025, 16, 1367–1379, doi:10.3762/bjnano.16.99

• datasets to implement on new systems and demonstrate a proof-of-principle automated experiment that is able to repeatedly prepare the tip, identify molecules of interest, and perform site-specific STS experiments using DM, in order to produce large numbers of spectra with different tips suitable for

• statistical analysis. Deterministic methods can be easily implemented to classify the imaging and spectroscopic quality of a STM tip for the purposes of high-resolution STM and STS on small organic molecules. Via automated classification of the tip state, we demonstrate an automated experiment that can

• collect a high number of spectra on multiple molecules without human intervention. The technique can be easily extended to most metal–adsorbate systems and is promising for the development of automated, high-throughput, STM characterisation of small adsorbate systems. Keywords: automated; machine

Deep-learning recognition and tracking of individual nanotubes in low-contrast microscopy videos

• Vladimir Pimonov,
• Said Tahir and
• Vincent Jourdain

Beilstein J. Nanotechnol. 2025, 16, 1316–1324, doi:10.3762/bjnano.16.96

• developing an automated deep learning (DL) approach. A Mask-RCNN architecture, enhanced with a ResNet-FPN backbone, was employed to recognize and track individual nanotubes in microscopy videos, significantly improving the efficiency and reproducibility of kinetic data extraction. The method involves a

• , while panel (b) includes nanotubes with varying growth rates. Green dots represent data obtained using the automated recognition system (AI), and grey dots correspond to manual measurements (MR). Large dots indicate the mean values of each distribution, with whiskers representing one standard deviation

Soft materials nanoarchitectonics: liquid crystals, polymers, gels, biomaterials, and others

• Katsuhiko Ariga

Beilstein J. Nanotechnol. 2025, 16, 1025–1067, doi:10.3762/bjnano.16.77

• on/off response of the fabricated structures is length-dependent. For example, the switching current under light illumination increases with increasing molecular length and monolayer thickness. Furthermore, the technique has the potential to be automated, which would facilitate its use as an assembly

Focused ion and electron beams for synthesis and characterization of nanomaterials

• Aleksandra Szkudlarek

Beilstein J. Nanotechnol. 2025, 16, 613–616, doi:10.3762/bjnano.16.47

• intelligence and automation, the potential for real-time process control and modeling-informed precision fabrication is immense. Rapid data analysis and automated software development could pave the way for a bottom-up approach, akin to how nature constructs complex biological systems. On behalf of all editors

Functionalized gold nanoflowers on carbon screen-printed electrodes: an electrochemical platform for biosensing hemagglutinin protein of influenza A H1N1 virus

• Carlos Enrique Torres-Méndez,
• Sharmilee Nandi,
• Klara Martinovic,
• Patrizia Kühne,
• Yifan Liu,
• Sam Taylor,
• Maria Lysandrou,
• Maria Ines Berrojo Romeyro Mascarenhas,
• Viktoria Langwallner,
• Javier Enrique Sebastián Alonso,
• Ivana Jovanovic,
• Maike Lüftner,
• Georgia-Vasiliki Gkountana,
• David Bern,
• Abdul-Raouf Atif,
• Ehsan Manouchehri Doulabi,
• Gemma Mestres and
• Masood Kamali-Moghaddam

Beilstein J. Nanotechnol. 2025, 16, 540–550, doi:10.3762/bjnano.16.42

• was coupled to an automated microfluidics system, and no significant decrease of the electrochemical signal was observed. Keywords: charge transfer; cyclic voltammetry; differential pulse voltammetry; electrochemical impedance spectroscopy; electrodeposition; Introduction Viral infections pose a

• measurements [46]. Furthermore, compatibility with microfluidic devices is important for the development of portable biosensing devices with automated functions and of simple use. Different antigens of the influenza A H1N1 virus have been targeted for detection over the years. In order to make a substantial

Integrating high-performance computing, machine learning, data management workflows, and infrastructures for multiscale simulations and nanomaterials technologies

• Fabio Le Piane,
• Mario Vozza,
• Matteo Baldoni and
• Francesco Mercuri

Beilstein J. Nanotechnol. 2024, 15, 1498–1521, doi:10.3762/bjnano.15.119

• ]), collaborative research environments (ResearchGate Labs [29], Mendeley Data) and other services for AI, data analytics, visualization, and training. Cloud platforms have also been used to perform simulations in the materials science domain [30] and to perform automated data analysis [31]. However, the power of

• domain provides the basic components to represent complex workflows in terms of basic and reusable building blocks enabling high-throughput and automated data processing. IATA Frameworks Integrated Approaches to Testing and Assessment (IATA) frameworks constitute another key set of technologies in the

• predictive analysis [71]. Moreover, it is tailored to the safe-by-design paradigm, making it an essential tool for future researches [72]. ASCOT (an acronym derived from Ag-Silver, Copper Oxide, Titanium Oxide) is a tool for the automated construction and optimization of molecular structures for, as the name

Hymenoptera and biomimetic surfaces: insights and innovations

• Vinicius Marques Lopez,
• Carlo Polidori and
• Rhainer Guillermo Ferreira

Beilstein J. Nanotechnol. 2024, 15, 1333–1352, doi:10.3762/bjnano.15.107

• some of these Hymenopteran species, that can even carry lift loads greater than the theoretical maximum as expected by their body mass and wing morphology [190], can inspire the design of robotic systems for material handling and transport, enhancing the efficiency of automated loading and unloading

New design of operational MEMS bridges for measurements of properties of FEBID-based nanostructures

• Bartosz Pruchnik,
• Krzysztof Kwoka,
• Ewelina Gacka,
• Dominik Badura,
• Piotr Kunicki,
• Andrzej Sierakowski,
• Paweł Janus,
• Tomasz Piasecki and
• Teodor Gotszalk

Beilstein J. Nanotechnol. 2024, 15, 1273–1282, doi:10.3762/bjnano.15.103

• prototyping and experimentation, such as electron and ion beams, and in particular FEBID [11][12][13]. FEBID has a resolution of a few nanometres [14] and can be automated [15] or combined with other technologies [16][17]. It can be used to deposit conductive or insulating layers, as well as layers of special

Direct electron beam writing of silver using a β-diketonate precursor: first insights

• Katja Höflich,
• Krzysztof Maćkosz,
• Chinmai S. Jureddy,
• Aleksei Tsarapkin and
• Ivo Utke

Beilstein J. Nanotechnol. 2024, 15, 1117–1124, doi:10.3762/bjnano.15.90

• deposition of an automated sequence of shapes overnight, carefully avoiding unintended electron beam impact while precursor molecules were present (cf. the section on deposit evolution in Supporting Information File 1 for more details). The high-resolution images presented in the main manuscript were taken

On the mechanism of piezoresistance in nanocrystalline graphite

• Sandeep Kumar,
• Simone Dehm and
• Ralph Krupke

Beilstein J. Nanotechnol. 2024, 15, 376–384, doi:10.3762/bjnano.15.34

• , which was constructed in-house and automated using Python. Then, sheet resistance measurements under externally applied strain are discussed. Raman spectroscopy of the NCG under strain is studied, which gives insights into the distribution of strain in the film. Utilizing electrical and optical

• Keithley 2636A device. The substrate holder and contacts holder were machined and attached to the stepper motor as shown in Figure 1a. A detailed description of the setup has been given by Kumar [23]. The complete setup was automated via self-programmed Python code. To completely eliminate any strain

Comparative electron microscopy particle sizing of TiO₂ pigments: sample preparation and measurement

• Ralf Theissmann,
• Christopher Drury,
• Markus Rohe,
• Thomas Koch,
• Jochen Winkler and
• Petr Pikal

Beilstein J. Nanotechnol. 2024, 15, 317–332, doi:10.3762/bjnano.15.29

• , and M3 completely rely on particle edge detection by the human eye, which is the most accurate detection method assuming good laboratory practice. Methods M1, P1, and P6 rely on automated particle detection, the former using a model-free sizing algorithm and the latter two using a sizing algorithm

• boundaries, the software packages listed in Table 10 evaluate all relevant size parameters, including ECD, Feret, and shape characteristics (e.g., convexity or shape factor). The automated pigment detection used by KRONOS detects the pigments based on their grey value in the image after automatic

• thresholding. While the former detection methods do not require any pre-processing of the image filtering of the obtained results, the automated detection methods require both noise reduction and contrast–brightness unification prior to the automated grey-value thresholding, and a shape- and grey value-based

Multiscale modelling of biomolecular corona formation on metallic surfaces

• Parinaz Mosaddeghi Amini,
• Ian Rouse,
• Julia Subbotina and
• Vladimir Lobaskin

Beilstein J. Nanotechnol. 2024, 15, 215–229, doi:10.3762/bjnano.15.21

• molecule, each constituent glucose bead is assigned a charge of 0, and the Hamaker term is neglected because of the small size of these beads. Following this parameterization, the coarse-grained lactose molecule is processed identically to proteins using the same automated pipeline, that is, UnitedAtom is

Dual-heterodyne Kelvin probe force microscopy

• Benjamin Grévin,
• Fatima Husainy,
• Dmitry Aldakov and
• Cyril Aumaître

Beilstein J. Nanotechnol. 2023, 14, 1068–1084, doi:10.3762/bjnano.14.88

• of the post-data acquisition data treatment (automated adjustment of the matrix of spectroscopic curves by batch processing with OriginPro software) are presented in Figure 4, along with the topographic image recorded simultaneously pixel by pixel with the spectroscopic curves. Note that the

A wearable nanoscale heart sound sensor based on P(VDF-TrFE)/ZnO/GR and its application in cardiac disease detection

• Yi Luo,
• Jian Liu,
• Jiachang Zhang,
• Yu Xiao,
• Ying Wu and
• Zhidong Zhao

Beilstein J. Nanotechnol. 2023, 14, 819–833, doi:10.3762/bjnano.14.67

• features, specifying validation scenarios, training models, and evaluating the results. Automated training was used to search for the best classification model types, including decision trees, support vector machines, logistic regression, and KNN. After cross-validation, a fine KNN (with a K value of 1

Metal-organic framework-based nanomaterials as opto-electrochemical sensors for the detection of antibiotics and hormones: A review

• Akeem Adeyemi Oladipo,
• Saba Derakhshan Oskouei and
• Mustafa Gazi

Beilstein J. Nanotechnol. 2023, 14, 631–673, doi:10.3762/bjnano.14.52

On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets

• Keith R. Paton,
• Konstantinos Despotelis,
• Naresh Kumar,
• Piers Turner and
• Andrew J. Pollard

Beilstein J. Nanotechnol. 2023, 14, 509–521, doi:10.3762/bjnano.14.42

• %), transmission electron microscopy (TEM) (7.2%) or X-ray photoelectron spectroscopy (XPS) (5.6%). It has the advantages of relatively low cost, simple sample preparation, quick measurements, and automated analysis, offering clear benefits for quality control applications. It has been demonstrated in several

• a GNP sample, individual spectra need to be analysed and classified before averaging. Using a metric based around the residual of a simple peak fitting means that this can be implemented in an automated, unsupervised method. This is essential for the use in a quality control process for industrial

Liquid phase exfoliation of talc: effect of the medium on flake size and shape

• Samuel M. Sousa,
• Helane L. O. Morais,
• Joyce C. C. Santos,
• Ana Paula M. Barboza,
• Bernardo R. A. Neves,
• Elisângela S. Pinto and
• Mariana C. Prado

Beilstein J. Nanotechnol. 2023, 14, 68–78, doi:10.3762/bjnano.14.8

• . Thick flakes (>100 nm) must be removed to implement a semi-automated analysis of thousands of flakes based on AFM images that provide a robust statistical representation of the sample [24][25]. At the same time, the removal of flakes that are few to tens of nanometers thick would make the effect of

DNA aptamer selection and construction of an aptasensor based on graphene FETs for Zika virus NS1 protein detection

• Nathalie B. F. Almeida,
• Thiago A. S. L. Sousa,
• Viviane C. F. Santos,
• Camila M. S. Lacerda,
• Thais G. Silva,
• Rafaella F. Q. Grenfell,
• Flavio Plentz and
• Antero S. R. Andrade

Beilstein J. Nanotechnol. 2022, 13, 873–881, doi:10.3762/bjnano.13.78

• /ampicillin and incubated overnight at 37 °C, 200 rpm. The plasmids were extracted following the manufacturer protocol of the Wizard® Plus SV Minipreps DNA purification system kit (Promega) and quantified via 260 nm absorbance in a spectrophotometer. The vectors were sequenced by the automated Sanger

Reliable fabrication of transparent conducting films by cascade centrifugation and Langmuir–Blodgett deposition of electrochemically exfoliated graphene

• Teodora Vićentić,
• Stevan Andrić,
• Vladimir Rajić and
• Marko Spasenović

Beilstein J. Nanotechnol. 2022, 13, 666–674, doi:10.3762/bjnano.13.58

• , Oviedo, Spain, Figure 2b). Using an automated pipette, the entire specific volume of the graphene dispersion in NMP was vertically dripped onto the surface of deionized water. Because the volumes ranged from 250 to 1000 µL, while the amount of graphene in that volume was kept fixed, the concentration of

A new method for obtaining the magnetic shape anisotropy directly from electron tomography images

• Cristian Radu,
• Ioana D. Vlaicu and
• Andrei C. Kuncser

Beilstein J. Nanotechnol. 2022, 13, 590–598, doi:10.3762/bjnano.13.51

• opposite is true. Two methods for thresholding have been implemented, an automated one using Otsu’s method [23] and a heuristic one, based on visual inspection of the result. While Otsu’s method is a well-established technique in image processing, the other method based on the visual inspection depends

Tin dioxide nanomaterial-based photocatalysts for nitrogen oxide oxidation: a review

• Viet Van Pham,
• Hong-Huy Tran,
• Thao Kim Truong and
• Thi Minh Cao

Beilstein J. Nanotechnol. 2022, 13, 96–113, doi:10.3762/bjnano.13.7

• SnO2, TiO2, and CuInS2 using an automated spray pyrolysis method, which is particularly beneficial for air cleaning applications. This work showed that the surface tension of the material surface directly impacts the photocatalytic activity under humid conditions. Furthermore, introducing CuInS2

Identifying diverse metal oxide nanomaterials with lethal effects on embryonic zebrafish using machine learning

• Richard Liam Marchese Robinson,
• Haralambos Sarimveis,
• Philip Doganis,
• Xiaodong Jia,
• Marianna Kotzabasaki,
• Christiana Gousiadou,
• Stacey Lynn Harper and
• Terry Wilkins

Beilstein J. Nanotechnol. 2021, 12, 1297–1325, doi:10.3762/bjnano.12.97