Heng Dong

ORCID: 0000-0003-2281-5983
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Research Areas
  • Advanced Photocatalysis Techniques
  • Advanced battery technologies research
  • Catalytic Processes in Materials Science
  • Advanced oxidation water treatment
  • Microbial Fuel Cells and Bioremediation
  • Supercapacitor Materials and Fabrication
  • CO2 Reduction Techniques and Catalysts
  • Pharmaceutical and Antibiotic Environmental Impacts
  • Electrochemical Analysis and Applications
  • Industrial Gas Emission Control
  • Electrochemical sensors and biosensors
  • Gas Sensing Nanomaterials and Sensors
  • Ionic liquids properties and applications
  • Advanced Nanomaterials in Catalysis
  • Electrocatalysts for Energy Conversion
  • Nanomaterials for catalytic reactions
  • Pancreatic and Hepatic Oncology Research
  • Business Process Modeling and Analysis
  • Diamond and Carbon-based Materials Research
  • Ammonia Synthesis and Nitrogen Reduction
  • Biofuel production and bioconversion
  • Stochastic processes and statistical mechanics
  • Artificial Intelligence in Law
  • Membrane Separation Technologies
  • Carbon dioxide utilization in catalysis

Nankai University
2014-2023

The microbial fuel cell (MFC), being an environment-friendly technology for wastewater treatment, is limited by low efficiency and high cost. Power output based on capital cost had been greatly increased in our previous work introducing a novel activated carbon (AC) air-cathode (ACAC). catalysis behavior of this ACAC was studied here kinetics pore analysis both powders catalyst layers (CLs). Plain AC (AC1#), ultracapacitor (AC2#), non-AC (XC-72) were used as catalysts. electron transfer...

10.1021/es303619a article EN Environmental Science & Technology 2012-11-14

Current gas diffusion electrodes (GDEs) for electrochemical reduction of carbon dioxide to formic acid (ERCF) suffer from poor catalyst utilization or high cost. In this work, we developed a novel Sn GDE (SGDE) consisting PTFE-bound layer produced using the rolling-press method and Nafion-bound synthesised by spraying. The influence loading, Nafion fraction electrolytic potential was studied. results showed that increasing loading in an appropriate range both led improvement ERCF via...

10.1039/c4ra10775f article EN RSC Advances 2014-10-29

Abstract BACKGROUND: Pt‐free cathodic catalyst is needed for microbial fuel cells (MFCs). Perovskite‐type oxide could be a substitute Pt because it has been proved to highly active and low‐cost oxygen reduction in chemical cells. RESULTS: A nano‐sized La 0.4 Ca 0.6 Co 0.9 Fe 0.1 O 3 perovskite‐type on carbon support (LCCF/C) was prepared tested its performance stability (15 cycles) MFCs. An exchange current density of 7.030 × 10 −5 (A cm −2 ) obtained with fresh LCCF/C cathode increased...

10.1002/jctb.3893 article EN Journal of Chemical Technology & Biotechnology 2012-08-07

Using a two-layer gas diffusion electrode for ERCF in MEC, the Faraday efficiency was improved by 36.1%.

10.1039/c4ra14535f article EN RSC Advances 2015-01-01

Electroreduction of CO2 to formic acid (ERCF) based on gas diffusion electrodes (GDEs) has been considered as a promising method convert into value-added chemicals. However, current GDEs for ERCF suffer from low efficiency electron transfer. In this work, novel Sn-based electrode (ESGDE) is prepared by electrodepositing Sn Nafion-bonded carbon black catalyst layer enhance transfer and thus the ERCF. The highest Faraday (73.01 ± 3.42%), density (34.21 1.14 mA cm-2) production rate (1772.81...

10.1038/s41598-017-14233-y article EN cc-by Scientific Reports 2017-10-16

As humans increasingly share environments with diverse agents powered by RL, LLMs, and beyond, the ability to explain their policies in natural language will be vital for reliable coexistence. In this paper, we build a model-agnostic explanation generator based on an LLM. The technical novelty is that rewards training LLM are generated generative flow matching model. This model has specially designed structure hidden layer merged harness linguistic cues of explanations into generating...

10.48550/arxiv.2502.12530 preprint EN arXiv (Cornell University) 2025-02-17
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