Low-cost flexible plasmonic nanobump metasurfaces for label-free sensing of serum tumor marker.

The use of plasmonic metasurface for sensing has great potential on label-free detection of human tumor markers, which could benefit clinical examination. In this work, we adopt nanoimprint and plasma etching to optimize the nanofabrication for low-cost flexible plasmonic metasurface sensors with gold nanobump arrays, which enable facile surface bio-functionality, high sensitivity and simple optical measurement in the visible range. A high bulk refractive index sensitivity of 454.4 nm/RIU is achieved for the prototype plasmonic metasurface sensors at the wavelengths from 620 nm to 720 nm. The rapid quantitative tumor marker sensing of carcinoembryonic antigen in human serum samples from less than 10 ng/mL to more than 87 ng/mL is achieved, which demonstrates good agreement with the conventional chemiluminescence immunoassay system and sufficiently covers the threshold tumor marker concentration of 20 ng/mL for early cancer prediction. Our method is capable of low-cost high-throughput manufacturing for flexible lightweight plasmonic metasurface sensors, which will facilitate wide applications on portable biomedical sensing devices for future point-of-care diagnosis and mobile healthcare

Low-cost flexible plasmonic nanobump metasurfaces for label-free sensing of serum tumor marker

Abstract(#br)The use of plasmonic metasurface for sensing has great potential on label-free detection of human tumor markers, which could benefit clinical examination. In this work, we adopt nanoimprint and plasma etching to optimize the nanofabrication for low-cost flexible plasmonic metasurface sensors with gold nanobump arrays, which enable facile surface bio-functionality, high sensitivity and simple optical measurement in the visible range. A high bulk refractive index sensitivity of 454.4 nm/RIU is achieved for the prototype plasmonic metasurface sensors at the wavelengths from 620 nm to 720 nm. The rapid quantitative tumor marker sensing of carcinoembryonic antigen in human serum samples from less than 10 ng/mL to more than 87 ng/mL is achieved, which demonstrates good agreement with the conventional chemiluminescence immunoassay system and sufficiently covers the threshold tumor marker concentration of 20 ng/mL for early cancer prediction. Our method is capable of low-cost high-throughput manufacturing for flexible lightweight plasmonic metasurface sensors, which will facilitate wide applications on portable biomedical sensing devices for future point-of-care diagnosis and mobile healthcare

Construction of Vibronic Diabatic Hamiltonian for Excited-State Electron and Energy Transfer Processes

Photoinduced excited-state electron and energy transfer processes are crucial in biological photoharvesting systems and organic photovoltaic devices. We discuss the construction of a diabatic vibronic Hamiltonian for the proper treatment of these processes involving the projection approach acting on both electronic wave functions and vibrational modes. In the electronic part, the wave function projection approach is used to construct the diabatic Hamiltonian in which both local excited states and charge-transfer states are included on the same footing. For the vibrational degrees of freedom, the vibronic couplings in the diabatic Hamiltonian are obtained in the basis of the pseudonormal modes localized on each monomer site by applying delocalized-to-localized mode projection. This systematic approach allows us to construct the vibronic diabatic Hamiltonian in molecular aggregates

Ultrafast Nonadiabatic Dynamics of Singlet Fission: Quantum Dynamics with the Multilayer Multiconfigurational Time-Dependent Hartree (ML-MCTDH) Method

Singlet fission (SF) is supposed to potentially improve the efficiency of solar energy conversion in organic photovoltaic systems. The multilayer multiconfigurational time-dependent Hartree (ML-MCTDH) method was employed to describe the singlet fission of the pentacene system with a three-state model. The ML-MCTDH result agrees well with the previous simulations using the Redfield theory, the hierarchical equation of motion (HEOM) and the symmetrical quasi-classical (SQC) theory. We carefully investigated the role of vibrational modes with different frequencies in singlet fission dynamics. Interestingly, we observed the important contribution of a few modes with frequency resonance to electronic transition. Such a finding can be understood by revisiting the superexchange mechanism within the framework of Fermi’s golden rule. As a numerically exact method, ML-MCTDH not only provides an accurate description of the microscopy insight of the SF dynamics but also provides benchmark results to examine the performance of other approximated dynamical methods

The Data-Driven Modeling of Pressure Loss in Multi-Batch Refined Oil Pipelines with Drag Reducer Using Long Short-Term Memory (LSTM) Network

Due to the addition of the drag reducer in refined oil pipelines for increasing the pipeline throughput as well as reducing energy consumption, the classical method based on the Darcy-Weisbach Formula for precise pressure loss calculation presents a large error. Additionally, the way to accurately calculate the pressure loss of the refined oil pipeline with the drag reducer is in urgent need. The accurate pressure loss value can be used as the input parameter of pump scheduling or batch scheduling models of refined oil pipelines, which can ensure the safe operation of the pipeline system, achieving the goal of energy-saving and cost reduction. This paper proposes the data-driven modeling of pressure loss for multi-batch refined oil pipelines with the drag reducer in high accuracy. The multi-batch sequential transportation process and the differences in the physical properties between different kinds of refined oil in the pipelines are taken into account. By analyzing the changes of the drag reduction rate over time and the autocorrelation of the pressure loss sequence data, the sequential time effect of the drag reducer on calculating pressure loss is considered and therefore, the long short-term memory (LSTM) network is utilized. The neural network structure with two LSTM layers is designed. Moreover, the input features of the proposed model are naturally inherited from the Darcy-Weisbach Formula and on adaptation to the multi-batch sequential transportation process in refined oil pipelines, using the particle swarm optimization (PSO) algorithm for network hyperparameter tuning. Case studies show that the proposed data-driven model based on the LSTM network is valid and capable of considering the multi-batch sequential transportation process. Furthermore, the proposed model outperforms the models based on the Darcy-Weisbach Formula and multilayer perceptron (MLP) from previous studies in accuracy. The MAPEs of the proposed model of pipelines with the drag reducer are all less than 4.7% and the best performance on the testing data is 1.3627%, which can provide the calculation results of pressure loss in high accuracy. The results also indicate that the model’s capturing sequential effect of the drag reducer from the input data set contributed to improving the calculation accuracy and generalization ability

Ultrafast Excited-State Energy Transfer in DTDCTB Dimers Embedded in a Crystal Environment: Quantum Dynamics with the Multilayer Multiconfigurational Time-Dependent Hartree Method

Photoinduced excited-state energy transfer (EET) processes play a key role in the solar energy conversion of small molecule organic solar cells. We investigated intermolecular EET dynamics in the 2-[[7-(5-<i>N</i>,<i>N</i>-ditolylaminothiophen-2-yl)-2,1,3-benzothiadiazol-4-yl]­methylene]­malononitrile (DTDCTB) dimer embedded in a crystal environment using full quantum dynamics, i.e., the multilayer multiconfigurational time-dependent Hartree (ML-MCTDH) method. Two different stacking statuses of the DTDCTB dimers, which occur along the OA axis in the DTDCTB crystal, were considered. We built a vibronic diabatic Hamiltonian using the projection method based on quantum mechanics/molecular mechanics results. Different model Hamiltonians were considered in the full quantum dynamics studies. First, reduced-dimensional models were constructed by simply including more of the important vibrational modes. Second, we tried to construct a continuous spectral density based on the vibronic coupling strengths of different modes and then created a set of “pseudomodes” to represent electron–phonon couplings. The dynamics results based on these reduced models were compared with the results obtained with the full dimensional model. Our theoretical descriptions demonstrated that ultrafast intermolecular EET dynamics takes place in the well-stacked DTDCTB dimers. This work deepens our understanding of the photoinduced ultrafast EET dynamics of realistic organic photovoltaic systems at the full quantum mechanical level