Solid-state NMR and DNP-Enhanced Solid-state NMR Analysis of Sustainable Materials

In the drive for more sustainable chemistry, a thorough understanding of the relationship between the structure and properties of any given product is essential. Molecular level characterization is key for optimization of desired properties and synthesis. For many materials, this can be done with high-resolution solution-state techniques or X-ray crystallography. However, to fully understand their structural-property relationships, materials must be studied in the state in which they will be used. Often this state is not amenable to these techniques. In these cases, solid-state NMR provides this vital information. In this work, solid-state NMR analysis has been applied to two classes of materials. Firstly, solid-state NMR was used to probe the defects in hybrid organic-inorganic perovskite materials with potential applications in solar cells. Structural defects in these materials can improve their function but also reduce their stability. To make these perovskite solar cells commercially viable, a thorough understanding of the relationship between the material properties and the dynamics and structural differences caused by these defects is essential. Static and MAS variable temperature 1H NMR has been used to identify possible diffusion of protonic defects in MAPbI3. The second class of materials studied were polymers. For these materials, dynamic nuclear polarization (DNP) enhanced solid-state NMR was used. The low sensitivity of NMR limits its capability to analyse intrinsically dilute aspects of high molecular weight polymers, such as cross-links, chain-ends, and interfaces. DNP-enhanced solid-state NMR has not had the same impact on polymer analysis as it has in biological and materials science. This may be attributed to the discouragingly low enhancements seen and difficult sample handling encountered when using traditional DNP methods on polymers. In this work, the benefits, and disadvantages of two sample impregnation methods for polymer DNP have been shown. Additional benefits of polymer DNP have also been demonstrated. Beyond a simple sensitivity enhancement, DNP has been shown to provide insight to the dynamics of polymer chains and functional groups

Solid-state NMR and DNP-Enhanced Solid-state NMR Analysis of Sustainable Materials

In the drive for more sustainable chemistry, a thorough understanding of the relationship between the structure and properties of any given product is essential. Molecular level characterization is key for optimization of desired properties and synthesis. For many materials, this can be done with high-resolution solution-state techniques or X-ray crystallography. However, to fully understand their structural-property relationships, materials must be studied in the state in which they will be used. Often this state is not amenable to these techniques. In these cases, solid-state NMR provides this vital information. In this work, solid-state NMR analysis has been applied to two classes of materials. Firstly, solid-state NMR was used to probe the defects in hybrid organic-inorganic perovskite materials with potential applications in solar cells. Structural defects in these materials can improve their function but also reduce their stability. To make these perovskite solar cells commercially viable, a thorough understanding of the relationship between the material properties and the dynamics and structural differences caused by these defects is essential. Static and MAS variable temperature 1H NMR has been used to identify possible diffusion of protonic defects in MAPbI3. The second class of materials studied were polymers. For these materials, dynamic nuclear polarization (DNP) enhanced solid-state NMR was used. The low sensitivity of NMR limits its capability to analyse intrinsically dilute aspects of high molecular weight polymers, such as cross-links, chain-ends, and interfaces. DNP-enhanced solid-state NMR has not had the same impact on polymer analysis as it has in biological and materials science. This may be attributed to the discouragingly low enhancements seen and difficult sample handling encountered when using traditional DNP methods on polymers. In this work, the benefits, and disadvantages of two sample impregnation methods for polymer DNP have been shown. Additional benefits of polymer DNP have also been demonstrated. Beyond a simple sensitivity enhancement, DNP has been shown to provide insight to the dynamics of polymer chains and functional groups

A map of human genome variation from population-scale sequencing

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10−8 per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic researc