Focused electron beam induced deposition (FEBID) is a powerful technique for 3D-printing of complex nanodevices. However, for resolutions below 10 nm, it struggles to control size, morphology and composition of the structures, due to a lack of molecular-level understanding of the underlying irradiation-driven chemistry (IDC). Computational modeling is a tool to comprehend and further optimize FEBID-related technologies. Here we utilize a novel multiscale methodology which couples Monte Carlo simulations for radiation transport with irradiation-driven molecular dynamics for simulating IDC with atomistic resolution. Through an in depth analysis of $$\hbox {W(CO)}_6$$ W(CO) 6 deposition on $$\hbox {SiO}_2$$ SiO 2 and its subsequent irradiation with electrons, we provide a comprehensive description of the FEBID process and its intrinsic operation. Our analysis reveals that simulations deliver unprecedented results in modeling the FEBID process, demonstrating an excellent agreement with available experimental data of the simulated nanomaterial composition, microstructure and growth rate as a function of the primary beam parameters. The generality of the methodology provides a powerful tool to study versatile problems where IDC and multiscale phenomena play an essential role.

In this work we compare Monte Carlo (MC) simulations of electron transport properties with reflection electron energy loss measurements in diamond and graphite films. We assess the impact of different approximations of the dielectric response on the observables of interest for the characterization of carbon-based materials. We calculate the frequency-dependent dielectric response and energy loss function of these materials in two ways: a full ab initio approach, in which we carry out time-dependent density functional simulations in linear response for different momentum transfers, and a semi-classical model, based on the Drude-Lorentz extension to finite momenta of the optical dielectric function. Ab initio calculated dielectric functions lead to a better agreement with electron energy loss measured spectra with respect the widely used Drude-Lorentz model. This discrepancy is particularly evident for insulators and semiconductors beyond the optical limit (q = 0), where single particle excitations become relevant. Furthermore, we show that the behaviour of the energy loss function at different accuracy levels has a dramatic effect on other physical observables, such as the inelastic mean free path and the stopping power in the low energy regime (< 100 eV) and thus on the accuracy of MC simulations. * Corresponding authors Email addresses: taioli@ectstar.eu (Simone Taioli), dapor@ectstar.eu (Maurizio Dapor)

In this work, we present a computational method, based on the Monte Carlo statistical approach, for calculating electron energy emission and yield spectra of metals, such as copper, silver and gold. The calculation of these observables proceeds via the Mott theory to deal with the elastic scattering processes, and by using the Ritchie dielectric approach to model the electron inelastic scattering events. In the latter case, the dielectric function, which represents the starting point for the evaluation of the energy loss, is obtained from experimental reflection electron energy loss spectra. The generation of secondary electrons upon ionization of the samples is also implemented in the calculation. A remarkable agreement is obtained between both theoretical and experimental electron emission spectra and yield curves.

Understanding nanoscale molecular order within organic electronic materials is a crucial factor in building better organic electronic devices. At present, techniques capable of imaging molecular order within a polymer are limited in resolution, accuracy, and accessibility. In this work, presented are secondary electron (SE) spectroscopy and secondary electron hyperspectral imaging, which make an exciting alternative approach to probing molecular ordering in poly(3‐hexylthiophene) (P3HT) with scanning electron microscope‐enabled resolution. It is demonstrated that the crystalline content of a P3HT film is reflected by its SE energy spectrum, both empirically and through correlation with nano‐Fourier‐transform infrared spectroscopy, an innovative technique for exploring nanoscale chemistry. The origin of SE spectral features is investigated using both experimental and modeling approaches, and it is found that the different electronic properties of amorphous and crystalline P3HT result in SE emission with different energy distributions. This effect is exploited by acquiring hyperspectral SE images of different P3HT films to explore localized molecular orientation. Machine learning techniques are used to accurately identify and map the crystalline content of the film, demonstrating the power of an exciting characterization technique.

Carbon and carbon/metal systems with a multitude of functionalities are ubiquitous in new technologies but understanding on the nanoscale remains elusive due to their affinity for interaction with their environment and limitations in available characterization techniques. This paper introduces a spectroscopic technique and demonstrates its capacity to reveal chemical variations of carbon. The effectiveness of this approach is validated experimentally through spatially averaging spectroscopic techniques and using Monte Carlo modeling. Characteristic spectra shapes and peak positions for varying contributions of sp2‐like or sp3‐like bond types and amorphous hydrogenated carbon are reported under circumstances which might be observed on highly oriented pyrolytic graphite (HOPG) surfaces as a result of air or electron beam exposure. The spectral features identified above are then used to identify the different forms of carbon present within the metallic films deposited from reactive organometallic inks. While spectra for metals is obtained in dedicated surface science instrumentation, the complex relations between carbon and metal species is only revealed by secondary electron (SE) spectroscopy and SE hyperspectral imaging obtained in a state‐of‐the‐art scanning electron microscope (SEM). This work reveals the inhomogeneous incorporation of carbon on the nanoscale but also uncovers a link between local orientation of metallic components and carbon form.

Highly Oriented Pyrolitic Graphite presents a layered structure. In this work, we propose a theoretical and computational model for taking into account the anisotropic structure of graphite in the Monte Carlo simulations of charge transport. In particular, the dielectric characteristics, such as the inelastic mean free path and energy losses, are treated by linearly combining the contribution to these observables along the two main orthogonal directions identifying the crystalline structure (along the layer plane and perpendicular to it). Energy losses are evaluated from ab initio calculations of the dielectric function of the system along these two perpendicular directions. Monte Carlo simulated spectra, obtained with this approach, are compared with acquired experimental data of Reflection Electron Energy Loss and Secondary Electron spectra showing a good agreement. These findings validate the idea of the importance of considering properly-weighted inter-planar and intra-planar interactions in the simulation of electron transport in layered materials.

In this work we describe two different models for interpreting and predicting Reflection Electron Energy Loss (REEL) spectra and we present results of a study on metallic systems comparing the computational cost and the accuracy of these techniques. These approaches are the Monte Carlo (MC) method and the Numerical Solution (NS) of the Ambartsumian-Chandrasekhr equations. The former is based on a statistical algorithm to sample the electron trajectories within the target material for describing the electron transport. The latter relies on the numerical solution of the Ambartsumian-Chandrasekhar equations using the invariant embedding method. Both methods receive the same input parameters to deal with the elastic and inelastic electron scattering. To test their respective capability to describe REEL experimental spectra, we use copper, silver, and gold as case studies. Our simulations include both bulk and surface plasmon contributions to the energy loss spectrum by using the effective electron energy loss functions and the relevant extensions to finite momenta. The agreement between MC and NS theoretical spectra with experimental data is remarkably good. Nevertheless, while we find that these approaches are comparable in accuracy, the computational cost of NS is several orders of magnitude lower than the widely used MC. Inputs, routines and data are enclosed with this manuscript via the Mendeley database.

Nowadays, micro-machining techniques are commonly used in several industrial fields, such as automotive, aerospace and medical. Different technologies are available, and the choice must be made considering many factors, such as the type of machining, the number of lots and the required accuracy specifications in terms of geometrical tolerances and surface finish. Lasers and electric discharge machining (EDM) are widely used to produce micro-components and are similarly unconventional thermal technologies. In general, a laser is particularly appreciated by the industry for the excellent machining speeds and for the possibility to machine essentially any type of materials. EDM, on the other hand, has a poor material removal rate (MRR) but can produce microparts on only electrically conductive workpieces, reaching high geometrical accuracy and realizing steep walls. The most common micro-application for both the technologies is drilling but they can make also milling operations. In this work, a comparison of femto-laser and EDM technologies was made focusing on micro-milling. Two features were selected to make the comparison: micro-channels and micro-pillars. The depth was varied on two levels for both features. As workpiece material, aluminum, stainless steel and titanium alloy were tested. Data regarding the process performance and the geometrical characteristics of the features were analyzed. The results obtained with the two technologies were compared. This work improves the knowledge of the micro-manufacturing processes and can help in the characterization of their capabilities.