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At least 127 records · Page 7

Combinatorial investigation of the Mn–Ge–N chemical system containing ternary nitrides Mn 3 GeN and MnGeN 2

By changing nitrogen chemical potential during synthesis of Mn–Ge–N ternary nitrides, both wurtzite MnGeN 2 and antiperovskite Mn 3 GeN ternary phases are prepared. Antiperovskite films are optically opaque and conductive, while wurtzite films with Mn/(Mn + Ge) ≤ 0.5 transmit light above ~ 2 eV. Alloys of Mn 3 GeN with Si and Al are also investigated. Mn 3 (Ge 1−x Al x )N alloys with 0.07 ≤ x ≤ 0.16 exhibit a cubic (rather than tetragonal) structure. Mn 3 (Ge 1−x Si x )N with x ≤ 0.05 maintains the tetragonal structure but becomes cubic when x > 0.05. This study shows that care must be taken in the synthesis of Mn–Ge–N and similar nitrides, especially when materials are integrated into devices not amenable to structural and chemical probing.

36 MATERIALS SCIENCE↗

Constructing non-Abelian quantum spin liquids using combinatorial gauge symmetry

We construct Hamiltonians with only 1- and 2-body interactions that exhibit an exact non-Abelian gauge symmetry (specifically, combinatiorial gauge symmetry). Our spin Hamiltonian realizes the quantum double associated to the group of quaternions. It contains only ferromagnetic and anti-ferromagnetic ZZ Z Z interactions, plus longitudinal and transverse fields, and therefore is an explicit example of a spin Hamiltonian with no sign problem that realizes a non-Abelian topological phase. In addition to the spin model, we propose a superconducting quantum circuit version with the same symmetry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Combinatorial Evaluation of Physical Feature Engineering, Classical Machine Learning, and Deep Learning Models for Synchrophasor Data at Scale

A major objective of the project was to train and evaluate the effectiveness of multiple event and anomaly detection, identification and classification deep temporal learning models for processing of real-time phasor measurement unit (PMU) data streams. A vast dataset, consisting of two years of phasor measurements from all three U.S. Interconnections, was curated and released by the Department of Energy (DOE) through Pacific Northwest National Laboratory (PNNL). The dataset also included an event log that provided event times and types (e.g. generator trips, line trips, planned service events, transformer operations, etc.). Our analysis of this dataset addressed six (6) of the eleven (11) research priorities identified in Funding Opportunity Announcement (FOA) DE-FOA-0001861 “Big Data Analysis of Synchrophasor Data” (FOA 1861). Rather than being limited to pre-determined specific algorithms, this project relied on the uniquely structured, highly performant underlying time series database capabilities of the PredictiveGrid platform to assess the vast dataset utilizing a wide variety of algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Combinatorial Membrane Synthesis: Fundamentals of Hybrid Metal-Organic Brush (MOB) Membranes for Organic Solvent Nanofiltration (Renewal)

(a) Goals: The goals of our current 3-year research project are (i) expansion of the novel modification technique Single Electron Transfer- Living Radical Polymerization (SET-LRP) to graft polymer brushes on a polyimide stable support followed by characterization and testing of the ensuing membrane (ii) stiffen brush network utilizing (a) metal organic frameworks and (b) covalent bonds formed as a result of crosslinking the grafted brush network. (b) Approach: The approach taken for this research was: (i) to graft branches terminated with a carboxyl group on each bristle (or bristle branch) allowing (a) metal immobilization to form MOF-like structures between branches or (b) crosslink bristles using aliphatic or aromatic diamines; (ii) to test the performance of the membranes using organic dyes, pure solvents (alcohols) and industrially relevant organic solvent separations; and (iii) to characterize these modified brush membranes. (c) Findings: The significant findings from the past one year are summarized below (papers resulting from this work are listed below and in D. PUBLICATIONS and relevant references are found in E. REFERENCES.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combinatorial Glycomic Analyses to Direct CAZyme Discovery for the Tailored Degradation of Canola Meal Non-Starch Dietary Polysaccharides

Canola meal (CM), the protein-rich by-product of canola oil extraction, has shown promise as an alternative feedstuff and protein supplement in poultry diets, yet its use has been limited due to the abundance of plant cell wall fibre, specifically non-starch polysaccharides (NSP) and lignin. The addition of exogenous enzymes to promote the digestion of CM NSP in chickens has potential to increase the metabolizable energy of CM. We isolated chicken cecal bacteria from a continuous-flow mini-bioreactor system and selected for those with the ability to metabolize CM NSP. Of 100 isolates identified, Bacteroides spp. and Enterococcus spp. were the most common species with these capabilities. To identify enzymes specifically for the digestion of CM NSP, we used a combination of glycomics techniques, including enzyme-linked immunosorbent assay characterization of the plant cell wall fractions, glycosidic linkage analysis (methylation-GC-MS analysis) of CM NSP and their fractions, bacterial growth profiles using minimal media supplemented with CM NSP, and the sequencing and de novo annotation of bacterial genomes of high-efficiency CM NSP utilizing bacteria. The SACCHARIS pipeline was used to select plant cell wall active enzymes for recombinant production and characterization. This approach represents a multidisciplinary innovation platform to bioprospect endogenous CAZymes from the intestinal microbiota of herbivorous and omnivorous animals which is adaptable to a variety of applications and dietary polysaccharides.

glycome profiling↗

Estimation of the Chances to Find New Phenomena at the LHC in a Model-Agnostic Combinatorial Analysis

In this paper, we estimate the number of event topologies that have the potential to be produced in 𝑝𝑝 collisions at the Large Hadron Collider (LHC) without violating kinematic and other constraints. We use numerical calculations and combinatorics, guided by large-scale Monte Carlo simulations of Standard Model (SM) processes. Then, we set the upper limit on the probability that new physics may escape detection, assuming a model-agnostic approach. The calculated probability is unexpectedly large, and the fact that LHC has not found new physics until now is not entirely surprising. Theoretical limitations and experimental challenges in observing new physics within the studied exclusive event classes are examined.

BSM↗