Cascaded half-harmonic generation of femtosecond frequency combs in mid-IR

For the growing demand of frequency combs in mid-infrared (mid-IR), known as the "molecular fingerprint" region of the spectrum [1], down conversion of near-IR frequency combs through half- harmonic generation offers numerous benefits including high conversion efficiency and intrinsic phase and frequency locking to the near-IR pump [2]. Hence cascaded half-harmonic generation promises a simple path towards extending the wavelength coverage of stable frequency combs. Here, we report a two-octave down-conversion of a frequency comb around 1 {\mu}m through cascaded half-harmonic generation with ~64% efficiency in the first stage, and ~18% in the second stage. We obtain broadband intrinsically-frequency-locked frequency combs with ~50-fs pulses at ~2 {\mu}m and ~110-fs pulses at ~4 {\mu}m. These results indicate the effectiveness of half-harmonic generation as a universal tool for efficient phase- and frequency-locked down-conversion, which can be beneficial for numerous applications requiring long-wavelength coherent sources

Computationally Connecting Organic Photovoltaic Performance to Atomistic Arrangements and Bulk Morphology

Rationally designing roll-to-roll printed organic photovoltaics requires a fundamental understanding of active layer morphologies optimized for charge separation and transport, and which ingredients can be used to self-assemble those morphologies. In this review article we discuss advances in three areas of computational modeling that provide insight into active layer morphology and the charge transport properties that result. We explain the computational bottlenecks prohibiting atomistically-detailed simulations of device-scale active layers and the coarse-graining and hardware acceleration strategies for overcoming them. We review coarse-grained simulations of organic photovoltaic active layers and show that high throughput simulations of experimentally-relevant length scales are now accessible. We describe a new Python package diffractometer that permits grazing-incidence X-ray scattering patterns of simulated active layers to be compared against experiments. We explain the accurate calculation of charge-carrier mobilities from coarse-grained active layer morphologies by using atomistic backmapping, quantum chemical calculations, and kinetic Monte Carlo simulations. We employ these simulations to show that ordering of poly(3-hexylthiophene-2,5-diyl) explains a factor of 1000 improvement in charge mobility. In concert, we present a suite of computational tools enabling large-scale electronic properties of organic photovoltaics to be studied and screened for by molecular simulations

Self Assembled Clusters of Spheres Related to Spherical Codes

We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres, and free energy calculations to predict the expected cluster sizes and shapes as a function of temperature and inner particle diameter. We show that the arrangements of outer spheres at finite temperatures are related to spherical codes, an ideal mathematical sequence of points corresponding to densest possible sphere packings. We demonstrate that temperature and the ratio of the diameters of the inner and outer spheres dictate cluster morphology and dynamics. We find that some N-clusters exhibit collective particle rearrangements, and these collective modes are unique to a given cluster size N. We present a surprising result for the equilibrium structure of a 5-cluster, which prefers an asymmetric square pyramid arrangement over a more symmetric arrangement. Our results suggest a promising way to assemble anisotropic building blocks from constituent colloidal spheres.Comment: 15 pages, 10 figure

Nonlinear Machine Learning and Design of Reconfigurable Digital Colloids

Digital colloids, a cluster of freely rotating “halo particles tethered to the surface of a central particle, were recently proposed as ultra-high density memory elements for information storage. Rational design of these digital colloids for memory storage applications requires a quantitative understanding of the thermodynamic and kinetic stability of the configurational states within which information is stored. We apply nonlinear machine learning to Brownian dynamics simulations of these digital colloids to extract the low-dimensional intrinsic manifold governing digital colloid morphology, thermodynamics, and kinetics. By modulating the relative size ratio between halo particles and central particles, we investigate the size-dependent configurational stability and transition kinetics for the 2-state tetrahedral (N=4) and 30-state octahedral (N=6) digital colloids. We demonstrate the use of this framework to guide the rational design of a memory storage element to hold a block of text that trades off the competing design criteria of memory addressability and volatility

Natural Resource Monitoring Progression of Forest Park’s Forested Natural Areas in St. Louis, Missouri

St. Louis City, MO had 121 acres managed as woodland or forested natural areas: 98 acres in Forest Park and 13 acres in O’Fallon Park. In Forest Park, standardized Missouri forest vegetation monitoring plots were started in 1993 to develop and guide habitat management such as thinning, species richness development, etc. In 2018 and 2019, a holistic Natural Resources Management Plan (NRMP) for Forest Park provided additional recommended metrics and monitoring, some of which have already begun implementation

Restoration and Management of High-Use Urban Missouri Woodlands and Forests in St. Louis

St. Louis City’s urban woodland and forested natural areas were modified, degraded, and/or overly-mature habitats requiring management intervention for ecological health, species diversity, and public safety. To accomplish long-term success in Forest Park’s woodlands and forests, restorations and management strategies seeking to “treat the problem not the symptom” was implemented. The most important best management practices for Forest Park’s woodlands and forests included forest stand improvement, prescribed burns, invasive and non-native species management, creation of public stewards, and plant material supplementation

Mrgprd Enhances Excitability in Specific Populations of Cutaneous Murine Polymodal Nociceptors

The Mas-related G protein-coupled receptor D (Mrgprd) is selectively expressed in nonpeptidergic nociceptors that innervate the outer layers of mammalian skin. The function of Mrgprd in nociceptive neurons and the physiologically relevant somatosensory stimuli that activate Mrgprd^-expressing (Mrgprd^+) neurons are currently unknown. To address these issues, we studied three Mrgprd knock-in mouse lines using an ex vivo somatosensory preparation to examine the role of the Mrgprd receptor and Mrgprd+ afferents in cutaneous somatosensation. In mouse hairy skin, Mrgprd, as marked by expression of green fluorescent protein reporters, was expressed predominantly in the population of nonpeptidergic, TRPV1-negative, C-polymodal nociceptors. In mice lacking Mrgprd, this population of nociceptors exhibited decreased sensitivity to cold, heat, and mechanical stimuli. Additionally, in vitro patch-clamp studies were performed on cultured dorsal root ganglion neurons from Mrgprd^(–/–) and Mrgprd^(+/–) mice. These studies revealed a higher rheobase in neurons from Mrgprd^(–/–) mice than from Mrgprd^(+/–) mice. Furthermore, the application of the Mrgprd ligand β-alanine significantly reduced the rheobase and increased the firing rate in neurons from Mrgprd^(+/–) mice but was without effect in neurons from Mrgprd^(–/–) mice. Our results demonstrate that Mrgprd influences the excitability of polymodal nonpeptidergic nociceptors to mechanical and thermal stimuli