Prediction of cytotoxicity of heavy metals adsorbed on nano-TiO₂ with periodic table descriptors using machine learning approaches

• Joyita Roy,
• Souvik Pore and
• Kunal Roy

Beilstein J. Nanotechnol. 2023, 14, 939–950, doi:10.3762/bjnano.14.77

• datasets with great efficiency [27]. It can be regarded as a dimensionality reduction method since it analyzes large input data and finds all important variables. While handling RF datasets, the model emphasizes the importance of parameters, which is a highly helpful aspect [28]. Adaptive boosting

A chemiresistive sensor array based on polyaniline nanocomposites and machine learning classification

• Jiri Kroutil,
• Alexandr Laposa,
• Ali Ahmad,
• Jan Voves,
• Vojtech Povolny,
• Ladislav Klimsa,
• Marina Davydova and
• Miroslav Husak

Beilstein J. Nanotechnol. 2022, 13, 411–423, doi:10.3762/bjnano.13.34

• composed by seven different conductive sensors with composite sensing layers are measured and analyzed using machine learning. Statistical tools, such as principal component analysis and linear discriminant analysis, are used as dimensionality reduction methods. Five different classification methods

• process classification (GPC) in order to enhance the discrimination of gases and get better selectivity [13]. In this work we suggest a new method in our classification system by combining the abovementioned methods and using the output of the two most powerful techniques in dimensionality reduction and

On the frequency dependence of viscoelastic material characterization with intermittent-contact dynamic atomic force microscopy: avoiding mischaracterization across large frequency ranges

• Enrique A. López-Guerra and
• Santiago D. Solares

Beilstein J. Nanotechnol. 2020, 11, 1409–1418, doi:10.3762/bjnano.11.125

• dimensionality reduction (MDR) [51]. The four coupled equations (three cantilever eigenmodes and the viscoelastic model relaxation and force calculation) were integrated numerically. The simulation procedures have been discussed in detail in previous publications and their supporting information files [14][33

Evidence of friction reduction in laterally graded materials

• Roberto Guarino,
• Gianluca Costagliola,
• Federico Bosia and
• Nicola Maria Pugno

Beilstein J. Nanotechnol. 2018, 9, 2443–2456, doi:10.3762/bjnano.9.229

• , the method of dimensionality reduction [24][25] has been extended to the axisymmetric frictionless contact of elastically graded materials [26], and solutions are also provided in the presence of adhesion [27]. In all these cases, the elastic gradients are considered with respect to the depth, with an

Imaging of viscoelastic soft matter with small indentation using higher eigenmodes in single-eigenmode amplitude-modulation atomic force microscopy

• Miead Nikfarjam,
• Enrique A. López-Guerra,
• Santiago D. Solares and
• Babak Eslami

Beilstein J. Nanotechnol. 2018, 9, 1116–1122, doi:10.3762/bjnano.9.103

• knowledge of the loading history is not available, we use an alternative approach based on the method of dimensionality reduction (MDR) in which a three-dimensional continuum is replaced by a uniquely defined one-dimensional linear viscoelastic foundation [23]. This simple method has proven to generate

Stick–slip boundary friction mode as a second-order phase transition with an inhomogeneous distribution of elastic stress in the contact area

• Iakov A. Lyashenko,
• Vadym N. Borysiuk and
• Valentin L. Popov

Beilstein J. Nanotechnol. 2017, 8, 1889–1896, doi:10.3762/bjnano.8.189

• of the friction block through an elastic spring, the frequency of the melting/solidification phase transitions increases with time. Keywords: boundary friction; dimensionality reduction; numerical simulation; shear stress and strain; stick–slip motion; tribology; Introduction The boundary friction

• method of dimensionality reduction (MDR) [24][25][26], which allows us to reduce the three-dimensional problem (with general coordinate r) to an equivalent one-dimensional (coordinate x) with a possible reverse transition. Within the MDR technique, a one-dimensional distribution of the force density can

• increases (as it is shown in Figure 2 and Figure 4) due to the increase in the strain rate. Conclusion We have presented the dynamical simulation of the boundary friction between a cylindrically shaped stamp and a flat surface. Using the method of dimensionality reduction (MDR) we have studied the stick

Kelvin probe force microscopy in liquid using electrochemical force microscopy

• Liam Collins,
• Stephen Jesse,
• Jason I. Kilpatrick,
• Alexander Tselev,
• M. Baris Okatan,
• Sergei V. Kalinin and
• Brian J. Rodriguez

Beilstein J. Nanotechnol. 2015, 6, 201–214, doi:10.3762/bjnano.6.19

• that within the first two PCs, isolated regions or hot spots demonstrate a different electrochemical behavior from their immediate surroundings. This highlights the usefulness of PCA for dimensionality reduction and qualitative visualization of spatial variations in the EcFM measurements. The