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1. Using a machine learning approach to determine the space group of a structure from the atomic pair distribution function

   https://doi.org/10.1107/S2053273319005606  

   Liu, Chia-Hao ; Tao, Yunzhe ; Hsu, Daniel ; Du, Qiang ; Billinge, Simon J. ( July 2019 , Acta Crystallographica Section A Foundations and Advances)

   A method is presented for predicting the space group of a structure given a calculated or measured atomic pair distribution function (PDF) from that structure. The method utilizes machine learning models trained on more than 100 000 PDFs calculated from structures in the 45 most heavily represented space groups. In particular, a convolutional neural network (CNN) model is presented which yields a promising result in that it correctly identifies the space group among the top-6 estimates 91.9% of the time. The CNN model also successfully identifies space groups for 12 out of 15 experimental PDFs. Interesting aspects of the failed estimates are discussed, which indicate that the CNN is failing in similar ways as conventional indexing algorithms applied to conventional powder diffraction data. This preliminary success of the CNN model shows the possibility of model-independent assessment of PDF data on a wide class of materials. 

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2. A new method for in situ structural investigations of nano-sized amorphous and crystalline materials using mixed-flow reactors

   https://doi.org/10.1107/S2053273319008623  

   Hoeher, Alexandria ; Mergelsberg, Sebastian ; Borkiewicz, Olaf J. ; Dove, Patricia M. ; Michel, F. Marc ( September 2019 , Acta Crystallographica Section A Foundations and Advances)

   Structural investigations of amorphous and nanocrystalline phases forming in solution are historically challenging. Few methods are capable of in situ atomic structural analysis and rigorous control of the system. A mixed-flow reactor (MFR) is used for total X-ray scattering experiments to examine the short- and long-range structure of phases in situ with pair distribution function (PDF) analysis. The adaptable experimental setup enables data collection for a range of different system chemistries, initial supersaturations and residence times. The age of the sample during analysis is controlled by adjusting the flow rate. Faster rates allow for younger samples to be examined, but if flow is too fast not enough data are acquired to average out excess signal noise. Slower flow rates form older samples, but at very slow speeds particles settle and block flow, clogging the system. Proper background collection and subtraction is critical for data optimization. Overall, this MFR method is an ideal scheme for analyzing the in situ structures of phases that form during crystal growth in solution. As a proof of concept, high-resolution total X-ray scattering data of amorphous and crystalline calcium phosphates and amorphous calcium carbonate were collected for PDF analysis. 

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3. Symmetry-mode analysis for local structure investigations using pair distribution function data

   https://doi.org/10.1107/S1600576723005794  

   Hamilton, Parker K. ; Moya, Jaime M. ; Hallas, Alannah M. ; Morosan, E. ; Baral, Raju ; Frandsen, Benjamin A. ( August 2023 , Journal of Applied Crystallography)

   Symmetry-adapted distortion modes provide a natural way of describing distorted structures derived from higher-symmetry parent phases. Structural refinements using symmetry-mode amplitudes as fit variables have been used for at least ten years in Rietveld refinements of the average crystal structure from diffraction data; more recently, this approach has also been used for investigations of the local structure using real-space pair distribution function (PDF) data. Here, the value of performing symmetry-mode fits to PDF data is further demonstrated through the successful application of this method to two topical materials: TiSe 2 , where a subtle but long-range structural distortion driven by the formation of a charge-density wave is detected, and MnTe, where a large but highly localized structural distortion is characterized in terms of symmetry-lowering displacements of the Te atoms. The analysis is performed using fully open-source code within the DiffPy framework via two packages developed for this work: isopydistort , which provides a scriptable interface to the ISODISTORT web application for group theoretical calculations, and isopytools , which converts the ISODISTORT output into a DiffPy -compatible format for subsequent fitting and analysis. These developments expand the potential impact of symmetry-adapted PDF analysis by enabling high-throughput analysis and removing the need for any commercial software. 

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4. Characterising the atomic structure of mono-metallic nanoparticles from x-ray scattering data using conditional generative models

   https://doi.org/10.26434/chemrxiv.12662222.v1  

   Anker, Andy S. ; Kjaer, Emil T. ; Dam, Erik B. ; Billinge, Simon J. ; Jensen, Kirsten M. ; Selvan, Raghavendra ( July 2020 , ChemRxiv)

   null (Ed.)

   The development of new nanomaterials for energy technologies is dependent on understanding the intricate relation between material properties and atomic structure. It is, therefore, crucial to be able to routinely characterise the atomic structure in nanomaterials, and a promising method for this task is Pair Distribution Function (PDF) analysis. The PDF can be obtained through Fourier transformation of x-ray total scattering data, and represents a histogram of all interatomic distances in the sample. Going from the distance information in the PDF to a chemical structure is an unassigned distance geometry problem (uDGP), and solving this is often the bottleneck in nanostructure analysis. In this work, we propose to use a Conditional Variational Autoencoder (CVAE) to automatically solve the uDGP to obtain valid chemical structures from PDFs. We use a simple model system of hypothetical mono-metallic nanoparticles containing up to 100 atoms in the face centered cubic (FCC) structure as a proof of concept. The model is trained to predict the assigned distance matrix (aDM) from a simulated PDF of the structure as the conditional input. We introduce a novel representation of structures by projecting them inside a unit sphere and adding additional anchor points or satellites to help in the reconstruction of the chemical structure. The performance of the CVAE model is compared to a Deterministic Autoencoder (DAE) showing that both models are able to solve the uDGP reasonably well. We further show that the CVAE learns a structured and meaningful latent embedding space which can be used to predict new chemical structures. 

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5. CHIIMP : An automated high‐throughput microsatellite genotyping platform reveals greater allelic diversity in wild chimpanzees

   https://doi.org/10.1002/ece3.4302  

   Barbian, Hannah J. ; Connell, Andrew Jesse ; Avitto, Alexa N. ; Russell, Ronnie M. ; Smith, Andrew G. ; Gundlapally, Madhurima S. ; Shazad, Alexander L. ; Li, Yingying ; Bibollet‐Ruche, Frederic ; Wroblewski, Emily E. ; et al ( July 2018 , Ecology and Evolution)

   Short tandem repeats (STRs), also known as microsatellites, are commonly used to noninvasively genotype wild‐living endangered species, including African apes. Until recently, capillary electrophoresis has been the method of choice to determine the length of polymorphicSTRloci. However, this technique is labor intensive, difficult to compare across platforms, and notoriously imprecise. Here we developed a MiSeq‐based approach and tested its performance using previously genotyped fecal samples from long‐term studied chimpanzees in Gombe National Park, Tanzania. Using data from eight microsatellite loci as a reference, we designed a bioinformatics platform that converts raw MiSeq reads into locus‐specific files and automatically calls alleles after filtering stutter sequences and otherPCRartifacts. Applying this method to the entire Gombe population, we confirmed previously reported genotypes, but also identified 31 new alleles that had been missed due to sequence differences and size homoplasy. The new genotypes, which increased the allelic diversity and heterozygosity in Gombe by 61% and 8%, respectively, were validated by replicate amplification and pedigree analyses. This demonstrated inheritance and resolved one case of an ambiguous paternity. Using both singleplex and multiplex locus amplification, we also genotyped fecal samples from chimpanzees in the Greater Mahale Ecosystem in Tanzania, demonstrating the utility of the MiSeq‐based approach for genotyping nonhabituated populations and performing comparative analyses across field sites. The new automated high‐throughput analysis platform (available athttps://github.com/ShawHahnLab/chiimp) will allow biologists to more accurately and effectively determine wildlife population size and structure, and thus obtain information critical for conservation efforts.

    

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