Materials science research by synchrotron radiation spectroscopy

We report a fully organic pyridine-tetrapyrrolic U-shaped acyclic receptor 10, which prefers a supramolecular pseudo-macrocyclic dimeric structure (10)2 in a less polar, non-coordinating solvent (e.g., CHCl3). Conversely, when it is crystalized from a polar, coordinating solvent (e.g., N,N-dimethylformamide, DMF), it exhibited an infinite supramolecular one-dimensional (1D) “zig-zag” polymeric chain, as inferred from the single-crystal X-ray structures. This supramolecular system acts as a potential receptor for strong acids, e.g., p-toluenesulfonic acid (PTSA), methane sulfonic acid (MSA), H2SO4, HNO3, and HCl, with a prominent colorimetric response from pale yellow to deep red. The receptor can easily be recovered from the organic solution of the host–guest complex by simple aqueous washing. It was observed that relatively stronger acids with pKa < −1.92 in water were able to interact with the receptor, as inferred from 1H NMR titration in tetrahydrofuran-d8 (THF-d8) and ultraviolet–visible (UV–vis) spectroscopic titrations in anhydrous THF at 298 K. Therefore, this new dynamic supramolecular receptor system may have potentiality in materials science research.

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IBM to Award New Grants for Materials Science Research

Physics Today ◽

10.1063/1.2814499 ◽

1985 ◽

Vol 38 (3) ◽

pp. 114-114

Keyword(s):

Materials Science ◽

Science Research

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High-Impact Practices in Materials Science Education: Student Research Internships Leading to Pedagogical Innovation in STEM Laboratory Learning Activities

MRS Advances ◽

10.1557/adv.2017.106 ◽

2017 ◽

Vol 2 (31-32) ◽

pp. 1667-1672 ◽

Cited By ~ 2

Author(s):

Lon A. Porter

Keyword(s):

Computer Aided Design ◽

Materials Science ◽

Undergraduate Research ◽

Science Research ◽

High Impact ◽

Digital Design ◽

Education Student ◽

Research Experience ◽

Student Research ◽

Pedagogical Innovation

ABSTRACTTraditional lecture-centered approaches alone are inadequate for preparing students for the challenges of creative problem solving in the STEM disciplines. As an alternative, learnercentered and other high-impact pedagogies are gaining prominence. The Wabash College 3D Printing and Fabrication Center (3D-PFC) supports several initiatives on campus, but one of the most successful is a computer-aided design (CAD) and fabrication-based undergraduate research internship program. The first cohort of four students participated in an eight-week program during the summer of 2015. A second group of the four students was successfully recruited to participate the following summer. This intensive materials science research experience challenged students to employ digital design and fabrication in the design, testing, and construction of inexpensive scientific instrumentation for use in introductory STEM courses at Wabash College. The student research interns ultimately produced a variety of successful new designs that could be produced for less than $25 per device and successfully detect analytes of interest down to concentrations in the parts per million (ppm) range. These student-produced instruments have enabled innovations in the way introductory instrumental analysis is taught on campus. Beyond summer work, the 3D-PFC staffed student interns during the academic year, where they collaborated on various cross-disciplinary projects with students and faculty from departments such as mathematics, physics, biology, rhetoric, history, classics, and English. Thus far, the student work has led to three campus presentations, four presentations at national professional conferences, and three peer-reviewed publications. The following report highlights initial progress as well as preliminary assessment findings.

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First european conference on synchrotron radiation in materials science

Synchrotron Radiation News ◽

10.1080/08940889408261309 ◽

1994 ◽

Vol 7 (6) ◽

pp. 11-12 ◽

Cited By ~ 1

Author(s):

Neville Greaves

Keyword(s):

Synchrotron Radiation ◽

Materials Science ◽

European Conference

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Symmetry-general ab initio computation of physical properties using quantum software integrated with crystal structure databases: results and perspectives

Acta Crystallographica Section B Structural Science ◽

10.1107/s0108768102002422 ◽

2002 ◽

Vol 58 (3) ◽

pp. 349-357 ◽

Cited By ~ 8

Author(s):

Yvon Le Page ◽

Paul W. Saxe ◽

John R. Rodgers

Keyword(s):

Crystal Structure ◽

Physical Properties ◽

Ab Initio ◽

Materials Science ◽

Science Research ◽

Elastic Tensor ◽

Pure Phase ◽

Simulation And Experiment ◽

Structure Databases ◽

Using Data

The timely integration of crystal structure databases, such as CRYSTMET, ICSD etc., with quantum software, like VASP, OresteS, ElectrA etc., allows ab initio cell and structure optimization on existing pure-phase compounds to be performed seamlessly with just a few mouse clicks. Application to the optimization of rough structure models, and possibly new atomic arrangements, is detailed. The ability to reproduce observed cell data can lead to an assessment of the intrinsic plausibility of a structure model, even without a competing model. The accuracy of optimized atom positions is analogous to that from routine powder studies. Recently, the ab initio symmetry-general least-squares extraction of the coefficients of the elastic tensor for pure-phase materials using data from corresponding entries in crystal structure databases was automated. A selection of highly encouraging results is presented, stressing the complementarity of simulation and experiment. Additional physical properties also appear to be computable using existing quantum software under the guidance of an automation scheme designed following the above automation for the elastic tensor. This possibility creates the exciting perspective of mining crystal structure databases for new materials with combinations of physical properties that were never measured before. Crystal structure databases can accordingly be expected to become the cornerstone of materials science research within a very few years, adding immense practical value to the archived structure data.

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