Inflatable Re-entry Vehicle Experiment (IRVE-4) Overview

The suite of Inflatable Re-Entry Vehicle Experiments (IRVE) is designed to further our knowledge and understanding of Hypersonic Inflatable Aerodynamic Decelerators (HIADs). Before infusion into a future mission, three challenges need to be addressed: surviving the heat pulse during re-entry, demonstrating system performance at relevant scales, and demonstrating controllability in the atmosphere. IRVE-4 will contribute to a better understanding of controllability by characterizing how a HIAD responds to a set of controlled inputs. The ability to control a HIAD is vital for missions that are g-limited, require precision targeting and guidance for aerocapture or entry, descent, and landing. The IRVE-4 flight test will focus on taking a first look into controlling a HIAD. This paper will give an overview of the IRVE-4 mission including the control response portion of the flight test sequence, and will provide a review of the mission s development

Precise implications for real-space pair distribution function modeling of effects intrinsic to modern time-of-flight neutron diffractometers

Total scattering and pair distribution function (PDF) methods allow for detailed study of local atomic order and disorder, including materials for which Rietveld refinements are not traditionally possible (amorphous materials, liquids, glasses and nanoparticles). With the advent of modern neutron time-of-flight (TOF) instrumentation, total scattering studies are capable of producing PDFs with ranges upwards of 100–200 Å, covering the correlation length scales of interest for many materials under study. Despite this, the refinement and subsequent analysis of data are often limited by confounding factors that are not rigorously accounted for in conventional analysis programs. While many of these artifacts are known and recognized by experts in the field, their effects and any associated mitigation strategies largely exist as passed-down `tribal' knowledge in the community, and have not been concisely demonstrated and compared in a unified presentation. This article aims to explicitly demonstrate, through reviews of previous literature, simulated analysis and real-world case studies, the effects of resolution, binning, bounds, peak shape, peak asymmetry, inconsistent conversion of TOF to d spacing and merging of multiple banks in neutron TOF data as they directly relate to real-space PDF analysis. Suggestions for best practice in analysis of data from modern neutron TOF total scattering instruments when using conventional analysis programs are made, as well as recommendations for improved analysis methods and future instrument design

Precise implications for real-space pair distribution function modeling of effects intrinsic to modern time-of-flight neutron diffractometers

Total scattering and pair distribution function (PDF) methods allow for detailed study of local atomic order and disorder, including materials for which Rietveld refinements are not traditionally possible (amorphous materials, liquids, glasses and nanoparticles). With the advent of modern neutron time-of-flight (TOF) instrumentation, total scattering studies are capable of producing PDFs with ranges upwards of 100–200 Å, covering the correlation length scales of interest for many materials under study. Despite this, the refinement and subsequent analysis of data are often limited by confounding factors that are not rigorously accounted for in conventional analysis programs. While many of these artifacts are known and recognized by experts in the field, their effects and any associated mitigation strategies largely exist as passed-down `tribal' knowledge in the community, and have not been concisely demonstrated and compared in a unified presentation. This article aims to explicitly demonstrate, through reviews of previous literature, simulated analysis and real-world case studies, the effects of resolution, binning, bounds, peak shape, peak asymmetry, inconsistent conversion of TOF to d spacing and merging of multiple banks in neutron TOF data as they directly relate to real-space PDF analysis. Suggestions for best practice in analysis of data from modern neutron TOF total scattering instruments when using conventional analysis programs are made, as well as recommendations for improved analysis methods and future instrument design

Self-driving Multimodal Studies at User Facilities

Multimodal characterization is commonly required for understanding materials. User facilities possess the infrastructure to perform these measurements, albeit in serial over days to months. In this paper, we describe a unified multimodal measurement of a single sample library at distant instruments, driven by a concert of distributed agents that use analysis from each modality to inform the direction of the other in real time. Powered by the Bluesky project at the National Synchrotron Light Source II, this experiment is a world's first for beamline science, and provides a blueprint for future approaches to multimodal and multifidelity experiments at user facilities.Comment: 36th Conference on Neural Information Processing Systems (NeurIPS 2022). AI4Mat Worksho

Crystallography companion agent for high-throughput materials discovery

The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time-consuming, error-prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications -- rather than absolutes -- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering significant time savings. It was demonstrated on a diverse set of organic and inorganic materials characterization challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.Comment: For associated code, see https://github.com/maffettone/xc

Draft Genome Sequence of "Candidatus Phytoplasma oryzae" Strain Mbita1, the Causative Agent of Napier Grass Stunt Disease in Kenya.

Phytoplasmas are bacterial plant pathogens with devastating impact on agricultural production worldwide. In eastern Africa, Napier grass stunt disease causes serious economic losses in the smallholder dairy industry. This draft genome sequence of " ITALIC! CandidatusPhytoplasma oryzae" strain Mbita1 provides insight into its genomic organization and the molecular basis of pathogenicity

Help when it's needed first: A controlled evaluation of brief, preventive behavioral family intervention in a primary care setting

This study evaluated the effects of a brief 3- to 4-session behavioral family intervention program for parents of preschool-aged children in a primary care setting, compared to parents in a wait-list control condition. Parents receiving the Primary Care Triple P-Positive Parenting Program intervention reported significantly lower levels of targeted child behavior problems, dysfunctional parenting, and reduced parental anxiety and stress in comparison to wait-listed parents at postassessment. These short-term effects were largely maintained at 6-month follow-up assessment of the intervention group. Implications of these findings for the prevention of behavioral and emotional problems in children are discussed