Publications

Controlling the chemistry at the interface of nanocrystalline solids has been a challenge and an important goal to realize desired properties. Integrating two different types of materials has the potential to yield new functions resulting from cooperative effects between the two constituents. Metal–organic frameworks (MOFs) are unique in that they are constructed by linking inorganic units with organic linkers where the building units can be varied nearly at will. This flexibility has made MOFs ideal materials for the design of functional entities at interfaces and hence allowing control of properties. This review highlights the strategies employed to access synergistic functionality at the interface of nanocrystalline MOFs (nMOFs) and inorganic nanocrystals (NCs).

Footwear, carpet, automotive interiors, and multilayer packaging are examples of products manufactured from several types of polymers whose inextricability poses substantial challenges for recycling at the end of life. Here, we show that chemical circularity in mixed-polymer recycling becomes possible by controlling the rates of depolymerization of polydiketoenamines (PDK) over several orders of magnitude through molecular engineering. Stepwise deconstruction of mixed-PDK composites, laminates, and assemblies is chemospecific, allowing a prescribed subset of monomers, fillers, and additives to be recovered under pristine condition at each stage of the recycling process. We provide a theoretical framework to understand PDK depolymerization via acid-catalyzed hydrolysis and experimentally validate trends predicted for the rate-limiting step. The control achieved by PDK resins in managing chemical and material entropy points to wide-ranging opportunities for pairing circular design with sustainable manufacturing.

The design and development of metal-cluster-based heterogeneous catalysts with high activity, selectivity, and stability under solution-phase reaction conditions will enable their applications as recyclable catalysts in large-scale fine chemicals production. To achieve these required catalytic properties, a heterogeneous catalyst must contain specific catalytically active species in high concentration, and the active species must be stabilized on a solid catalyst support under solution-phase reaction conditions. These requirements pose a great challenge for catalysis research to design metal-cluster-based catalysts for solution-phase catalytic processes. Here, we focus on a silica-supported, polymer-encapsulated Pt catalyst for an electrophilic hydroalkoxylation reaction in toluene, which exhibits superior selectivity and stability against leaching under mild reaction conditions. We unveil the key factors leading to the observed superior catalytic performance by combining X-ray absorption spectroscopy (XAS) and reaction kinetic studies. On the basis of the mechanistic understandings obtained in this work, we also provide useful guidelines for designing metal-cluster-based catalyst for a broader range of reactions in the solution phase.

Human trajectory forecasting is an inherently multi-modal problem. Uncertainty in future trajectories stems from two sources: (a) sources that are known to the agent but unknown to the model, such as long term goals and (b)sources that are unknown to both the agent & the model, such as intent of other agents & irreducible randomness indecisions. We propose to factorize this uncertainty into its epistemic & aleatoric sources. We model the epistemic un-certainty through multimodality in long term goals and the aleatoric uncertainty through multimodality in waypoints& paths. To exemplify this dichotomy, we also propose a novel long term trajectory forecasting setting, with prediction horizons upto a minute, an order of magnitude longer than prior works. Finally, we presentY-net, a scene com-pliant trajectory forecasting network that exploits the pro-posed epistemic & aleatoric structure for diverse trajectory predictions across long prediction horizons.Y-net significantly improves previous state-of-the-art performance on both (a) The well studied short prediction horizon settings on the Stanford Drone & ETH/UCY datasets and (b) The proposed long prediction horizon setting on the re-purposed Stanford Drone & Intersection Drone datasets.

Density functional theory (DFT) calculations are performed to investigate the energetics of the CO2 electrochemical reduction on metal (M) porphyrin-like motifs incorporated into graphene layers. The objective is to develop strategies that enhance CO2 reduction while suppressing the competitive hydrogen evolution reaction (HER). We find that there exists a scaling relation between the binding energy of the catalyst to hydrogen and that to COOH, a key intermediate in the reduction of CO2 to CO; however, the M-H bond is stronger than the M-COOH bond, driving the reaction toward the HER rather than the reduction of CO2 to CO. This scaling relation holds even with axial ligation to the metal cation coordinated to the porphyrin ring. When 4f lanthanide or 5f actinide elements are used as the reactive center, the scaling relation still holds but the M-COOH bond is stronger than the M-H bond, and the reaction favors the reduction of CO2 to CO. By contrast, there is no scaling relation between the binding energy of the catalyst to H and that to OCHO, the key intermediate in CO2 reduction to formic acid. Interestingly, we find that coordination of a ligand to an unoccupied axial site can make the M-OCHO bond stronger than the M-H bond, resulting in preferential formic acid formation. This means that the axial ligand effectively enhances CO2 reduction to formic acid and suppresses the HER. Our DFT calculations have also identified several promising electrocatalysts for CO2 reduction to HCOOH with almost zero overpotentials.

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Poly(N-vinylpyrrolidone) (PVP) capped platinum and rhodium nanoparticles (7-12 nm) have been studied with UV-VIS, FTIR and Raman spectroscopy. The absorption bands in the region 190-900 nm are shown to be sensitive to the electronic structure of surface Rh and Pt atoms as well as to the aggregation of the nanoparticles. In-situ FTIR-DRIFT spectroscopy of the thermal decay of PVP stabilized Rh and Pt nanoparticles in H{sub 2} and O{sub 2} atmospheres in temperatures ranging from 30 C-350 C reveal that decomposition of PVP above 200 C, PVP transforms into a 'polyamidpolyene' - like material that is in turn converted into a thin layer of amorphous carbon above 300 C. Adsorbed carbon monoxide was used as a probing molecule to monitor changes of electronic structure of surface Rh and Pt atoms and accessible surface area. The behavior of surface Rh and Pt atoms with ligated CO and amide groups of pyrrolidones resemble that of surface coordination compounds.

The Cadmium-Lined Outer-Core Irradiation Tube (CLOCIT) is a new irradiation facility for 40Ar/39Ar geochronology at the Oregon State University TRIGA® reactor. We report fluence parameters from the first four CLOCIT irradiations and compare them to the existing Cadmium-Lined Inner-Core Irradiation Tube (CLICIT). CLOCIT provides an average neutron flux equivalent of 1.45–1.53 ×10-4 J/h; about 55% of CLICIT. Radial fluence gradients are on the order of 0.2–2.4 %/cm. A planar fit of J-values results in residuals in the range of uncertainty in the J-value, but systematic deviations resolve a non-planar component of the neutron flux field which has also been observed in CLICIT. Axial neutron fluence gradients are 0.6–1 %/cm, compared to 0.7–1.6 %/cm for the CLICIT. Production rate ratios of interfering reactions are (40Ar/39Ar)K = (4±6) ×10-4 and (38Ar/39Ar)K = (1.208±0.002) ×10-2, (36Ar/37Ar)Ca = (2.649±0.014) ×10-4, (38Ar/37Ar)Ca = (3.33±0.12) ×10-5, and (39Ar/37Ar)Ca = (9.1±0.28) ×10-4, similar to the CLICIT values.

Extensive efforts have been devoted in both the engineering and scientific domains to seek new designs and processing techniques capable of making stronger and tougher materials. One such method for enhancing such damage-tolerance in metallic alloys is a surface nano-crystallization technology that involves the use of hundreds of small hard balls which are vibrated using high-power ultrasound so that they impact onto the surface of a material at high speed (termed Surface Mechanical Attrition Treatment or SMAT). However, few studies have been devoted to the precise underlying mechanical mechanisms associated with this technology and the effect of processing parameters. As SMAT is dynamic plastic deformation process, here we use random impact deformation as a means to investigate the relationship between impact deformation and the parameters involved in the processing, specifically ball size, impact velocity, ball density and kinetic energy. Using analytical and numerical solutions, we examine the size of the indents and the depths of the associated plastic zones induced by random impacts, with results verified by experiment in austenitic stainless steels. In addition, global random impact and local impact frequency models are developed to analyze the statistical characteristics of random impact coverage, together with a description of the effect of random multiple impacts, which are more reflective of SMAT. We believe that these models will serve as a necessary foundation for further, and more energy-efficient, development of such surface nano-crystalline processing technologies for the strengthening of metallic materials.