Publications

Multivalent-ion batteries offer an alternative to Li-based technologies, with the potential for greater sustainability, improved safety, and higher energy density, primarily due to their rechargeable system featuring a passivating metal anode. Although a system based on the Ca²⁺/Ca couple is particularly attractive given the low electrochemical plating potential of Ca²⁺, the remaining challenge for a viable rechargeable Ca battery is to identify Ca cathodes with fast ion transport. In this work, a high-throughput computational pipeline is adapted to (1) discover novel Ca cathodes in a largely unexplored space of "empty intercalation hosts" and (2) develop material design rules for Ca-ion mobility. One candidate from the screening, W₂O₃(PO₄)₂, is confirmed to have a low Nudged Elastic Band (NEB) barrier of 168 meV within a one-dimensional (1D) ion percolation topology. This candidate is subsequently synthesized and electrochemically tested, achieving reversible Ca cycling with a capacity of 25 mA h/g. To further accelerate the screening for promising Ca intercalation electrodes, machine learning (ML) Random Forest (RF) and Extreme Gradient Boosting (XGB) classification models are created with local environment descriptors based on a large, structurally and chemically diverse dataset of minimum energy pathways, spanning over 5,000 density functional theory (DFT) site energy calculations. Accuracies of 92% are achieved, material design metrics are quantified, ML force-fields are leveraged in an accelerated iteration of the screening, and a total of 27 novel Ca cathode materials are highlighted for further investigation.

Many past systems have explored how to eliminate redundant transfers from network links and improve network efficiency. Several of these systems operate at the application layer, while the more recent systems operate on individual packets. A common aspect of these systems is that they apply to localized settings, e.g. at stub network access links. In this paper, we explore the benefits of deploying packet-level redundant content elimination as a universal primitive on all Internet routers. Such a universal deployment would immediately reduce link loads everywhere. However, we argue that far more significant network-wide benefits can be derived by redesigning network routing protocols to leverage the universal deployment. We develop "redundancy-aware" intra- and inter-domain routing algorithms and show that they enable better traffic engineering, reduce link usage costs, and enhance ISPs' responsiveness to traffic variations. In particular, employing redundancy elimination approaches across redundancy-aware routes can lower intra and inter-domain link loads by 10-50%. We also address key challenges that may hinder implementation of redundancy elimination on fast routers. Our current software router implementation can run at OC48 speeds.

Automatic symbolic traffic scene analysis is essential to many areas of IVHS (Intelligent Vehicle Highway Systems). Traffic scene information can be used to optimize traffic flow during busy periods, identify stalled vehicles and accidents, and aid the decision-making of an autonomous vehicle controller. Improvements in technologies for machine vision-based surveillance and high-level symbolic reasoning have enabled the authors to develop a system for detailed, reliable traffic scene analysis. The machine vision component of the system employs a contour tracker and an affine motion model based on Kalman filters to extract vehicle trajectories over a sequence of traffic scene images. The symbolic reasoning component uses a dynamic belief network to make inferences about traffic events such as vehicle lane changes and stalls. In this paper, the authors discuss the key tasks of the vision and reasoning components as well as their integration into a working prototype. Preliminary results of an implementation on special purpose hardware using C-40 Digital Signal Processors show that near real-time performance can be achieved without further improvements.

We describe Livenotes, a shared whiteboard system and educational practice that uses wireless communication and tablet computing to support real-time conversations within small groups of students during lectures, independent of class size. We present an interface design that enables group members to interact with one another by taking lecture notes cooperatively, as well as to augment student note-taking by providing instructor slides in the background to annotate over. Livenotes was designed to facilitate more efficient, stimulating modes of learning that other collaborative approaches do not. We report how the system impacts cooperative learning in an undergraduate class and how students interacted with background slides in the workspace. We conclude with directions for improving the system and learning practice.

This work details an in-depth evaluation of an unprecedented mechanism for the hydrosilylation of carbonyl compounds catalyzed by (PPh3)2Re(O)2I. The proposed mechanism involves addition of a silane Si-H bond across one of the rhenium-oxo bonds to form siloxyrhenium hydride intermediate 2 that reacts with a carbonyl substrate to generate siloxyrhenium alkoxide 4, which, in turn, affords the silyl ether product. Compelling evidence for the operation of this pathway includes the following: (a) isolation and structural characterization by X-ray diffraction of siloxyrhenium hydride intermediate 2, (b) demonstration of the catalytic competence of intermediate 2 in the hydrosilylation reaction, (c) 1H and 31P{1H} NMR and ESI-MS evidence for single-turnover conversion of 2 into 1, (d) observation of intermediate 2 in the working catalyst system, and (e) kinetic analysis of the catalytic hydrosilylation of carbonyl compounds by 1.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Background We examined maternal depressive symptoms ( MDS ) as longitudinal predictors of actigraphy‐measured sleep; children's respiratory sinus arrhythmia ( RSA ) was tested as a moderator of these relations. Method A total of 271 children (145 boys and 126 girls) participated in a three‐wave study ( M age at T1 = 9.38 years), with a 1‐year lag between waves. Children wore actigraphs to derive sleep parameters. RSA reactivity was assessed during a social stress test. Results Contrary to hypotheses, MDS were related to less sleep over time for children exhibiting greater RSA withdrawal. Consistent with hypotheses, MDS were related longitudinally to decreased sleep activity for children exhibiting less RSA withdrawal. Conclusions Findings illustrate the importance of maternal influences and physiological regulation as predictors of children's sleep.

Abstract A polyacrylate‐based monolithic column bearing cationic functionalities and designed for capillary electrochromatography (CEC) has been prepared via photopolymerization of a mixture of hexyl acrylate, butanediol diacrylate, 2‐(acryloyloxy) ethyltrimethyl ammonium chloride (monomers), azobisisobutyronitrile (photoinitiator), acetonitrile, phosphate buffer, and ethanol (porogens). The polymerization process was initiated with UV light at 360 nm. The column performance was evaluated via the separations of alkylbenzenes, substituted anilines, basic drugs, peptides, and a protein digest. The separation of complex peptide mixtures was then studied since such separations constitute a promising application of capillary electrochromatograhy. In particular, the effects of mobile phase composition, including ionic strength of the buffer solution and the percentage of acetonitrile on the retention factor, the column efficiency, and the resolution were determined. The separations were affected by both interaction of the peptides with the stationary phase and their own electrophoretic mobility. Excellent separations with column efficiencies of up to 160 000 plates/m were achieved for both a mixture of ten well‐defined peptides and a tryptic digest of cytochrome c. The fractions of eluent containing peptides of the digest separated in the monolithic column were collected and characterized using matrix‐assisted laser desorption ionization mass spectrometry.

The bright, nearby, recently discovered supernova (SN) 2010jl is a luminous Type IIn SN. Here, we report archival Hubble Space Telescope (HST) observations of its host galaxy UGC 5189A taken roughly 10 yr prior to explosion, as well as early-time optical spectra of the SN. The HST images reveal a luminous, blue point source at the position of the SN, with an absolute magnitude of –12.0 in the F300W filter. If it is not just a chance alignment, the source at the SN position could be (1) a massive young (<6 Myr) star cluster in which the SN resided, (2) a quiescent, luminous blue star with an apparent temperature around 14,000 K, (3) a star caught during a bright outburst akin to those of luminous blue variables, or (4) a combination of option (1) and option (2) or (3). Although we cannot confidently choose between these possibilities with the present data, any of them imply that the progenitor of SN 2010jl had an initial mass above 30 M_☉. This reinforces mounting evidence that many SNe IIn result from very massive stars, that massive stars can produce visible SNe without collapsing quietly to black holes, and that massive stars can sometimes retain their H envelopes until shortly before explosion. Standard stellar evolution models fail to account for these observed properties.