Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Ecological Planting Imperative: Functional Systems,Not Stylized Ecologies

The ability of landscape architectural projects to mitigate the worst effects of climate change will depend upon designed ecological systems. These systems will be built with plants. Despite the recognition of ecology as an essential driver of landscapes, the professionals of landscape architecture too often lack the knowledge and practical skills to create robust vegetative systems. New approaches and tools are required. This article outlines principles and methods for designing biodiverse plant systems for urban sites. Planting methods that increase species richness, functional diversity, and spatial complexity are emphasized as a way of developing more resilient plantings. Selecting species with similar evolutionary adaptions to stress, disturbance, and competition—as well as creating multi-layered compositions of diverse plant morphologies—allows designers to create compatible, long-lived plant mixes. To balance the increased visual complexity of diverse plant mixes, the article explores design techniques to make plantings more appealing to the public. The strategies explored here are based on the projects, experience, and research of Phyto Studio, a Washington, D.C. based studio. The methods build on work described in the author’s book, Planting in a Post-Wild World, an exploration of how to create designed plant communities.     

Full AC analysis of value of DER to the grid and optimal DER scheduling

This paper presents part of the work ComEd and Quanta Technology have performed to quantify the locational and temporal value of DER to avoid distribution grid upgrade investments. It focuses on the formulation of a robust and efficient algorithm for DER optimal dispatch on a distribution feeder to mitigate the violation of current and voltage limits using the allocated cost of capacity and locational marginal value of real and reactive DER injection/withdrawal.     

Discovery of GPR183 Agonists Based on an Antagonist Scaffold

The G protein-coupled receptor GPR183/EBI2, which is activated by oxysterols, is a therapeutic target for inflammatory and metabolic diseases where both antagonists and agonists are of potential interest. Using the piperazine diamide core of the known GPR183 antagonist (E)-3-(4-bromophenyl)-1-(4-(4-methoxybenzoyl)piperazin-1-yl)prop-2-en-1-one (NIBR189) as starting point, we identified and sourced 79 structurally related compounds that were commercially available. In vitro screening of this compound collection using a Ca²⁺ mobilization assay resulted in the identification of 10 compounds with agonist properties. To enable establishment of initial structure-activity relationship trends, these were supplemented with five in-house compounds, two of which were also shown to be GPR183 agonists. Taken together, our findings suggest that the agonist activity of this compound series is dictated by the substitution pattern of one of the two distal phenyl rings, which functions as a molecular efficacy-switch.     

Ratiometric Detection of Glutathione Based on Disulfide Linkage Rupture between a FRET Coumarin Donor and a Rhodamine Acceptor

Abnormal levels of glutathione, a cellular antioxidant, can lead to a variety of diseases. We have constructed a near-infrared ratiometric fluorescent probe to detect glutathione concentrations in biological samples. The probe consists of a coumarin donor, which is connected through a disulfide-tethered linker to a rhodamine acceptor. Under the excitation of the coumarin donor at 405 nm, the probe shows weak visible fluorescence of the coumarin donor at 470 nm and strong near-infrared fluorescence of the rhodamine acceptor at 652 nm due to efficient Forster resonance energy transfer (FRET) from the donor to the acceptor. Glutathione breaks the disulfide bond through reduction, which results in a dramatic increase in coumarin fluorescence and a corresponding decrease in rhodamine fluorescence. The probe possesses excellent cell permeability, biocompatibility, and good ratiometric fluorescence responses to glutathione and cysteine with a self-calibration capability. The probe was utilized to ratiometrically visualize glutathione concentration alterations in HeLa cells and Drosophila melanogaster larvae.     

In Vivo Albumin-Binding of a C-Functionalized Cyclam Platform for 64Cu-PET/CT Imaging in Breast Cancer Model

An improved glucose-chelator-albumin bioconjugate (GluCAB) derivative, GluCAB-2^Mal, has been synthesized and studied for in vivo ⁶⁴Cu-PET/CT imaging in breast cancer mice models together with its first-generation analogue GluCAB-1^Mal. The radioligand works on the principle of tumor targeting through the enhanced permeability and retention (EPR) effect with a supportive role played by glucose metabolism. [⁶⁴Cu]Cu-GluCAB-2^Mal (99 % RCP) exhibited high serum stability with immediate binding to serum proteins. In vivo experiments for comparison between tumor targeting of [⁶⁴Cu]Cu-GluCAB-2^Mal and previous-generation [⁶⁴Cu]Cu-GluCAB-1^Mal encompassed microPET/CT imaging and biodistribution analysis in an allograft E0771 breast cancer mouse model. Tumor uptake of [⁶⁴Cu]Cu-GluCAB-2^Mal was clearly evident with twice as much accumulation as compared to its predecessor and a tumor/muscle ratio of up to 5 after 24 h. Further comparison indicated a decrease in liver accumulation for [⁶⁴Cu]Cu-Glu-CAB-2^Mal.     

Environmental effects on the strength and impact damage resistance of alumina based oxide/oxide ceramic matrix composites

In this study the effects of high temperature and moisture on the impact damage resistance and mechanical strength of Nextel 610/alumina silicate ceramic matrix composites were experimentally evaluated. Composite laminates were exposed to either a 1050°C isothermal furnace-based environment for 30 consecutive days at 6 h a day, or 95% relative humidity environment for 13 consecutive days at 67°C. Low velocity impact, tensile and short beam strength tests were performed on both ambient and environmentally conditioned laminates and damage was characterized using a combination of non-destructive and destructive techniques. High temperature and humidity environmental exposure adversely affected the impact resistance of the composite laminates. For all the environments, planar internal damage area was greater than the back side dent area, which in turn was greater than the impactor side dent area. Evidence of environmental embrittlement through a stiffer tensile response was noted for the high temperature exposed laminates while the short beam strength tests showed greater propensity for interlaminar shear failure in the moisture exposed laminates. Destructive evaluations exposed larger, more pronounced delaminations in the environmentally conditioned laminates in comparison to the ambient ones. External damage metrics of the impactor side dent depth and area directly influenced the post-impact tensile strength of the laminates while no such trend between internal damage area and residual strength could be ascertained.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.