Upper bounds on absorption and scattering

A general framework for determining fundamental bounds in nanophotonics is introduced in this paper. The theory is based on convex optimization of dual problems constructed from operators generated by electromagnetic integral equations. The optimized variable is a contrast current defined within a prescribed region of a given material constitutive relations. Two power conservation constraints analogous to optical theorem are utilized to tighten the bounds and to prescribe either losses or material properties. Thanks to the utilization of matrix rank-1 updates, modal decompositions, and model order reduction techniques, the optimization procedure is computationally efficient even for complicated scenarios. No dual gaps are observed. The method is well-suited to accommodate material anisotropy and inhomogeneity. To demonstrate the validity of the method, bounds on scattering, absorption, and extinction cross sections are derived first and evaluated for several canonical regions. The tightness of the bounds is verified by comparison to optimized spherical nanoparticles and shells. The next metric investigated is bi-directional scattering studied closely on a particular example of an electrically thin slab. Finally, the bounds are established for Purcell's factor and local field enhancement where a dimer is used as a practical example.Comment: 38 pages, 16 figure

Conversion Matrix Method of Moments for Time-Varying Electromagnetic Analysis

A conversion matrix approach to solving network problems involving time-varying circuit components is applied to the method of moments for electromagnetic scattering analysis. Detailed formulations of this technique's application to the scattering analysis of structures loaded with time-varying circuit networks or constructed from general time-varying media are presented. The computational cost of the method is discussed, along with an analysis of compression techniques capable of significantly reducing computational cost for partially loaded systems. Several numerical examples demonstrate the capabilities of the technique along with its validation against conventional methods of modeling time-varying electromagnetic systems, such as finite difference time domain and transient circuit co-simulation.Comment: 11 pages, 11 figure

1,10-Bis(4-nitro­phen­oxy)deca­ne

The title compound, C22H28N2O6, crystallizes with four half-mol­ecules in the asymmetric unit: each mol­ecule is located about a crystallographic inversion centre. The central methyl­ene groups of two mol­ecules are disordered over two sets of equally occupied sites. The crystal packing is characterized by sheets of mol­ecules parallel to (14)

Induction of viral mimicry upon loss of DHX9 and ADAR1 in breast cancer cells

UNLABELLED: Detection of viral double-stranded RNA (dsRNA) is an important component of innate immunity. However, many endogenous RNAs containing double-stranded regions can be misrecognized and activate innate immunity. The IFN-inducible ADAR1-p150 suppresses dsRNA sensing, an essential function for adenosine deaminase acting on RNA 1 (ADAR1) in many cancers, including breast. Although ADAR1-p150 has been well established in this role, the functions of the constitutively expressed ADAR1-p110 isoform are less understood. We used proximity labeling to identify putative ADAR1-p110-interacting proteins in breast cancer cell lines. Of the proteins identified, the RNA helicase DHX9 was of particular interest. Knockdown of DHX9 in ADAR1-dependent cell lines caused cell death and activation of the dsRNA sensor PKR. In ADAR1-independent cell lines, combined knockdown of DHX9 and ADAR1, but neither alone, caused activation of multiple dsRNA sensing pathways leading to a viral mimicry phenotype. Together, these results reveal an important role for DHX9 in suppressing dsRNA sensing by multiple pathways. SIGNIFICANCE: These findings implicate DHX9 as a suppressor of dsRNA sensing. In some cell lines, loss of DHX9 alone is sufficient to cause activation of dsRNA sensing pathways, while in other cell lines DHX9 functions redundantly with ADAR1 to suppress pathway activation

1,5-Bis(4-nitro­phen­oxy)penta­ne

The title compound, C17H18N2O6, crystallizes with two mol­ecules in the asymmetric unit. In both molecules, one of the C—C bonds of the penta­methyl­ene chain connecting the two aromatic rings is in a trans conformation and another displays a gauche conformation. The aromatic rings within each mol­ecule are nearly coplanar [dihedral angles = 3.36 (9) and 4.50 (9)°] and the nitro groups are twisted slightly out of the planes of their attached rings [dihedral angles = 8.16 (3)/6.6 (2) and 4.9 (4)/3.8 (3)°]

4-(4-Nitro­phen­oxy)butanol

The crystal structure of the title compound, C10H13NO4, features inter­molecular O—H⋯O(nitro) hydrogen bonding, which links mol­ecules into supra­molecular chains running parallel to the bc diagonal. There is also π–π stacking between 4-nitro­phenyl groups, the inter­planar distance between the nitro­benzene rings being 3.472 (2) Å

6-(4-Nitro­phen­oxy)hexa­nol

The title compound, C12H17NO4, features an almost planar mol­ecule (r.m.s. deviation for all non-H atoms = 0.070 Å). All methyl­ene C—C bonds adopt an anti­periplanar conformation. In the crystal structure the mol­ecules lie in planes parallel to (12) and the packing is stabilized by O—H⋯O hydrogen bonds

Benchmark problem definition and cross-validation for characteristic mode solvers

In October 2016, the Special Interest Group on Theory of Characteristic Modes (TCM) initiated a coordinated effort to perform benchmarking work for characteristic mode (CM) analysis. The primary purpose is to help improve the reliability and capability of existing CM solvers and to provide the means for validating future tools. Significant progress has already been made in this joint activity. In particular, this paper describes several benchmark problems that were defined and analyzes some results from the cross-validations of different CM solvers using these problems. The results show that despite differences in the implementation details, good agreement is observed in the calculated eigenvalues and eigencurrents across the solvers. Finally, it is concluded that future work should focus on understanding the impact of common parameters and output settings to further reduce variability in the results