Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials

Neural message passing on molecular graphs is one of the most promising methods for predicting formation energy and other properties of molecules and materials. In this work we extend the neural message passing model with an edge update network which allows the information exchanged between atoms to depend on the hidden state of the receiving atom. We benchmark the proposed model on three publicly available datasets (QM9, The Materials Project and OQMD) and show that the proposed model yields superior prediction of formation energies and other properties on all three datasets in comparison with the best published results. Furthermore we investigate different methods for constructing the graph used to represent crystalline structures and we find that using a graph based on K-nearest neighbors achieves better prediction accuracy than using maximum distance cutoff or the Voronoi tessellation graph

Edge-dependent reflection and inherited fine structure of higher-order plasmons in graphene nanoribbons

We investigate higher-order plasmons in graphene nanoribbons, and present how electronic edge states and wavefunction fine structure influence the graphene plasmons. Based on nearest-neighbor tight-binding calculations, we find that a standing-wave model based on nonlocal bulk plasmon dispersion is surprisingly accurate for armchair ribbons of widths even down to a few nanometers, and we determine the corresponding phase shift upon edge reflection and an effective ribbon width. Wider zigzag ribbons exhibit a similar phase shift, whereas the standing-wave model describes few-nanometer zigzag ribbons less satisfactorily, to a large extent because of their edge states. We directly confirm that also the larger broadening of plasmons for zigzag ribbons is due to their edge states. Furthermore, we report a prominent fine structure in the induced charges of the ribbon plasmons, which for armchair ribbons follows the electronic wavefunction oscillations induced by inter-valley coupling. Interestingly, the wavefunction fine structure is also found in our analogous density-functional theory calculations, and both these and tight-binding numerical calculations are explained quite well with analytical Dirac theory for graphene ribbons

Emergent scale invariance of non-classical plasmons in graphene nanoribbons

Using a nearest-neighbor tight-binding model we investigate quantum effects of plasmons on few-nanometer wide graphene nanoribbons, both for zigzag and armchair edge terminations. With insight from the Dirac description we find an emerging scale-invariant behavior that deviates from the classical model both for zigzag and armchair structures. The onset of the deviation can be related to the position of the lowest parabolic band in the band structure. Dirac theory is only valid in the parameter subspace where the scale invariance holds that relates narrow ribbons with high doping to wide ribbons with low doping. We also find that the edge states present in zigzag ribbons give rise to a blueshift of the plasmon, in contrast to earlier findings for graphene nanodisks and nanotriangles

Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors

Computational materials screening studies require fast calculation of the properties of thousands of materials. The calculations are often performed with Density Functional Theory (DFT), but the necessary computer time sets limitations for the investigated material space. Therefore, the development of machine learning models for prediction of DFT calculated properties are currently of interest. A particular challenge for \emph{new} materials is that the atomic positions are generally not known. We present a machine learning model for the prediction of DFT-calculated formation energies based on Voronoi quotient graphs and local symmetry classification without the need for detailed information about atomic positions. The model is implemented as a message passing neural network and tested on the Open Quantum Materials Database (OQMD) and the Materials Project database. The test mean absolute error is 20 meV on the OQMD database and 40 meV on Materials Project Database. The possibilities for prediction in a realistic computational screening setting is investigated on a dataset of 5976 ABSe$_3$ selenides with very limited overlap with the OQMD training set. Pretraining on OQMD and subsequent training on 100 selenides result in a mean absolute error below 0.1 eV for the formation energy of the selenides.Comment: 14 pages including references and 13 figure

Influence of intermartensitic transitions on transport properties of Ni2.16Mn0.84Ga alloy

Magnetic, transport, and x-ray diffraction measurements of ferromagnetic shape memory alloy Ni$_{2.16}$Mn$_{0.84}$Ga revealed that this alloy undergoes an intermartensitic transition upon cooling, whereas no such a transition is observed upon subsequent heating. The difference in the modulation of the martensite forming upon cooling from the high-temperature austenitic state [5-layered (5M) martensite], and the martensite forming upon the intermartensitic transition [7-layered (7M) martensite] strongly affects the magnetic and transport properties of the alloy and results in a large thermal hysteresis of the resistivity $\rho$ and magnetization $M$. The intermartensitic transition has an especially marked influence on the transport properties, as is evident from a large difference in the resistivity of the 5M and 7M martensite, $(\rho_{\mathrm{5M}} - \rho_{\mathrm{7M}})/\rho _{\mathrm{5M}} \approx 15$, which is larger than the jump of resistivity at the martensitic transition from the cubic austenitic phase to the monoclinic 5M martensitic phase. We assume that this significant difference in $\rho$ between the martensitic phases is accounted for by nesting features of the Fermi surface. It is also suggested that the nesting hypothesis can explain the uncommon behavior of the resistivity at the martensitic transition, observed in stoichiometric and near-stoichiometric Ni-Mn-Ga alloys.Comment: 7 pages, 6 figures, REVTEX

The Service Use Index: A Tool for Examining Rural/Urban Differences

Development of tools for identifying and tracking differences in older adult service utilization by race, ethnicity, income, and geographic area is vital in the face of current demographic and economic changes in rural areas, particularly in areas experiencing rapid demographic changes. In this conceptual article, we explain how to calculate a service use index that compares service utilization of a specific group of older adults to that of the entire older adult population. We then illustrate its usefulness with a case example using geographic information systems (GIS). This unique approach can be utilized to understand differences across fields of practice, enhance planning to address differences, and monitor changes over time

A Decolonial Critique of the Racialized “Localwashing” of Extraction in Central Africa

Responding to calls for increased attention to actions and reactions “from above” within the extractive industry, we offer a decolonial critique of the ways in which corporate entities and multinational institutions propagate racialized rhetoric of “local” suffering, “local” consultation, and “local” fault for failure in extractive zones. Such rhetoric functions to legitimize extractive intervention within a set of practices that we call localwashing. Drawing from a decade of research on and along the Chad-Cameroon Oil Pipeline, we show how multi-scalar actors converged to assert knowledge of, responsibility for, and collaborations with “local” people within a racialized politics of scale. These corporate representations of the racialized “local” are coded through long-standing colonial tropes. We identify three interrelated and overlapping flexian elite rhetoric(s) and practices of racialized localwashing: (a) anguishing, (b) arrogating, and (c) admonishing. These elite representations of a racialized “local” reveal diversionary efforts “from above” to manage public opinion, displace blame for project failures, and domesticate dissent in a context of persistent scrutiny and criticism from international and regional advocates and activists