Modifying the organic/electrode interface in Organic Solar Cells (OSCs) and improving the efficiency of solution-processed phosphorescent Organic Light-Emitting Diodes (OLEDs)

Organic semiconductors devices, such as, organic solar cells (OSCs), organic light-emitting diodes (OLEDs) and organic field-effect transistors (OFETs) have drawn increasing interest in recent decades. As organic materials are flexible, light weight, and potentially low-cost, organic semiconductor devices are considered to be an alternative to their inorganic counterparts. This dissertation will focus mainly on OSCs and OLEDs. As a clean and renewable energy source, the development of OSCs is very promising. Cells with 9.2% power conversion efficiency (PCE) were reported this year, compared to \u3c 8% two years ago. OSCs belong to the so-called third generation solar cells and are still under development. While OLEDs are a more mature and better studied field, with commercial products already launched in the market, there are still several key issues: (1) the cost of OSCs/OLEDs is still high, largely due to the costly manufacturing processes; (2) the efficiency of OSCs/OLEDs needs to be improved; (3) the lifetime of OSCs/OLEDs is not sufficient compared to their inorganic counterparts; (4) the physics models of the behavior of the devices are not satisfactory. All these limitations invoke the demand for new organic materials, improved device architectures, low-cost fabrication methods, and better understanding of device physics. For OSCs, we attempted to improve the PCE by modifying the interlayer between active layer/metal. We found that ethylene glycol (EG) treated poly(3,4-ethylenedioxy-thiophene):polystyrenesulfonate (PEDOT: PSS) improves hole collection at the metal/polymer interface, furthermore it also affects the growth of the poly(3-hexylthiophene) (P3HT):phenyl-C61-butyric acid methyl ester (PCBM) blends, making the phase segregation more favorable for charge collection. We then studied organic/inorganic tandem cells. We also investigated the effect of a thin LiF layer on the hole-collection of copper phthalocyanine (CuPc)/C70-based small molecular OSCs. A thin LiF layer serves typically as the electron injection layer in OLEDs and electron collection interlayer in the OSCs. However, several reports showed that it can also assist in hole-injection in OLEDs. Here we first demonstrate that it assists hole-collection in OSCs, which is more obvious after air-plasma treatment, and explore this intriguing dual role. For OLEDs, we focus on solution processing methods to fabricate highly efficient phosphorescent OLEDs. First, we investigated OLEDs with a polymer host matrix, and enhanced charge injection by adding hole- and electron-transport materials into the system. We also applied a hole-blocking and electron-transport material to prevent luminescence quenching by the cathode. Finally, we substituted the polymer host by a small molecule, to achieve more efficient solution processed small molecular OLEDs (SMOLEDs); this approach is cost-effective in comparison to the more common vacuum thermal evaporation. All these studies help us to better understand the underlying relationship between the organic semiconductor materials and the OSCs and OLEDs\u27 performance and will subsequently assist in further enhancing the efficiencies of OSCs and OLEDs. With better efficiency and longer lifetime, the OSCs and OLEDs will be competitive with their inorganic counterparts

Studies Towards a pH-Sensitive Anticancer Prodrug Model

Tumour-activated prodrug (TAP) is designed to aim at increasing the prodrug selectivity to kill cancer cells. One strategy to is to design a TAP containing an amine cytotoxin, present as an amide function, which could be released more rapidly in the low pH environment of tumour tissues when amide undergoes hydrolysis. The prodrug model (1) was the subject of the current study. At lower pH its un-ionised carboxylic acid group provides neighbouring catalysis of hydrolysis of the adjacent amide. It was synthesised via ring-opening of the imide (2) which itself was directly synthesised from endo-bicyclo[2.2.2]octa-5-ene-2,3-dicarboxylic anhydride and p-methoxyaniline. The pH-rate profile of (1) was established over the pH range of 3-10, covering rapid hydrolysis of un-ionised acid-amide at lower pH but slower imide formation above pH 8 from the ionised acid-amide. From the kinetic data were calculated the dissociation constant for (1) (pKa: 5.1 at 30 C) and limiting lower pH rate constant for hydrolysis of (1) in its fully neutral form (klim: 0.44 min-1 at 30 C). The data in the pH range of 8-10 provided klow (0.067 min-1) representing formation of (2) from fully ionised (1). The following equilibrium reaction was also investigated at high pH, at which (1) was in its fully ionised amide carboxylate form, by kinetic studies on (2) in hydroxide solutions. Imide + OH- Amide carboxylate The second order rate constant for the forward reaction, kf, was 74 L mol-1 min-1 which with klow for the reverse reaction gave K as 1100 L mol-1

Local Non-Hermitian Hamiltonian Formalism for Dissipative Fermionic Systems and Loss-Induced Population Increase in Fermi Superfluids

Non-Hermitian Hamiltonian (NHH) is an effective formalism for open quantum systems. In common wisdom, when the system is described by the Lindblad master equation, the NHH obtained by neglecting its jump term is believed to be a good approximation for a timescale sufficiently shorter than the inverse of the dissipation rate. We challenge this common wisdom and develop a scheme to obtain an appropriate NHH from the original master equation for dissipative fermionic systems. This NHH, called the local NHH, describes the loss process in each individual mode locally. As a concrete example, we justify our new scheme using fermionic superfluid under one-body loss. Furthermore, we find loss-induced population increase in the long time evolution due to the dissipation-induced phase locking between the pairing gap and the anomalous field

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback

Probabilistic learning to rank (LTR) has been the dominating approach for optimizing the ranking metric, but cannot maximize long-term rewards. Reinforcement learning models have been proposed to maximize user long-term rewards by formulating the recommendation as a sequential decision-making problem, but could only achieve inferior accuracy compared to LTR counterparts, primarily due to the lack of online interactions and the characteristics of ranking. In this paper, we propose a new off-policy value ranking (VR) algorithm that can simultaneously maximize user long-term rewards and optimize the ranking metric offline for improved sample efficiency in a unified Expectation-Maximization (EM) framework. We theoretically and empirically show that the EM process guides the leaned policy to enjoy the benefit of integration of the future reward and ranking metric, and learn without any online interactions. Extensive offline and online experiments demonstrate the effectiveness of our methods

Sensing-Resistance-Oriented Beamforming for Privacy Protection from ISAC Devices

With the evolution of integrated sensing and communication (ISAC) technology, a growing number of devices go beyond conventional communication functions with sensing abilities. Therefore, future networks are divinable to encounter new privacy concerns on sensing, such as the exposure of position information to unintended receivers. In contrast to traditional privacy preserving schemes aiming to prevent eavesdropping, this contribution conceives a novel beamforming design toward sensing resistance (SR). Specifically, we expect to guarantee the communication quality while masking the real direction of the SR transmitter during the communication. To evaluate the SR performance, a metric termed angular-domain peak-to-average ratio (ADPAR) is first defined and analyzed. Then, we resort to the null-space technique to conceal the real direction, hence to convert the optimization problem to a more tractable form. Moreover, semidefinite relaxation along with index optimization is further utilized to obtain the optimal beamformer. Finally, simulation results demonstrate the feasibility of the proposed SR-oriented beamforming design toward privacy protection from ISAC receivers.Comment: Accepted for presentation at WS29 ICC 2024 Workshop - ISAC6

3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs

Generating molecules with desired properties is a critical task with broad applications in drug discovery and materials design. Inspired by recent advances in large language models, there is a growing interest in using natural language descriptions of molecules to generate molecules with the desired properties. Most existing methods focus on generating molecules that precisely match the text description. However, practical applications call for methods that generate diverse, and ideally novel, molecules with the desired properties. We propose 3M-Diffusion, a novel multi-modal molecular graph generation method, to address this challenge. 3M-Diffusion first encodes molecular graphs into a graph latent space aligned with text descriptions. It then reconstructs the molecular structure and atomic attributes based on the given text descriptions using the molecule decoder. It then learns a probabilistic mapping from the text space to the latent molecular graph space using a diffusion model. The results of our extensive experiments on several datasets demonstrate that 3M-Diffusion can generate high-quality, novel and diverse molecular graphs that semantically match the textual description provided