Rearrangements and Dilatancy for Sheared Dense Materials

Constitutive equations are proposed for dense materials, based on the identification of two types of free-volume activated rearrangements associated to shear and compaction. Two situations are studied: the case of an amorphous solid in a stress-strain test, and the case of a lubricant in tribology test. Varying parameters, strain softening, shear thinning, and stick-slip motion can be observed.Comment: 4 pages, 3 figure

Health and Safety Events for Latino Families: Collaborating to Create \u3ci\u3eEl Día de los Niños Celebración\u3c/i\u3e

Latino immigrants to rural counties within North Carolina are at an increased risk for experiencing injury, health complications, and chronic illness. This is due largely to the fact that many new immigrants arrive with limited knowledge of the health and safety risks that are present in their communities. To reduce the incidence of injury and health complications, programs must be developed to increase local awareness of these risks. This article outlines the collaborative efforts of one rural North Carolina community to develop and implement a community-based health and safety event for Latino families

Rapid and accurate molecular deprotonation energies from quantum alchemy

We assess the applicability of alchemical perturbation density functional theory (APDFT) for quickly and accurately estimating deprotonation energies. We have considered all possible single and double deprotonations in one hundred small organic molecules drawn at random from QM9 [Ramakrishnan et al., JCTC, 2015]. Numerical evidence is presented for 5160 deprotonated species at both HF/def2-TZVP and CCSD/6-31G* levels of theory. We show that the perturbation expansion formalism of APDFT quickly converges to reliable results: using CCSD electron densities and derivatives, regular Hartree-Fock calculations are outperformed at the second or third order for ranking all possible doubly or singly deprotonated molecules, respectively. CCSD single deprotonation energies are reproduced within 1.4 kcal mol-1 on average within third order APDFT. We introduce a hybrid approach where the computational cost of APDFT is reduced even further by mixing first order terms at a higher level of theory (CCSD) with higher order terms at a lower level of theory only (HF). We find that this approach reaches 2 kcal mol-1 accuracy in absolute deprotonation energies compared to CCSD at 2% of the computational cost of third order APDFT

Simplifying inverse material design problems for fixed lattices with alchemical chirality

Massive brute-force compute campaigns relying on demanding ab initio calculations routinely search for novel materials in chemical compound space, the vast virtual set of all conceivable stable combinations of elements and structural configurations which form matter. Here we demonstrate that 4-dimensional chirality, arising from anti-symmetry of alchemical perturbations, dissects that space and defines approximate ranks which effectively reduce its formal dimensionality, and enable us to break down its combinatorial scaling. The resulting distinct `alchemical' enantiomers must share the exact same electronic energy up to third order -- independent of respective covalent bond topology, and imposing relevant constraints on chemical bonding. Alchemical chirality deepens our understanding of chemical compound space and enables the `on-the-fly' establishment of new trends without empiricism for any materials with fixed lattices. We demonstrate its efficacy for three such cases: i) new formulas for estimating electronic energy contributions to chemical bonding; ii) analysis of the perturbed electron density of BN doped benzene; and iii) ranking stability estimates for BN doping in over 2,000 naphthalene and over 400 million picene derivatives

Simplifying inverse materials design problems for fixed lattices with alchemical chirality

Brute-force compute campaigns relying on demanding ab initio calculations routinely search for previously un- known materials in chemical compound space (CCS), the vast set of all conceivable stable combinations of elements and structural configurations. Here, we demonstrate that four-dimensional chirality arising from antisymmetry of alchemical perturbations dissects CCS and defines approximate ranks, which reduce its formal dimensionality and break down its combinatorial scaling. The resulting "alchemical" enantiomers have the same electronic energy up to the third order, independent of respective covalent bond topology, imposing relevant constraints on chemical bonding. Alchemical chirality deepens our understanding of CCS and enables the establishment of trends without empiricism for any materials with fixed lattices. We demonstrate the efficacy for three cases: (i) new rules for elec- tronic energy contributions to chemical bonding; (ii) analysis of the electron density of BN-doped benzene; and (iii) ranking over 2000 and 4 million BN-doped naphthalene and picene derivatives, respectively

Deep Sequencing Analysis of RNAs from Citrus Plants Grown in a Citrus Sudden Death-Affected Area Reveals Diverse Known and Putative Novel Viruses.

Citrus sudden death (CSD) has caused the death of approximately four million orange trees in a very important citrus region in Brazil. Although its etiology is still not completely clear, symptoms and distribution of affected plants indicate a viral disease. In a search for viruses associated with CSD, we have performed a comparative high-throughput sequencing analysis of the transcriptome and small RNAs from CSD-symptomatic and -asymptomatic plants using the Illumina platform. The data revealed mixed infections that included Citrus tristeza virus (CTV) as the most predominant virus, followed by the Citrus sudden death-associated virus (CSDaV), Citrus endogenous pararetrovirus (CitPRV) and two putative novel viruses tentatively named Citrus jingmen-like virus (CJLV), and Citrus virga-like virus (CVLV). The deep sequencing analyses were sensitive enough to differentiate two genotypes of both viruses previously associated with CSD-affected plants: CTV and CSDaV. Our data also showed a putative association of the CSD-symptomatic plants with a specific CSDaV genotype and a likely association with CitPRV as well, whereas the two putative novel viruses showed to be more associated with CSD-asymptomatic plants. This is the first high-throughput sequencing-based study of the viral sequences present in CSD-affected citrus plants, and generated valuable information for further CSD studies

Improved decision making with similarity based machine learning

Despite their fundamental importance for science and society at large, experimental design decisions are often plagued by extreme data scarcity which severely hampers the use of modern ready-made machine learning models as they rely heavily on the paradigm, 'the bigger the data the better'. Presenting similarity based machine learning we show how to reduce these data needs such that decision making can be objectively improved in certain problem classes. After introducing similarity machine learning for the harmonic oscillator and the Rosenbrock function, we describe real-world applications to very scarce data scenarios which include (i) quantum mechanics based molecular design, (ii) organic synthesis planning, and (iii) real estate investment decisions in the city of Berlin, Germany