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The increasing need to simulate the dynamics of photoexcited molecular systems and nanosystems in the subpicosecond regime demands new efficient tools able to describe the quantum nature of matter at a low computational cost. By combining the power of the approximate DFTB method with the semiclassical Ehrenfest method for nuclear-electron dynamics, we have achieved a real-time time-dependent DFTB (TD-DFTB) implementation that fits such requirements. In addition to enabling the study of nuclear motion effects in photoinduced charge transfer processes, our code adds novel features to the realm of static and time-resolved computational spectroscopies. In particular, the optical properties of periodic materials such as graphene nanoribbons or the use of corrections such as the "LDA+U" and "pseudo SIC" methods to improve the optical properties in some systems can now be handled at the TD-DFTB level. Moreover, the simulation of fully atomistic time-resolved transient absorption spectra and impulsive vibrational spectra can now be achieved within reasonable computing time, owing to the good performance of the implementation and a parallel simulation protocol. Its application to the study of UV/visible light-induced vibrational coherences in molecules is demonstrated and opens a new door into the mechanisms of nonequilibrium ultrafast phenomena in countless materials with relevant applications.
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http://dx.doi.org/10.1021/acs.jctc.9b01217 | DOI Listing |
ACS Sens
September 2025
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
Alpha-2-macroglobulin (A2M) is a critical biomarker implicated in inflammation, immune regulation, coagulation, and various pathological conditions such as liver fibrosis, neurodegenerative diseases, and cancers. However, its precise quantification remains challenging due to complex conformational dynamics, subtle abundance fluctuations, and interference from plasma proteins. Here, we present a label-free dynamic single-molecule sensing (LFDSMS) strategy for the sensitive and specific detection of A2M.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA.
We present a self-consistent algorithm for optimal control simulations of many-body quantum systems. The algorithm features a two-step synergism that combines discrete real-time machine learning (DRTL) with Quantum Optimal Control Theory (QOCT) using the time-dependent Schrödinger equation. Specifically, in step (1), DRTL is employed to identify a compact working space (i.
View Article and Find Full Text PDFDrug Dev Res
September 2025
Endoscopy Center, Minhang Hospital, Fudan University, Shanghai, China.
Colorectal cancer (CRC) is a common malignancy often characterized by metastasis and poor prognosis. This study attempts to ascertain the anticancer impacts of theaflavin (TF) on CRC cells and examine the fundamental molecular mechanisms, focusing on the function of DDIT4 in CRC progression. This study utilized RNA sequencing for gene expression profiling, differential expression analysis, and Venn diagram analysis for overlapping genes.
View Article and Find Full Text PDFJ Mater Chem B
September 2025
Guangdong Key Laboratory of Nanomedicine, CAS-HK Joint Lab of Biomaterials, CAS Key Laboratory of Biomedical Imaging Science and System, Shenzhen Key Laboratory of Metabolic Halth, Shenzhen Metabolism and Reproductive Targeted Delivery Proof-of-Concept Center, Shenzhen Engineering Laboratory of Nano
Bacterial infections pose significant challenges in clinical diagnostics and microbiological research due to the need for rapid, sensitive, and specific detection methods. Herein, we report the development of Cy5-NO2, a novel nitro-containing fluorescent probe designed for real-time monitoring of bacterial nitroreductase (NTR) activity. Cy5-NO2 is synthesized through a streamlined, high-yield process without chromatography, yielding a stable compound confirmed by X-ray crystallography and spectroscopic methods.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
September 2025
Myoelectric pattern recognition systems serve as a promising predictive control approach for the lower limbs prostheses and exoskeletons. However, their actual deployment is challenged by the signal stochastic nature that could contaminate the decision stream with physiologically implausible transitions, posing safety and metabolic cost concerns on the potential user. Therefore, this study proposes a novel Physics-Informed Bayesian Fusion (PI-BF) post-processor that embeds biomechanical sequentiality constraints into the posterior probabilistic output of the classifiers to suppress unstable transitions and promote natural gait progression.
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