Search

Elucidating cellulose-lignin interactions at the molecular and nanometric scales is an important research topic with impacts on several pathways of biomass valorization. Here, the interaction forces between a cellulosic substrate and lignin are investigated. Atomic force microscopy with lignin-coated tips is employed to probe the site-specific adhesion to a cellulose film in liquid water. Over seven thousand force-curves are analyzed by a machine-learning approach to cluster the experimental data into types of cellulose-tip interactions. The molecular mechanisms for distinct types of cellulose-lignin interactions are revealed by molecular dynamics simulations of lignin globules interacting with different cellulose Iβ crystal facets. This unique combination of experimental force-curves, data-driven analysis, and molecular simulations opens a new approach of investigation and updates the understanding of cellulose-lignin interactions at the nanoscale.

Monolayers of transition metal dichalcogenides (TMDs) in the 2H structural phase have been recently classified as higher-order topological insulators (HOTI), protected by $C_3$ rotation symmetry. In addition, theoretical calculations show an orbital Hall plateau in the insulating gap of TMDs, characterized by an orbital Chern number. We explore the correlation between these two phenomena in TMD monolayers in two structural phases: the noncentrosymmetric 2H and the centrosymmetric 1T. Using density functional theory, we confirm the characteristics of 2H-TMDs and reveal that 1T-TMDs are identified by a $\mathbb{Z}_4$ topological invariant. As a result, when cut along appropriate directions, they host conducting edge-states, which cross their bulk energy-band gaps and can transport orbital angular momentum. Our linear response calculations thus indicate that the HOTI phase is accompanied by an orbital Hall effect. Using general symmetry arguments, we establish a connection between the two phenomena with potential implications for spin-orbitronics., 5 pages, 4 figures

Using a combination of in situ high-resolution transmission electron microscopy and density functional theory, we report the formation and rupture of ZrO_{2} atomic ionic wires. Near rupture, under tensile stress, the system favors the spontaneous formation of oxygen vacancies, a critical step in the formation of the monatomic bridge. In this length scale, vacancies provide ductilelike behavior, an unexpected mechanical behavior for ionic systems. Our results add an ionic compound to the very selective list of materials that can form monatomic wires and they contribute to the fundamental understanding of the mechanical properties of ceramic materials at the nanoscale.

Understanding the role of microscopic attributes in nanocomposites allows for a controlled and, therefore, acceleration in experimental system designs. In this work, we extracted the relevant parameters controlling the graphene oxide binding strength to cellulose by combining first-principles calculations and machine learning algorithms. We were able to classify the systems among two classes with higher and lower binding energies, which are well defined based on the isolated graphene oxide features. By a theoretical X-ray photoelectron spectroscopy analysis, we show the extraction of these relevant features. Additionally, we demonstrate the possibilities of a refined control within a machine learning regression between the binding energy values and the system's characteristics. Our work presents a guiding map to the control graphene oxide/cellulose interaction.

Polyphenols are natural molecules of crucial importance in many applications, of which tannic acid (TA) is one of the most abundant and established. Most high-value applications require precise control of TA interactions with the system of interest. However, the molecular structure of TA is still not comprehended at the atomic level, of which all electronic and reactivity properties depend. Here, we combine an enhanced sampling global optimization method with density functional theory (DFT)-based calculations to explore the conformational space of TA assisted by unsupervised machine learning visualization and then investigate its lowest energy conformers. We study the external environment's effect on the TA structure and properties. We find that vacuum favors compact structures by stabilizing peripheral atoms' weak interactions, while in water, the molecule adopts more open conformations. The frontier molecular orbitals of the conformers with the lowest harmonic vibrational free energy have a HOMO-LUMO energy gap of 2.21 (3.27) eV, increasing to 2.82 (3.88) eV in water, at the DFT generalized gradient approximation (and hybrid) level of theory. Structural differences also change the distribution of potential reactive sites. We establish the fundamental importance of accurate structural consideration in determining TA and related polyphenol interactions in relevant technological applications.

One of the main goals and challenges of materials discovery is to find the best candidates for each interest property or application. Machine learning rises in this context to efficiently optimize this search, exploring the immense materials space, consisting of simultaneously the atomic, compositional, and structural spaces. Topological insulators, presenting symmetry-protected metallic edge states, are a promising class of materials for different applications. However, further, development is limited by the scarcity of viable candidates. Here we present and discuss machine learning-accelerated strategies for searching the materials space for two-dimensional topological materials. We show the importance of detailed investigations of each machine learning component, leading to different results. Using recently created databases containing thousands of ab initio calculations of 2D materials, we train machine learning models capable of determining the electronic topology of materials, with an accuracy of over 90%. We can then generate and screen thousands of novel materials, efficiently predicting their topological character without the need for a priori structural knowledge. We discover 56 non-trivial materials, of which 17 novel insulating candidates for further investigation, for which we corroborate their topological properties with density functional theory calculations. This strategy is 10$\times$ more efficient than the trial-and-error approach while few orders of magnitude faster and is a proof of concept for guiding improved materials discovery search strategies., Comment: Accepted for publication in Applied Physical Review. For Supplemental Materials please contact one of the authors

The robustness of topological materials against disorder and defects is presumed but has not been demonstrated explicitly in realistic systems. In this work, we use state-of-the-art density functional theory and recursive nonequilibrium Green's functions methods to study the effect of disorder on the electronic transport of long nanoribbons, up to $157\phantom{\rule{0.28em}{0ex}}\mathrm{nm}$, as a function of vacancy concentration. In narrow nanoribbons, a finite-size effect gives rise to hybridization between the edge states erasing topological protection. Hence, even small vacancy concentrations enable backscattering events. We show that the topological protection is more robust for wide nanoribbons, but surprisingly it breaks down at moderate structural disorder. Our study helps to establish some bounds on defective bismuthene nanoribbons as promising candidates for spintronic applications.

Two-dimensional ${\mathrm{Na}}_{3}\mathrm{Bi}$ is a dual topological insulator protected by time-reversal and mirror symmetry, resulting in a promising platform for device design. However, in reality, the design of topological devices is hindered by a sensitivity against disorder and temperature. We study the topological properties of ${\mathrm{Na}}_{3}\mathrm{Bi}$ in the presence of intrinsic defects, investigating the robustness of the edge states and the resulting transport properties. We apply a recursive Green's function technique enabling the study of disordered systems with lengths comparable to experimentally synthesized materials, in the order of micrometers. We combine our findings to propose a topological insulator device, where intrinsic defects are used to filter the response of trivial bulk states. This results in a stable conductance throughout a large range of electronic temperatures, and controllable by a perpendicular electric field. Our proposal is general, enabling the design of various dual topological insulator devices.

We investigate the structure and electronic spectra properties of two-dimensional amorphous bismuthene structures and show that these systems are topological insulators. We employ a realistic modeling of amorphous geometries together with density functional theory for electronic structure calculations. We investigate the system topological properties throughout the amorphization process and find that the robustness of the topological phase is associated with the spin–orbit coupling strength and size of the pristine topological gap. Using recursive non-equilibrium Green’s function, we study the electronic transport properties of nanoribbons devices with lengths comparable to experimentally synthesized materials. We find a 2e 2/h conductance plateau within the topological gap and an onset of Anderson localization at the trivial insulator phase.