Construction of a Mode-Combination Hamiltonian under the Grid-Based Representation for the Quantum Dynamics of OH + HO2 → O2 + H2O.

In this work, a systematic construction framework on a mode-combination Hamiltonian operator of a typical polyatomic reaction, OH + HO2 → O2 + H2O, is developed. First, a set of Jacobi coordinates are employed to construct the kinetic energy operator (KEO) through the polyspherical approach ( Phys. Rep. 2009, 484, 169). Second, due to the multiconfigurational electronic structure of this system, a non-adiabatic potential energy surface (PES) is constructed where the first singlet and triplet states are involved with spin-orbital coupling. To improve the training database, the training set of random energy data was optimized through a popular iterative optimization approach with extensive trajectories. Here, we propose an automatic trajectory method, instead of the classical trajectory on a crude PES, where the gradients are directly computed by the present ab initio calculations. Third, on the basis of the training set, the potential function is directly constructed in the canonical polyadic decomposition (CPD) form ( J. Chem. Theory Comput. 2021, 17, 2702-2713) which is helpful in propagating the nuclear wave function under the grid-based representation. To do this, the Gaussian process regression (GPR) approach for building the CPD form, called the CPD-GPR method ( J. Phys. Chem. Lett. 2022, 13, 11128-11135) is adopted where we further revise CPD-GPR by introducing the mode-combination (mc) scheme leading to the present CPD-mc-GPR approach. Constructing the full-dimension non-adiabatic Hamiltonian operator with mode combination, as test calculations, the nuclear wave function is propagated to preliminarily compute the reactive probability of OH + HO2 → O2 + H2O where the reactants are prepared in vibrational ground states and in the first triplet electronic state.

Chemistry-Informed Generative Model for Classical Dynamics Simulations.

In this work, a chemistry-informed generative model was proposed, leading to the chemistry-informed generative adversarial network (CI-GAN) approach. To easily build the input database for complex molecular systems, an image-input algorithm is also implemented, leading to the capability to directly recognize the molecular image. Extensive test calculations and analysis on typical examples, H + H2, OH + HO2, and H2O/TiO2(110), find that the present CI-GAN approach generates distributions of geometry and energy. Calculations on the above examples show that the present CI-GAN approach is able to generate 50%-80% meaningful results among all of the generated data with chemistry constraints. Thus, it has the potential capability to predict classical dynamics simulations as well as ab initio calculations avoiding expensive calculations. These results and the power of CI-GANs in generating ab initio energies and MD trajectories are deeply discussed.

Multilayer Multiconfiguration Time-Dependent Hartree Study on the Mode-/Bond-Specific Quantum Dynamics of Water Dissociation on Cu(111).

In this work, full-dimensional (9D) quantum dynamics calculations on mode-/bond-specific surface scattering of a water molecule on a copper (111) rigid surface are performed through the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) method. To easily perform the ML-MCTDH calculations on such a triatomic molecule-surface system, we first choose specific Jacobi coordinates as a set of coordinates of water. Next, to efficiently perform the 9D ML-MCTDH wavepacket propagation, the potential energy surface is transferred to a canonical polyadic decomposition form with the aid of a Monte Carlo-based method. Excitation-specific dissociation probabilities of H2O on Cu(111) are computed, and mode-/bond-specific dynamics are demonstrated by comparison with a probability curve computed for a water molecule in the ground state. The dependence of the dissociation probability of the initial state of H2O is studied, and it is found that the excitation-specific dissociation probabilities can be divided into three groups. We find that the vibrationally excited states enhance the dissociation reactivity of H2O, while the rotationally excited states hardly influence it.

Distribution modes of residual carbon and ash in coal gasification fine slag and its feasibility analysis as particle electrodes.

From the perspective of environmental protection and resource utilization, the feasibility of treating m-cresol wastewater with coal gasification fine slag (GFS) as particle electrodes in an electrocatalytic system was evaluated to achieve the purpose of treating waste with waste. Characterization by scanning electron microscope (SEM), Brunauer-Emmett-Teller (BET), Raman, and fourier transform infrared spectroscopy (FTIR) confirmed that the GFS featured a diverse inorganic framework, large specific surface area (as large as above 155 m2 g-1), hierarchical porous structure, and plenty of catalytic sites. The Venn diagram method was used to systematically propose the following distribution modes of residual carbon (RC) and ash in GFS: discrete distribution, embedded distribution, crosslinked distribution, and association and bonding. Only 8 g L-1 of GFS particle electrodes prevented the formation of a yellow sticky passivation film on the anode. Compared to the two-dimensional electrocatalytic system (47.89%), the wastewater treatment efficiency was increased by 108.81%. Zero-order kinetic results showed that the reaction rate constant was the highest (2.1106 mg L-1·min-1) when the secondary flotation RC was adopted as particle electrodes. It was indicated that GFS in discrete mode played either no role or at most a minor role. Last but not least, the synergy of RC and ash was revealed from a molecular perspective. The RC exhibited hierarchical microporous/mesoporous/macroporous structure, which facilitated the entry of H2O2 into the catalytic sites of ash. Abundant catalytic sites in ash accelerated adsorption and oxidation processes on RC surfaces.

Solving two industrial waste issues simultaneously: Coal gasification fine slag-based hierarchical porous composite with enhanced CO2 adsorption performance.

The coal gasification fine slag (FS) is industrial waste consisting of residual carbon (RC) and slag particles (SP). High-performance hierarchical porous composite (HPC) was synthesized by chemical activation followed by hydrothermal treatment from FS. It has been realized that SP could play the positive role in developing pore structure of HPC which makes CO2 uptake have a sharp increase. Through taking the advantage of SP, HPC has an obvious increase in surface area and pore volume from 914 to 1932 m2/g and 0.617 to 1.332 cm3/g, respectively. The changes of pore structure were mainly attributed to the two factors in a synergetic way. First, hydrothermal treatment could decrease the content of SP which acted as a ballast to reduce the surface area of activated carbon. Second, the formed silicate/aluminosilicate deposits on the carbon surface and forms silicate/aluminosilicate film on internal surface of carbon particles. This makes the meso-macropores change to micro- mesopores leading to the increase of the surface area and pore volume. The porous composites also showed high CO2 adsorption performance. The 4-FSAC-HPC sample exhibits the highest CO2 uptake of 3.25 mol/kg and 1.41 mol/kg at 25 and 50 °C, respectively, which is an increase of around 52% and 83% comparing with that of FSAC sample. Besides, CO2 adsorption up to saturation can be achieved in less than 3 min. CO2 uptake of the 4-FSAC-HPC sample was well regeneration efficiencies above 98% after 10 cycles adsorption/desorption. This work provides a new approach to prepare high-performance porous compositions using the material which contains not only carbon component but mineral matters. Furthermore, it realizes solving two industrial waste issues (fine slag and CO2) simultaneous.

Parameter optimization of waste coal briquetting and particulate matter emissions test during combustion: A case study.

The abundant coal powder generated as a waste by-product during the lignite upgrading process is harmful to the environment. Lignite briquetting offers a practical solution for lignite usage. Altering the process parameters of briquetting can significantly improve briquette quality. In this paper, the characteristics of lignite briquettes, including drop strength and compressive strength were investigated. A combination of quadratic orthogonal rotation combination designs and regression equations established the best process parameters to be 40% weight of #2 upgraded coal, 20% weight of briquetting moisture, 25 MPa of briquetting pressure, and 12 h of drying time. The low error variance of the drop strength and compressive strength, at 0.01% and 1.83% respectively, verified the feasibility of the model. The analysis by scanning electron microscope (SEM) showed that the surface morphology of briquette was denser than that of raw coal. Finally, the combustion test of briquettes revealed that the particulate matter emission (PM2.5) of briquette was 16.7% lower than that of raw coal. In summary, these data provide a theoretical reference for realizing the reasonable utilization potential of waste products derived from industrial processes.