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Sum frequency generation (SFG) necessitates both noncentrosymmetry and coherence over multiple length scales. These requirements make vibrational SFG spectroscopy capable of probing structural information of noncentrosymmetric organic crystals interspersed in polymeric matrices and their three-dimensional spatial distributions within the matrices without spectral interferences from the amorphous components. However, this analysis is not as straightforward as simple vibrational spectroscopy or scattering experiments; it requires knowing the molecular hyperpolarizability of SFG-active vibrational modes and their interplay within the coherence length. This study demonstrates how density function theory (DFT) calculations can be used to construct the molecular hyperpolarizability of a model system and combine it with the SFG theory to predict the polarization and azimuth angle dependences of SFG intensities. A model system with short peptide chains mimicking β-sheet domains in Bombyx mori silk was chosen. SFG signals of the amide-I, II, III, and A bands and one of the CH deformation modes were simulated and compared with the experimental results and the predictions from the group theory. The SFG features of amide-I and A bands of antiparallel β-sheet could be explained with DFT-based theoretical calculations. Although vibrational coupling with neighboring groups breaks the symmetry of the D2 point group, the group theory approach and DFT calculations gave similar results for the amide-I mode. The DFT calculation results for amide-II did not match with experimental data, which suggested vibrational coupling within a larger crystalline domain may dominate the SFG spectral features of these modes. This methodology can be applied to the structural analysis of other biopolymers. 

Recent studies have reported the experimental discovery that nanoscale specimens of even a natural material, such as diamond, can be deformed elastically to as much as 10% tensile elastic strain at room temperature without the onset of permanent damage or fracture. Computational work combining ab initio calculations and machine learning (ML) algorithms has further demonstrated that the bandgap of diamond can be altered significantly purely by reversible elastic straining. These findings open up unprecedented possibilities for designing materials and devices with extreme physical properties and performance characteristics for a variety of technological applications. However, a general scientific framework to guide the design of engineering materials through such elastic strain engineering (ESE) has not yet been developed. By combining first-principles calculations with ML, we present here a general approach to map out the entire phonon stability boundary in six-dimensional strain space, which can guide the ESE of a material without phase transitions. We focus on ESE of vibrational properties, including harmonic phonon dispersions, nonlinear phonon scattering, and thermal conductivity. While the framework presented here can be applied to any material, we show as an example demonstration that the room-temperature lattice thermal conductivity of diamond can be increased by more than 100% or reduced by more than 95% purely by ESE, without triggering phonon instabilities. Such a framework opens the door for tailoring of thermal-barrier, thermoelectric, and electro-optical properties of materials and devices through the purposeful design of homogeneous or inhomogeneous strains. 

Abstract Nitrogen (N) doped graphene materials have been synthesized using the sole precursor adenine on the Ir(111) and Ru(0001) surfaces. X-ray photoelectron spectroscopy and scanning tunneling microscopy (STM) have been used to characterize the obtained N-doped graphene materials. Several graphitic and pyridinic N dopants have been identified on the atomic scale by combining STM measurements and STM simulations based on density functional theory calculations. 

There is a cohesive body of research on the effectiveness of problem-based learning (PBL) for a wide range of learner groups across different disciplines in engineering education. On the other hand, there is a growing interest in using immersive technologies such as virtual reality (VR) in engineering education. While there are many literature review articles on each of these subjects separately, there is a lack of review articles on the application of combined PBL-VR learning environments in engineering education. This paper provides an assessment of the applications and potential of implementing immersive technologies in a PBL setting to utilize the advantages of both paradigms. More specifically, this paper aims to provide insights related to two main questions: (1) where (in what disciplines/subjects) PBL and VR have been used together in engineering education? And, (2) how are VR and PBL integrated and used in engineering education? The first question is investigated by performing a bibliometric analysis of relevant papers published in the proceedings of previous ASEE annual conferences. The second question is explored by performing a literature review and classification of ASEE papers that discuss the use of VR in conjunction with PBL. Our findings reveal a gap between the application of integrated PBL and VR across different disciplines in engineering education. We also analyze the trends related to PBL and VR application in engineering education over time. Finally, we identify and propose future opportunities related to the combination of PBL and immersive technologies, including but not limited to immersive simulation-based learning (ISBL) and incorporating artificial intelligence (AI) into immersive virtual/simulated learning environments used in engineering education.