More Like this

1. Highly Efficient, Long-Lived Charge Separated States in Star-Shaped Ferrocene-Diketopyrrolopyrrole-Triphenylamine Donor-Acceptor-Donor Conjugates

   https://doi.org/doi.org/10.1002/chem.202000346  

   M. Poddar, Y. Jang (November 2020, Chemistry)

   null (Ed.)

   The significance of multiple number of donor-acceptor entities on a central electron donor in a star-shaped molecular system in improving light energy harvesting ability is reported. For this, donor-acceptor-donor type conjugates comprised up to three entities ferrocenyl (Fc)-diketopyrrolopyrrole (DPP) onto a central triphenylamine (TPA), (4-6) by the Pd-catalyzed Sonogashira cross–coupling reactions have been newly synthesized and characterized. Donor-acceptor conjugates possessing diketopyrrolopyrrole (1 to 3 entities) onto the central triphenylamine, (1-3) served as reference dyads while monomeric DPP and Fc-DPP served as control compounds. Both DPP and Fc-DPP carrying conjugates exhibited red-shifted absorption compared to their respective control compounds revealing existence of ground state interactions. Furthermore, DPP fluorescence in 4-6 was found to be quantitatively quenched while for 1-3, this property varied between 73-65% suggesting occurrence moderate amounts of excited state events. The electrochemical investigations exhibited an additional low potential oxidation in the case of Fc-DPP-TPA based derivatives (4-6) owing to the presence of ferrocene unit(s). This was in addition to DPP and TPA redox peaks. Using spectral, electrochemical and computational studies, Gibbs free-energy calculations were performed to visualize excited state charge separation (GCS) in these donor-acceptor conjugates as a function of different number of Fc-DPP entities. Formation of Fc+-DPP•--TPA charge separated states (CSS) in the case of 4-6 was evident. Using spectroelectrochemical studies, spectrum of CSS was deduced. Finally, femtosecond transient absorption spectral studies were performed to gather information on excited state charge separation. Increasing the number of Fc-DPP entities in 4-6 improved charge separation rates. Surprisingly, lifetime of the charge separated state, Fc+-DPP•--TPA was found to persist longer with an increase in the number of Fc-DPP entities in 4-6 as compared to Fc-DPP-control and simple DPP derived donor-acceptor conjugates in literature. This unprecedented result has been attributed to subtle changes in GCS and GCR and the associated electron coupling between different entities. 

   more » « less
2. Rd-dpp: Rate-distortion theory meets determinantal point process to diversify learning data samples

   Chen, Xiwen; Li, Huayu; Qiu, Peijie; Zhu, Wenhui; Amin, Rahul; Razi, Abolfazl (August 2024, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV))

   Selecting representative samples plays an indispensable role in many machine learning and computer vision applications under limited resources (e.g., limited communication bandwidth and computational power). Determinantal Point Process (DPP) is a widely used method for selecting the most diverse representative samples that can summarize a dataset. However, its adaptability to different tasks remains an open challenge, as it is challenging for DPP to perform task-specific tuning. In contrast, Rate-Distortion (RD) theory provides a way to measure task-specific diversity. However, optimizing RD for a data selection problem remains challenging because the quantity that needs to be optimized is the index set of the selected samples. To tackle these challenges, we first draw an inherent relationship between DPP and RD theory. Our theoretical derivation paves the way for taking advantage of both RD and DPP for a task-specific data selection. To this end, we propose a novel method for task-specific data selection for multi-level classification tasks, named RD-DPP. Empirical studies on seven different datasets using five benchmark models demonstrate the effectiveness of the proposed RD-DPP method. Our method also outperforms recent strong competing methods, while exhibiting high generalizability to a variety of learning tasks. 

   more » « less
3. Systematic control of the rate of singlet fission within 6,13-diphenylpentacene aggregates with PbS quantum dot templates

   https://doi.org/10.1039/C8FD00157J  

   Wang, Chen; Kodaimati, Mohamad S.; Lian, Shichen; Weiss, Emily A. (July 2019, Faraday Discussions)

   Lead chalcogenide quantum dots (QDs) are promising acceptors for photovoltaic devices that harness the singlet fission (SF) mechanism. The rate of singlet fission of polyacenes in the presence of QDs is a critical parameter in determining the performance of such devices. The present study demonstrates that the rates of SF in a pentacene derivative, 6,13-diphenylanthracene (DPP), are modulated by forming coaggregates with PbS QDs in aqueous dispersions. PbS QDs generally accelerate SF within DPP aggregates, and the extent of acceleration depends on the size of the QD. The average rate of SF increases from 0.074 ps −1 for DPP-only aggregates to 0.37 ps −1 within DPP-D co-aggregates for QDs with radius 2.2 nm, whereas co-aggregation with the smallest ( r = 1.6 nm) and largest ( r = 2.7 nm) QDs we tried only slightly change the SF rate. The rate variation is associated with (i) the density of surface ligands, which is influenced by the faceting of the PbS surface, and (ii) the local dielectric constant for DPP. To accelerate SF, the ligands should be dense enough to provide sufficient affinity for DPP aggregates and effectively perturb the perpendicular alignment of DPP monomers within aggregates to increase the intermolecular coupling that promotes SF, but should not be too dense so as to form a low dielectric environment that disfavors SF. The study suggests that it is critical to consider the influence of the microenvironment of the QD surface on photophysical processes when fabricating QD/organic hybrid devices. 

   more » « less
4. Learning on Bandwidth Constrained Multi-Source Data with MIMO-inspired DPP MAP Inference

   Chen, Xiwen; Li, Huayu; Amin, Rahul; Razi, Abolfazl (July 2024, IEEE Transactions on Machine Learning in Communications and Networking)

   Determinantal Point Process (DPP) is a powerful technique to enhance data diversity by promoting the repulsion of similar elements in the selected samples. Particularly, DPP-based Maximum A Posteriori (MAP) inference is used to identify subsets with the highest diversity. However, a commonly adopted presumption of all data samples being available at one point hinders its applicability to real-world scenarios where data samples are distributed across distinct sources with intermittent and bandwidth-limited connections. This paper proposes a distributed version of DPP inference to enhance multi-source data diversification under limited communication budgets. First, we convert the lower bound of the diversity-maximized distributed sample selection from matrix determinant optimization to a simpler form of the sum of individual terms. Next, a determinant-preserved sparse representation of selected samples is formed by the sink as a surrogate for collected samples and sent back to sources as lightweight messages to eliminate the need for raw data exchange. Our approach is inspired by the channel orthogonalization process of Multiple-Input Multiple-Output (MIMO) systems based on the Channel State Information (CSI). Extensive experiments verify the superiority of our scalable method over the most commonly used data selection methods, including GreeDi, Greedymax, random selection, and stratified sampling by a substantial gain of at least 12% reduction in Relative Diversity Error (RDE). This enhanced diversity translates to a substantial improvement in the performance of various downstream learning tasks, including multi-level classification (2%-4% gain in accuracy), object detection (2% gain in mAP), and multiple-instance learning (1.3% gain in AUC). 

   more » « less
5. A 99.7% Efficient 300 W Hard Disk Drive Storage Server with Multiport Ac-Coupled Differential Power Processing (MAC-DPP) Architecture

   https://doi.org/10.1109/ECCE.2019.8911853  

   Wang, Ping; Chen, Yenan; Kushima, Parker; Elasser, Youssef; Liu, Ming; Chen, Minjie (September 2019, 2019 IEEE Energy Conversion Congress and Exposition (ECCE))

   High performance computing needs high performance power electronics. This paper presents the design of an ultra-efficient series-stacked hard-disk-drive (HDD) data storage server with a multiport ac-coupled differential power processing (MAC-DPP) architecture. A large number of HDDs are connected in series and ac-coupled through a multi-winding transformer with a single flux linkage. The MAC-DPP architecture offers very low power conversion stress, can achieve extremely high efficiency, and can reduce the magnetic size and the component count. A hybrid time-sharing and distributed phase-shift control strategy is developed to modulate the ac-coupled multi-input-multi-output (MIMO) power flow. A 10-port MAC-DPP prototype was designed to support a 300 W data storage system with 10 series-stacked voltage domains. The MAC-DPP converter was tested with a 50-HDD 12TB testbench, which can maintain normal operation of the server against the worst hot-swapping scenario. The 300 W MAC-DPP prototype can achieve 99.7% peak system efficiency and over 100 W/in 3 power density. 

   more » « less