Session G47: Computational Design and Discovery of Novel Materials III

1D van der Waals Molecular Wires: Exfoliation Energies, Electronic Properties and Machine Learning Discovery

Two-dimensional (2D) materials derived from van der Waals (vdW)-bonded layered crystals have been the subject of considerable research focus, but analogous one-dimensional (1D) materials have received less attention while also exfoliable and useful for optical or electronic applications. Using density-functional-theory-based methods, we find binding energies of several 1D families to be within typical ranges possible for 2D materials. We compute the electronic properties of a variety of insulating, semiconducting, and metallic wires and find differences that could enable the identification of and distinction between 1D, 2D, and 3D forms during mechanical exfoliation onto a substrate. 1D wires from chemical families of the forms PdBr2, SbSeI, and GePdS3 are likely distinguishable from bulk materials via photoluminescence. Machine learning methods are used to predict undiscovered 1D materials, targeting conductive and magnetic compositions. Models trained on different data subsets recover similar predicted unsynthesized materials, illustrating robustness. We focus on classes of materials tailored for potential experimental synthesizability, specifically for chalcogen, halogen, and pnictogen-containing compounds.   

Properties of the overlooked boride-carbide-nitride families of MXenes via high-throughput DFT calculations

Since their initial discovery, many compositional and structural variations of the two-dimensional MXenes (M_n+1X_nT_x) have been proposed and synthesized. Each has distinct structural, electronic, and electrochemical properties. Here, instead of varying the “M” metal atom site as has mostly commonly been done, we study varying the “X” site atoms, substituting carbons for combinations of boron, carbon, and nitrogen. Using high-throughput density functional theory (DFT) enabled by an efficient and reproducible workflow, we obtain and analyze stable structures and resultant electronic properties of all combinations of these elements including for all common terminations (“T”). Results are contrasted with the established properties of Ti₃C₂. Based on their distinct properties, synthesis efforts for several of the novel materials are encouraged.   

High-throughput Identification of Stable 2D Janus-Bulk Materials Heterostructures

Janus materials possess a unique array of properties such as finite out-of-plane dipole moments, Rashba effect, strongly bound excitons, and strong interaction with light making these 2D materials ideal for a wide range of applications from piezoelectric devices to multi-layer 2D heterostructures. Janus MXY materials are 2D materials where a metal atomic layer M is sandwiched between layers X and Y of two different chalcogen, halogen, or pnictogen atoms. The properties of Janus materials are prone to alter due to interfacial interactions in a heterostructure.  Furthermore, the properties of 2D materials can be dramatically altered by placing them on substrates. For example, placing 2D-MoS₂ on a sapphire substrate reduces the mobility of the carriers by more than an order of magnitude. Using our workflow package 2dSynth, we compute the energetic stability, electronic properties, and charge transfer for ~50 MXY Janus materials on 50 elemental, cubic phase, metallic substrate materials using van der Waals-corrected density functional theory. Furthermore, we use machine learning models to identify structure-property correlations at the 2D Janus-substrate heterostructure interface.    

First principles study of oxidation resistance of atomically flat Cu(111) surface

Copper is one of the important materials used in modern technology and industries, but oxidation of copper deteriorates its application in nanotechnology. Our recent first principles total-energy calculations based on density functional theory is used to investigate the oxidation resistance of atomically flat Cu(111) surface. The exchange-correlation energy is described by the generalized gradient approximation (GGA) of Perdew–Burke–Ernzerhof (PBE) and projected augmented wave (PAW) method is employed. Our results show that atomically flat Cu(111) without multi-atomic steps is oxidation resistant. The energy barrier for oxygen penetrating flat surface and mono-atomic step is very high in comparison to multi-atomic steps. Also, incremental oxygen adsorption energy for the fcc site of the flat surface becomes positive and oxygen resistant above the oxygen coverage of 50%. These calculated results are consistent with the recent experimental finding.     

Structural dependence of spin-orbit-coupling induced band splitting in 2D hybrid organic inorganic perovskites.

We employ first-principles electronic structure calculations to study how structural motifs in organic and inorganic layers induce the Rashba/Dresselhaus types of band splitting in 2D hybrid organic inorganic perovskites (HOIPs). Through analysis of the spin texture, we elucidate how different chemical changes to phenyl ethyl ammonium spacer cations as well as changes to the inorganic layer cause the Rashba/Dresselhaus splitting. In this work we study 2D Lead Iodide perovskites with Phenyl ethyl ammonium (PEA) spacer cations to illustrate this spatio-symmetric dependence of spin textures in the inorganic sublattice of HOIPs.

    

Strain and interface effects on the stability and electronic properties of SiGe/GeC lateral heterostructure

A systematic investigation of the strain and interface effects on the stability and the electronic properties of SiGe/GeC lateral heterostructure is being carried out from the first principle calculations. Our preliminary results have shown that there exists a strong local strain due to the large lattice mismatch (over 20 %) between buckled SiGe and flatted GeC domains, and such local strain is distributed anisotropically. It is strong along the interface and weak inside the domains perpendicular to the interface. The stabilized structure of such heterostructure with the armchair interface shows a combination of a quasi-flatted GeC domain with a low buckled SiGe domain either in the Si-Ge/Ge-C type of bonding or in the Si-C/Ge-Ge type of bonding at the interface. However, a high buckling in the SiGe domain is found in such heterostructure with the zigzag interface. More interestingly, a gap opening is found in the system with the armchair interface, as compared to the gapless of the SiGe sheet, indicating its promising application in band gap engineering. Detail discussion will be presented in the presentation.   

First-principles study of the functionalized-MXene for Li-ion battery application

Two-dimensional (2D) transition-metal carbides/nitrides (MXenes) have been highlighted as one of the promising battery anode materials due to their long cycle lifetime, low diffusion barrier, and controllable interlayer distance using surface functionalization. Tailored introduction of functional groups on the surfaces of MXenes can further enhance their physical and chemical properties, extending possible applications of MXenes to a wider set of fields. In this presentation, we carried out first-principles calculation and studied the effect of functionalization of MXene in the aspect of the anode application for Li-ion battery. Calculating the binding energy, diffusion barrier, and diffusion path of a Li atom, we first evaluate the Li-ion battery anode performance of pristine Ti₃C₂ as well as functionalized MXenes (Ti₃C₂T_x, T_x = -F, -O) and exhibited that the MXene-based anodes show better performance than conventional graphite anode. Next, we consider Ti₃C₂O₂ with nitrobenzene-termination (C₆H₄NO₂), which was experimentally obtained recently and demonstrated that the Li ion diffusion paths can be controlled using nitrobenzene-termination with low diffusion barrier heights. This study will offer promising strategies for the design of advanced MXene-based battery materials.   

The amorphous-structure conundrum in two-dimensional materials: Monolayer amorphous carbon versus boron nitride

The structure of amorphous materials – continuous random networks (CRN) vs. CRN with crystallites – has been debated for decades. In two-dimension (2D), this question can be addressed more directly. Recently, atomic-resolution imaging revealed that monolayer amorphous carbon (MAC) is a CRN containing random graphene nanocrystallites. For another prototypical 2D material – h-BN, the existence and structure of its amorphous counterpart is unknown. Here we report kinetic Monte Carlo simulations of the formation and structure evolution of monolayer amorphous boron nitride (ma-BN) and demonstrate that it has a purely CRN structure. The key difference between MAC and ma-BN is that, at low temperatures, C atoms easily form canonical hexagons, whereas the probability to form canonical B-N-B-N-B-N hexagons is very low. It is the binary nature of BN that generates insurmountable steric constraints for the formation of h-BN crystallites. However, ma-BN contains pseudocrystalline nano regions comprising noncanonical hexagons, analogs of MAC's graphene nanocrystallites. Therefore, two distinct amorphous structures are possible in 2D. The ma-BN is stable and insulating, and the thermal conductivity is two orders of magnitudes smaller than h-BN due to vibrational-mode localization.   

Optical Engineering of Biphenylene and Graphene Nanoribbons

Confinement of electrons and strong light-matter interactions in graphene-based nanoribbons give rise to behavior not obtainable in bulk material. Such nanoribbons show potential to be used for numerous optoelectronic applications including field effect transistors, optical absorbers, and low noise biosensors. The optoelectronic properties of graphene nanoribbons are readily manipulated through multiple approaches: cutting direction, width, strain, electronic doping, and edge functionalization. Fan et. al. have recently reported on a procedure to synthesize quasi-1D nanoribbons based on biphenylene networks, another sp² hybridized carbon allotrope. Choice of carbon allotrope provides another method for engineering the optoelectronic properties of nanoribbons. We report on the results of high throughput DFT calculations for a wide array of biphenylene and graphene based nanoribbons. Nanoribbon structures are evaluated for phase, bandgap, dielectric function, and absorption. Machine learning is used to identify trends between nanoribbon structure and optical properties and predict new structures with desired optical response.   

Towards Accurate Calculations of Mechanical Properties in Monolayer Covalent-Organic Frameworks

Covalent-Organic Frameworks (COFs) are crystalline porous materials that are based on organic monomeric units, so called building blocks. As a multitude of different building blocks can be combined in reticular chemistry, manifold different porous structures with tailored properties have been synthesized in recent years. Through recent experimental progress, monolayer COF materials have been synthesized, providing a new class of 2D materials. From a computational point of view, however, accurately calculating properties of these materials is computationally demanding as the unit cells of COFs are usually very big. In this work we calculate mechanical properties for a set of 2D COFs and compare results of density functional based tight binding (DFTB) with classical force-fields. We show how force-fields can be very useful for mechanical property calculation, how their accuracy can be improved, and typical fallacies for 2D porous materials. Furthermore, we introduce models to predict mechanical properties from the properties of the monomeric building blocks. This paves the way for multiscale modeling, high-throughput calculations, and materials prediction with properties on demand.   

Quantum Mechanics Enables "Freedom of Design" in Molecular Property Space

Rational design of molecules with targeted properties requires understanding quantum-mechanical (QM) structure-property/property-property relationships (SPR/PPR) across chemical compound space. We analyze these relationships using the QM7-X dataset—which includes 42 QM properties for ~4.2 M equilibrium and non-equilibrium structures of small organic molecules. Instead of providing simple SPR/PPR that strictly follow physicochemical intuition, our analysis uncovers substantial flexibility in molecular property space (MPS) when searching for a single molecule with a desired pair of properties or distinct molecules with a targeted set of properties. As proof-of-concept, we used Pareto multi-property optimization to search for the most promising (i.e., highly polarizable and electrically stable) molecules for polymeric battery materials; without prior knowledge of this complex MPS manifold, Pareto front analysis reflected this intrinsic flexibility and identified small directed structural/compositional changes that simultaneously optimize both properties. Our analysis of such extensive QM property data provides compelling evidence for an intrinsic "freedom of design" in MPS and indicates that rational design of molecules with a diverse array of targeted properties is quite feasible.   

Graphene Origami with Highly Tunable Coefficient of Thermal Expansion

The coefficient of thermal expansion, which measures the change in length, area, or volume of a material upon heating, is a fundamental parameter with great relevance for many applications. Although there are various routes to design materials with targeted coefficient of thermal expansion at the macroscale, no approaches exist to achieve a wide range of values in graphene-based structures. Here, we use molecular dynamics simulations to show that graphene origami structures obtained through pattern-based surface functionalization provide tunable coefficients of thermal expansion from large negative to large positive. We show that the mechanisms giving rise to this property are exclusive to graphene origami structures, emerging from a combination of surface functionalization, large out-of-plane thermal fluctuations, and the three-dimensional geometry of origami structures.