Local Structural Determination in Strained-Layer Semiconductors

The theory of elasticity accurately describes the deformations of macroscopic bodies under the action of applied stress. In this lecture I will examine the internal mechanisms of elasticity for strained-layer semiconductor heterostructures. In particular, I will present extended x-ray absorption fine structure (EXAFS) and x-ray diffraction (XRD) measurements to show how bond lengths and bond angles change with strain and compare with various theoretical models. These synchrotron-based experimental techniques and their application to thin films will be developed in detail

Enhanced electron correlations at the SrxCa1-xVO3 surface

We report hard x-ray photoemission spectroscopy measurements of the electronic structure of the prototypical correlated oxide SrxCa1-xVO3. By comparing spectra recorded at different excitation energies, we show that 2.2 keV photoelectrons contain a substantial surface component, whereas 4.2 keV photoelectrons originate essentially from the bulk of the sample. Bulk-sensitive measurements of the O 2p valence band are found to be in good agreement with ab initio calculations of the electronic structure, with some modest adjustments to the orbital-dependent photoionization cross sections. The evolution of the O 2p electronic structure as a function of the Sr content is dominated by A-site hybridization. Near the Fermi level, the correlated V 3d Hubbard bands are found to evolve in both binding energy and spectral weight as a function of distance from the vacuum interface, revealing higher correlation at the surface than in the bulk

Local Structure and It's Effect on The Ferromagnetic Properties of La0.5_{0.5}Sr0.5_{0.5}CoO3_3 thin films}

We have used high-resolution Extended X-ray Absorption Fine-Structure and diffraction techniques to measure the local structure of strained La$_{0.5}$Sr$_{0.5}$CoO$_3$ films under compression and tension. The lattice mismatch strain in these compounds affects both the bond lengths and the bond angles, though the larger effect on the bandwidth is due to the bond length changes. The popular double exchange model for ferromagnetism in these compounds provides a correct qualitative description of the changes in Curie temperature $T_C$, but quantitatively underestimates the changes. A microscopic model for ferromagnetism that provides a much stronger dependence on the structural distortions is needed.Comment: 4 pages, 4 figure

BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction

Language models pre-trained on scientific literature corpora have substantially advanced scientific discovery by offering high-quality feature representations for downstream applications. However, these features are often not interpretable, and thus can reveal limited insights to domain experts. Instead of obtaining features from language models, we propose BLIAM, a literature-based data synthesis approach to directly generate training data points that are interpretable and model-agnostic to downstream applications. The key idea of BLIAM is to create prompts using existing training data and then use these prompts to synthesize new data points. BLIAM performs these two steps iteratively as new data points will define more informative prompts and new prompts will in turn synthesize more accurate data points. Notably, literature-based data augmentation might introduce data leakage since labels of test data points in downstream applications might have already been mentioned in the language model corpus. To prevent such leakage, we introduce GDSC-combo, a large-scale drug combination discovery dataset that was published after the biomedical language model was trained. We found that BLIAM substantially outperforms a non-augmented approach and manual prompting in this rigorous data split setting. BLIAM can be further used to synthesize data points for novel drugs and cell lines that were not even measured in biomedical experiments. In addition to the promising prediction performance, the data points synthesized by BLIAM are interpretable and model-agnostic, enabling in silico augmentation for in vitro experiments