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Li, Pengcheng

Publications and source records attributed to Li, Pengcheng.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Chain rigidity controlled aggregation ability and solid-state microstructures for efficient stretchable conjugated polymer films

Stretchable conjugated polymer films with good electrical performance under mechanical deformation are highly desirable for soft electronics. However, the mechanical and electrical properties of these films, particularly in conjugated polymer:elastomer blends, are not fully understood at molecular level. Here, this study explores the relationships among molecular structure, aggregation ability, film microstructure, and the electrical/mechanical properties of three diketopyrrolopyrrole-based conjugated polymers (P1, P2, P3) with decreasing backbone rigidity and their corresponding polymer:elastomer blends. The most flexible polymer P3 shows strong aggregation, which forms highly crystalline fibers to produce fragile neat film and produces large isolated crystallites restricting charge transport in blend film. As chain rigidity increases, the P1 and P2 polymers show weaker aggregation, and produce smaller crystallites in neat films with enhanced ductility. P1 and P2 based blend films display nanocrystallites polymer networks with dispersed elastomer domains. As a result, we achieved near-constant charge mobility before and after stretching under 50 % strain for P2-based blend films with well-controlled pathways for both charge transport and energy dissipation. This study demonstrates the critical role of backbone rigidity in regulating the properties of stretchable conjugated polymer films, paving the way for more reliable and deformable materials in soft electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Decoding the flow evolution in Au+Au reactions at 1.23 A GeV using hadron flow correlations and dileptons

We investigate the development of the directed, v 1 , and elliptic flow, v 2 , in heavy ion collisions in mid-central Au+Au reactions at E lab = 1.23A GeV. We demonstrate that the elliptic flow of hot and dense matter is initially positive (v 2 >0) due to the early pressure gradient. This positive v 2 transfers its momentum to the spectators, which leads to the creation of the directed flow v 1 . In turn, the spectator shadowing of the in-plane expansion leads to a preferred decoupling of hadrons in the out-of-plane direction and results in a negative v 2 for the observable final state hadrons. We propose a measurement of v 1 −v 2 flow correlations and of the elliptic flow of dileptons as methods to pin down this evolution pattern. The elliptic flow of the dileptons allows then to determine the early-state EoS more precisely, because it avoids the strong modifications of the momentum distribution due to shadowing seen in the protons. This opens the unique opportunity for the HADES and CBM collaborations to measure the Equation-of-State directly at 2-3 times nuclear saturation density.

Reichert, Tom↗
DOE OSTI2023

Atomically Local Electric Field Induced Interface Water Reorientation for Alkaline Hydrogen Evolution Reaction

The slow water dissociation process in alkaline electrolyte severely limits the kinetics of HER. The orientation of H 2 O is well known to affect the dissociation process, but H 2 O orientation is hard to control because of its random distribution. Herein, an atomically asymmetric local electric field was designed by IrRu dizygotic single-atom sites (IrRu DSACs) to tune the H 2 O adsorption configuration and orientation, thus optimizing its dissociation process. The electric field intensity of IrRu DSACs is over 4.00×10 10 N/C. The ab initio molecular dynamics simulations combined with in situ Raman spectroscopy analysis on the adsorption behavior of H 2 O show that the M–H bond length (M=active site) is shortened at the interface due to the strong local electric field gradient and the optimized water orientation promotes the dissociation process of interfacial water. This work provides a new way to explore the role of single atomic sites in alkaline hydrogen evolution reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Application of machine learning in the determination of impact parameter in the 132 Sn+ 124 Sn system

Here, 132 Sn + 124 Sn collisions at a beam energy of 270 MeV/nucleon were performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the nuclear equation of state. Reconstructing the impact parameter is one of the important tasks in the experiment as it relates to many observable. In this work, we employ three commonly used algorithms in machine learning, the artificial neural network (ANN), the convolutional neural network (CNN), and the light gradient boosting machine (LightGBM), to determine the impact parameter by analyzing either the charged particle spectra or several features simulated with events from the ultrarelativistic quantum molecular dynamics (UrQMD) model. To closely imitate experimental data and investigate the generalizability of the trained machine learning algorithms, incompressibility of nuclear equation of state and the in-medium nucleon-nucleon cross sections are varied in the UrQMD model to generate the training data. The mean absolute error Δb between the true and the predicted impact parameter is smaller than 0.45 fm if training and testing sets are sampled from the UrQMD model with the same parameter set. However, if training and testing sets are sampled with different parameter sets, Δb would increase to 0.8 fm. The generalizability of the trained machine learning algorithms suggests that these machine learning algorithms can be used reliably to reconstruct the impact parameter in experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗