Chemical Software Research Articles

Evaluation of a Minimum Liquid Discharge (MLD) Desalination Approach for Management of Unconventional Oil and Gas Produced Waters with a Focus on Waste Minimization

The objective of this research study was to evaluate the feasibility of using a minimum liquid discharge (MLD) desalination approach as an alternate management option for unconventional produced waters (PWs) with a focus on minimizing the generation of solid waste. The feasibility of MLD was evaluated using OLI, a water chemistry software, to model thermal desalination of unconventional PWs from the Delaware Basin in New Mexico (NM). Desalination was theoretically terminated at an evaporation point before halite (NaCl) saturation in the residual brine. Results of this study showed that selectively targeting a subset of higher flow rate and lower TDS wells/centralized tank batteries (CTBs) could yield up to 76% recovery of distillate while generating minimal solid waste. Using a selective MLD approach did reduce the quantity of distillate recovered when compared with ZLD, and left a reduced volume of residual brine which has to be managed as a liquid waste. However, selective MLD also greatly reduced the amount of solid waste. The use of a ZLD approach yielded incrementally greater quantities of distillate but at the cost of large quantities of difficult-to-manage highly soluble waste. Simulation results showed that waste generated before NaCl precipitation was primarily composed of insoluble compounds such as calcite, barite and celestite, which can be disposed in conventional landfills. This study also found a simple empirical linear relationship between TDS and distillate recovery, thus allowing a non-expert to rapidly estimate potential distillate recovery for a given starting PW quality.

Local approaches for electric dipole moments in periodic systems and their application to real-time time-dependent density functional theory.

Within periodic boundary conditions, the traditional quantum mechanical position operator is ill-defined, necessitating the use of alternative methods, most commonly the Berry phase formulation in the modern theory of polarization. Since any information about local properties is lost in this change of framework, the Berry phase formulation can only determine the total electric polarization of a system. Previous approaches toward recovering local electric dipole moments have been based on applying the conventional dipole moment operator to the centers of maximally localized Wannier functions (MLWFs). Recently, another approach to local electric dipole moments has been demonstrated in the field of subsystem density functional theory (DFT) embedding. We demonstrate in this work that this approach, aside from its use in ground state DFT-based molecular dynamics, can also be applied to obtain electric dipole moments during real-time propagated time-dependent DFT (RT-TDDFT). Moreover, we present an analogous approach to obtain local electric dipole moments from MLWFs, which enables subsystem analysis in cases where DFT embedding is not applicable. The techniques were implemented in the quantum chemistry software CP2K for the mixed Gaussian and plane wave method and applied to cis-diimide and water in the gas phase, cis-diimide in aqueous solution, and a liquid mixture of dimethyl carbonate and ethylene carbonate to obtain absorption and infrared spectra decomposed into localized subsystem contributions.

Effect of ZnO-SiO2 Composite Abrasive on Sapphire Polishing Performance and Mechanism Analysis

Sapphire is widely used because of its excellent physical and chemical properties, and the requirements for its surface quality and processing efficiency are becoming more stringent. Chemical mechanical polishing (CMP) has been widely used to achieve non-damaged and atomically smooth surfaces on sapphire wafers. To promote the removal rate and surface quality, the effect of ZnO-SiO2 composite abrasive on sapphire CMP performance was studied. A higher material removal rate and lower Root mean squared surface roughness (Sq) (less than 0.3 nm) were obtained with the ZnO nano-particle slurry. HSC chemistry software was used to calculate the Gibbs free energy of possible chemical reactions between sapphire, SiO2, H2O, and ZnO to determine whether new reactions can occur. At the same time, the action and removal mechanism of sapphire using the ZnO-SiO2 composite slurry were investigated. X-ray photoelectron spectroscopy showed that the new reaction was produced and the product of the solid-state reaction was ZnAl2O4. In addition, only a hydration layer was observed on the surface of soaked sapphire in ZnO-based slurry, while the solid-state reaction products of Al2SiO5/Al2SiO5(OH)4 and ZnAl2O4 existed on the surface of polished sapphire. This indicates that mechanical processing provides energy or conditions which can promote chemical effects during CMP and lead to solid-phase reactions. Finally, a mechanochemical effect is introduced to explain the mechanism of solid state reaction in sapphire CMP process, which has a certain guiding significance to the mechanism analysis of CMP for different materials.

Ab Initio Direct Dynamics.

The reactivity and dynamics of molecular systems can be explored computationally by classical trajectory calculations. The traditional approach involves fitting a functional form of a potential energy surface (PES) to the energies from a large number of electronic structure calculations and then integrating numerous trajectories on this fitted PES to model the molecular dynamics. The ever-decreasing cost of computing and continuing advances in computational chemistry software have made it possible to use electronic structure calculations directly in molecular dynamics simulations without first having to construct a fitted PES. In this "on-the-fly" approach, every time the energy and its derivatives are needed for the integration of the equations of motion, they are obtained directly from quantum chemical calculations. This approach started to become practical in the mid-1990s as a result of increased availability of inexpensive computer resources and improved computational chemistry software. The application of direct dynamics calculations has grown rapidly over the last 25 years and would require a lengthy review article. The present Account is limited to some of our contributions to methods development and various applications. To improve the efficiency of direct dynamics calculations, we developed a Hessian-based predictor-corrector algorithm for integrating classical trajectories. Hessian updating made this even more efficient. This approach was also used to improve algorithms for following the steepest descent reaction paths. For larger molecular systems, we developed an extended Lagrangian approach in which the electronic structure is propagated along with the molecular structure. Strong field chemistry is a rapidly growing area, and to improve the accuracy of molecular dynamics in intense laser fields, we included the time-varying electric field in a novel predictor-corrector trajectory integration algorithm. Since intense laser fields can excite and ionize molecules, we extended our studies to include electron dynamics. Specifically, we developed code for time-dependent configuration interaction electron dynamics to simulate strong field ionization by intense laser pulses. Our initial application of ab initio direct dynamics in 1994 was to CH2O → H2 + CO; the calculated vibrational distributions in the products were in very good agreement with experiment. In the intervening years, we have used direct dynamics to explore energy partitioning in various dissociation reactions, unimolecular dissociations yielding three fragments, reactions with branching after the transition state, nonstatistical dynamics of chemically activated molecules, dynamics of molecular fragmentation by intense infrared laser pulses, selective activation of specific dissociation channels by aligned intense infrared laser fields, angular dependence of strong field ionization, and simulation of sequential double ionization.

Direct microalloying of steel with cerium under slags of СаО–SiO 2 – Ce2O3– 15 % Al2O3 –8 % MgO system with additional reducing agents

An assessment of the possibility of steel direct microalloying with cerium was performed using thermodynamic modeling of cerium reduction from slags of CaO– SiO2– Ce2O3 system containing 15 % Al2O3 and 8 % МgO, additional additives of reducing agents (aluminum or ferrosilicoaluminium), at temperatures of 1550 and 1650 °C using the HSC 6.1 Chemistry (Outokumpu) software package. Depending on the additional additives of aluminum or ferroglycoaluminium, metal temperature, slag basicity and content of cerium oxide, 0.228 to 40.5 ppm of cerium transfers into the metal. With an additional additive of aluminum from slag (Y1) containing 1.0 % of cerium oxide, 0.228 ppm of cerium is transferred to the metal at 1550 °C. An increase in the system temperature to 1650 °C is accompanied by a slight increase in cerium content, reaching no more than 0.323 ppm. When added to ferrosilicoaluminium metal, cerium content in the metal is higher and amounts to 0.402 and 0.566 ppm at 1550 and 1650 °C, respectively. When concentration of cerium oxide in the slag (Y2) increases to 7.0 %, more signifcant increase in cerium content in the metal is observed, reaching in temperature range of 1550 – 1650 °C, 1.65 – 2.31 ppm with aluminum additives and 2.90 – 4.05 ppm with ferrosilicoaluminium additives. The most noticeable increase in cerium content in the metal is observed with an increase in slag basicity. During formation of slags with basicity of 2 – 3, containing 1 – 7 % Ce2O3, the equilibrium concentration of cerium in the metal varies from 0.5 to 4 ppm with aluminum additives and 1 – 7 ppm with ferro­silicoaluminium additives at 1550 °C. Slags transfer to the increased (up to 3 – 5) basicity is accompanied by an increase in the equilibrium content of cerium in the metal to 4 – 12 ppm with aluminum additives and 7 – 20 ppm with ferrosilicoaluminium additives at Ce2O3 content of 3 – 7 % and, as a result, an increase in efciency of cerium reduction process.

GQCP: The Ghent Quantum Chemistry Package.

The Ghent Quantum Chemistry Package (GQCP) is an open-source electronic structure software package that aims to provide an intuitive and expressive software framework for electronic structure software development. Its high-level interfaces (accessible through C++ and Python) have been specifically designed to correspond to theoretical concepts, while retaining access to lower-level intermediates and allowing structural run-time modifications of quantum chemical solvers. GQCP focuses on providing quantum chemical method developers with the computational "building blocks" that allow them to flexibly develop proof of principle implementations for new methods and applications up to the level of two-component spinor bases.

Theoretical and Experimental Studies of Sulfur and Boron Distribution between the Slag of the CaO-SiO<sub>2</sub>-B<sub>2</sub>O<sub>3</sub>-MgO-Al<sub>2</sub>O<sub>3</sub> System and the Metal

The equilibrium interfacial distribution of sulfur and boron was estimated using the HSC 6.1 Chemistry software package (Outokumpu) and the simplex-lattice planning method. Adequate mathematical models have been constructed in the form of III degree polynomial, which describe the effect of the composition of the studied oxide system on the equilibrium distribution of sulfur and boron between the slag and the metal. Generalization of the results of experimental studies and thermodynamic modeling made it possible to obtain new data on the influence of the basicity and content of B2O3 in the slag of the CaO-SiO2-B2O3-MgO-Al2O3 system on the interphase distribution of sulfur and boron. It was found that in the range of boron oxide concentration of 1.0-10%, an increase in slag basicity from 2 to 5 at 1600°C leads to an increase in the sulfur distribution coefficient from 1 to 20 and, as a consequence, a decrease in the sulfur content in the metal from 0.02 to 0.0014 %, i.e. an increase in slag basicity favorably affects the development of the metal desulfurization process. An increase in the B2O3 content from 2.0 to 10.0% in slags formed in the region of moderate basicity, not exceeding 2-3, is accompanied at 1600°C by a decrease in the boron interphase distribution coefficient from 450 to 150 and an increase in the boron concentration in the metal from 0.006 to 0.021 %, which indicates the progress of boron reduction from slag to metal. The shift of the formed slags to the area of ​​increased basicity up to 5.0 shows a high degree of boron reduction from slag to metal. The results of the laboratory experiment confirmed the results of thermodynamic modeling.

Effect of Basicity and Boron Oxide in Slags of the AOD Process on the Equilibrium Interphase Distribution of Sulfur and Boron

The use of fluorspar in modern metallurgical slags, incl. slags of the argon-oxygen decarburization (AOD) process, as a fluxing agent, is associated with many disadvantages. Those disadvantages can be solved by using boron oxide as an alternative, which also provides conditions for direct microalloying of steel with boron. The paper presents the results of thermodynamic modeling of the effect of basicity and boron oxide content in slags of the CaO–SiO2–B2O3–Cr2O3–Al2O3–MgO system on the equilibrium interphase distribution of sulfur and boron, and their equilibrium content in the metal. Modeling was carried out using the HSC 8.03 Chemistry software package (Outokumpu). Slag from the desulfurization period of the AOD-process was used as the oxide phase. As a result, it was shown that, in the range of basicities 2.0-2.5 and a content of 2-4% B2O3, it is possible to carry out desulfurization of the metal, providing a sulfur content of 0.001-0.007%, and simultaneous microalloying of steel with boron in an amount of up to 0.0103%.

Application of Zn-ferrite towards thermochemical utilization of carbon dioxide: A thermodynamic investigation

This study reports a thermodynamic analysis of ZnFe2O4 based CO2 splitting cycle. The model developed is evaluated by using HSC Chemistry software. Effects of the influence of the ratio of the molar flow rate of inert sweep gas to the molar flow rate of ZnFe2O4, thermal reduction temperature, and gas-to-gas heat recovery effectiveness on thermal energy required to drive the cycle and the solar-to-fuel energy conversion efficiency are investigated at reduction nonstoichiometry of 0.1. The decrease in the reduction temperature is significant when the ratio of the molar flow rate of inert sweep gas to the molar flow rate of ZnFe2O4 increases from 10 to 30. At a steady gas-to-gas heat recovery effectiveness equal to 0.7, a rise in the ratio of the molar flow rate of inert sweep gas to the molar flow rate of ZnFe2O4 from 10 to 90 is responsible for an increase in the thermal energy required to drive the cycle above 184.9 kW by a factor of 1.45 and decrease in the solar-to-fuel energy conversion efficiency by 4%. At gas-to-gas heat recovery effectiveness equal to 0, the difference between the thermal energy required to drive the cycle at the ratio of the molar flow rate of inert sweep gas to the molar flow rate of ZnFe2O4 equal to 10 and 100 is 346.5 kW. However, as the gas-to-gas heat recovery effectiveness increases to 0.9, this difference decreases to 11.8 kW. Because of this, the reduction in the solar-to-fuel energy conversion efficiency also drops to 0.6%. Therefore, a maximum possible solar-to-fuel energy conversion efficiency equal to 16.8% can be achieved.

Twitter integration of chemistry software tools

Social media activity on a research article is considered to be an altmetric, a new measure to estimate research impact. Demonstrating software on Twitter is a powerful way to attract attention from a larger audience. Twitter integration of software can also lower the barriers to trying the tools and make it easier to save and share the output. We present three case studies of Twitter bots for cheminformatics: retrosynthetic analysis, 3D molecule viewer, and 2D chemical structure editor. These bots make software research more accessible to a broader range of people and facilitate the sharing of chemical knowledge, concepts, and ideas.

Chemical post-processing of magneto-hydrodynamical simulations of star-forming regions: robustness and pitfalls

ABSTRACT A common approach to model complex chemistry in numerical simulations is via post-processing of existing magneto-hydrodynamic simulations, relying on computing the evolution of chemistry over the dynamic history of a subset of particles from within the raw simulation. Here, we validate such a technique, assessing its ability to recover the abundances of chemical species, using the chemistry package krome. We also assess, for the first time, the importance of the main free input parameters, by means of a direct comparison with a self-consistent state-of-the-art simulation in which chemistry was directly coupled to hydrodynamics. We have found that the post-processing is highly reliable, with an accuracy at the per cent level, even when the most relaxed input parameters are employed. In particular, our results show that the number of particles used does not affect significantly the average properties, although it suppresses the appearance of possibly important spatial features. On the other hand, the choice of the integration time-step plays a crucial role. Longer integration time-steps can produce large errors, as the post-processing solution will be forced towards chemical equilibrium, a condition that does not always necessarily apply. When the interpolation-based reconstruction of chemical properties is performed, the errors further increase up to a factor of ∼2. Concluding, our results suggest that this technique is extremely useful when exploring the relative quantitative effect of different chemical parameters and/or networks, without the need of re-running simulations multiple times, but some care should be taken in the choice of particles sub-sample and integration time-step.

Quantum Chemistry Estimation of Adhesion Strength of Hydroxyapatite with Titanium Substrate

One of the ways to improve the fusion of an implant with bone tissue is through the use of biocompatible coatings, in particular, hydroxyapatite (HAp). It is important to assess the strength of the HAp adhesion to the implant. The measure of the strength of the bond of the coating with the substrate is the energy of this bond. Using density functional theory and molecular dynamics, the reaction path, reaction products, oscillation frequency, activation energy and bond energy between different combinations of component anions HAp and Ti (II) – the standard material of implants – are calculated. Using the computational chemistry software suite Gaussian 09 (Revision C.01 was used), the stable configurations of the reactants and products are found, and the binding energy of hydroxyapatite and titanium is then calculated based on the difference in ground energy of reactants and ground energy of products. Thus, the method of adhesion strength estimation between HAp coatings and Ti is proposed based on numerical calculations using MD software, and suggestions are provided on which conditions would be the best for optimal binding strength.

Structurally explicit composition model of petroleum vacuum residue

The molecular modeling of fuels requires comprehensive composition data: names and molar fractions of the components. For fuels like petroleum residues, two problems arise: first, state-of-the-art analytical techniques can not detect the full list of molecule names, and second, this list would lead to a number of components that is unmanageable. A comprehensive composition can be modeled by the use of stochastic models that generate a combination of digital molecules whose global properties are close to the properties of the fuel under study. The current models only offer a set of representative molecules, from which an enormous number of different structures may be inferred. Different structures result in multiple initial conditions of a detailed kinetic model or conflicting results in a computational chemistry software. For an end user, it would be easy to build impossible structures that violate the rules of chemistry while interpreting the representative structures. To address these difficulties, a computer program was created which is able to model composition of any vacuum residue with unambiguous molecules. A custom-made molecule core library and a “molecular sieve” have been introduced, which consents generation of species that are proven to exist experimentally. Data analysis of the experimental results of three vacuum residues was performed and compared with simulation results. SARA separation simulation was executed for model validation. Detailed molecular class fractions of the simulation were provided; many distributions that are challenging to obtain by the use of experimentation were presented to better understand the molecular structures inside a vacuum residue.

Determination of corrosion products for steam and flue gas injection environments using thermodynamic simulation

Thermal recovery processes using steam injection with combustion gases (flue gas) have shown positive results in the recovery of heavy crude oil over the conventional process, by integrating different recovery mechanisms. However, under the operating conditions, the injection of these fluids generates highly corrosive environments that have an impact on the deterioration of the materials, resulting in risks and operational costs. Therefore, it is necessary to determine the theoretical corrosion products that can be generated in these processes. This research focused on the study of API N-80 carbon steel exposed to a steam and flue gas atmosphere, at pressure and temperature conditions in the ranges of 800 psia - 1100 psia (55 bar - 75 bar) and 520 °F - 560 °F (270 °C - 290 °C) respectively. Based on this environment, to determine the theoretical corrosion products, a thermodynamic simulation stage was developed using HSC Chemistry software, which was used to generate Pourbaix, Ellingham and thermodynamic equilibrium diagrams. It was found that the main theoretical corrosion products corresponded to oxides, carbonates, and hydroxides, among which the significant presence of iron (III) oxide (Fe2O3), iron (II, III) oxide (Fe3O4) and iron carbonate (II) (FeCO3) was corroborated.

Modelling H2 and its effects on star formation using a joint implementation of gadget-3 and KROME

ABSTRACT We present p-gadget3-k, an updated version of gadget-3, that incorporates the chemistry package krome. p-gadget3-k follows the hydrodynamical and chemical evolution of cosmic structures, incorporating the chemistry and cooling of H2 and metal cooling in non-equilibrium. We performed different runs of the same ICs to assess the impact of various physical parameters and prescriptions, namely gas metallicity, molecular hydrogen formation on dust, star formation recipes including or not H2 dependence, and the effects of numerical resolution. We find that the characteristics of the simulated systems, both globally and at kpc-scales, are in good agreement with several observable properties of molecular gas in star-forming galaxies. The surface density profiles of star formation rate (SFR) and H2 are found to vary with the clumping factor and resolution. In agreement with previous results, the chemical enrichment of the gas component is found to be a key ingredient to model the formation and distribution of H2 as a function of gas density and temperature. A star formation algorithm that takes into account the H2 fraction together with a treatment for the local stellar radiation field improves the agreement with observed H2 abundances over a wide range of gas densities and with the molecular Kennicutt–Schmidt law, implying a more realistic modelling of the star formation process.

Thermal Desalination of Produced Water—An Analysis of the Partitioning of Constituents into Product Streams and Its Implications for Beneficial Use Outside the O&G Industry

To understand partitioning of produced water (PW) constituents using thermal desalination, PW from the Delaware Basin was desalinated using a crystallization process and modeled using OLI Systems, Inc. (OLI, Parsippany, NJ, USA) chemistry software. The incorporation of a pretreatment step, steam stripping, prior to desalination was predicted to be effective at removing hydrocarbons (across a range of volatilities). As expected, inorganics were almost completely retained in the residual brine which was confirmed by OLI. As evaporation progressed, sparingly soluble compounds such as gypsum and celestite precipitated first and overall solids production at this stage was low (<1% of total solids). Further evaporation resulted in saturation of the residual brine with respect to NaCl, which started to precipitate in bulk up to a practical desalination limit of approximately 68% by mass (approximately 80% by volume). Beyond this point, the residual brine and solids mixture became too viscous to be pumped. Gravimetrically determined total dissolved solids (TDS) for PW, distillate and residual brine was found to be much higher than prediction, potentially due to the presence of neutral species, unstripped gases and organic (likely hydrophilic) constituents. Although the distillate had low TDS, the presence of unknown constituents including organic compounds in the distillate will likely require polishing treatment to mitigate potential toxicity associated with such compounds or transformation products post-release if discharged to the environment. OLI predicted near-complete retention of acetate in the residual brine. In contrast, laboratory tests showed nearly 50% partitioning of acetate into the distillate. Although not modeled, propionate partitioning was even higher at 94%. The inclusion of ammonia as an input species in OLI greatly improved the match between test data and model prediction. Additionally, it was hypothesized that acetic acid/acetate could have formed a volatile adduct with ammonia that increased its volatility and partitioning into the distillate. The findings of this study inform beneficial use by describing the chemical composition of desalination-derived distillate, brine and salt products. This study also identified alternative approaches, both treatment and non-treatment, for managing PW from unconventional operations.

Thermodynamic Modeling of Reduction of Cerium from Slags of CaO–SiO2–Ce2O3–15Al2O3–8MgO by Calcium Carbide Additives

Thermodynamic modeling of the reduction of cerium from slags of the CaO–SiO2–Ce2O3 system containing 15% Al2O4 and 8% MgO, with aluminum dissolved in the metal together with calcium carbide additives at temperatures of 1550 and 1650°C was performed using the HSC 8.03 Chemistry software package (Outokumpu) based on the simplex lattice planning method used to minimize Gibbs energy. The results of thermodynamic modeling are presented in the form of composition-property diagrams (equilibrium content of cerium in the metal) for temperatures of 1550 and 1650°C. It is shown that the formation of slags within a basicity range of 2–3 containing 1–7% Ce2O3 provides an equilibrium concentration of cerium in the metal varying from 1 to 7 ppm at a temperature of 1550°C. The displacement of slags in the area of increased basicity (up to 3–5) is accompanied by an increase in the equilibrium concentration of cerium in the metal up to 7–23 ppm with a content of 3–7% Ce2O3 and as a consequence an increase in the efficiency of the process of cerium reduction. At a temperature of 1650°C, the equilibrium concentration of cerium in the metal within the basicity range of 2–3 and having a Ce2O3 content of 1–7% varies from 2 to 12 ppm. The displacement of slags in the area of increased basicity (up to 3–5) is accompanied by an increase in the equilibrium concentration of cerium in the metal to 7–33 ppm with a Ce2O3 content of 3–7%. The positive influence of the temperature factor basicity of slags and the content of cerium oxide on the process of its reduction is qualitatively explained from the standpoint of the formation of the phase composition of the slags of the studied oxide system and the thermodynamics of chemical reactions of reduction of cerium with aluminum dissolved in the metal, as well as with aluminum dissolved in the metal together with calcium carbide additives.

The Future of Ligand Engineering in Colloidal Semiconductor Nanocrystals.

ConspectusNext-generation colloidal semiconductor nanocrystals featuring enhanced optoelectronic properties and processability are expected to arise from complete mastering of the nanocrystals’ surface characteristics, attained by a rational engineering of the passivating ligands. This aspect is highly challenging, as it underlies a detailed understanding of the critical chemical processes that occur at the nanocrystal–ligand–solvent interface, a task that is prohibitive because of the limited number of nanocrystal syntheses that could be tried in the lab, where only a few dozen of the commercially available starting ligands can actually be explored. However, this challenging goal can be addressed nowadays by combining experiments with atomistic calculations and machine learning algorithms. In the last decades we indeed witnessed major advances in the development and application of computational software dedicated to the solution of the electronic structure problem as well as the expansion of tools to improve the sampling and analysis in classical molecular dynamics simulations. More recently, this progress has also embraced the integration of machine learning in computational chemistry and in the discovery of new drugs. We expect that soon this plethora of computational tools will have a formidable impact also in the field of colloidal semiconductor nanocrystals.In this Account, we present some of the most recent developments in the atomistic description of colloidal nanocrystals. In particular, we show how our group has been developing a set of programs interfaced with available computational chemistry software packages that allow the thermodynamic controlling factors in the nanocrystal surface chemistry to be captured atomistically by including explicit solvent molecules, ligands, and nanocrystal sizes that match the experiments. At the same time, we are also setting up an infrastructure to automate the efficient execution of thousands of calculations that will enable the collection of sufficient data to be processed by machine learning.To fully capture the power of these computational tools in the chemistry of colloidal nanocrystals, we decided to embed the thermodynamics behind the dissolution/precipitation of nanocrystal–ligand complexes in organic solvents and the crucial process of binding/detachment of ligands at the nanocrystal surface into a unique chemical framework. We show that formalizing this mechanism with a computational bird’s eye view helps in deducing the critical factors that govern the stabilization of colloidal dispersions of nanocrystals in an organic solvent as well as the definition of those key parameters that need to be calculated to manipulate surface ligands. This approach has the ultimate goal of engineering surface ligands in silico, anticipating and driving the experiments in the lab.

Computational Chemistry Activities with Avogadro and ORCA

Computational chemistry modeling activities that took place as part of a course in physical chemistry are described. The main software tools used by the students were Avogadro and ORCA, which are freely available on the Internet for academic use. Avogadro is molecular visualization software, which can be used not only to prepare input files for a range of computational chemistry software but also to visualize output files from them. ORCA is an ab initio quantum chemistry program containing modern electronic structure methods, such as density functional theory, many-body perturbation, coupled cluster, multireference methods, and semiempirical quantum chemistry methods. Four introductory level computational chemistry activities are described for use in general chemistry and physical chemistry laboratory courses and all are suitable for virtual learning environments. Details of our implementation and the educational value of this work are discussed. In addition, a Student Assessment of their Learning Gains (SALG) survey was conducted after the implementation and the results are reported.

Multiscale Models for Light-Driven Processes.

Multiscale models combining quantum mechanical and classical descriptions are a very popular strategy to simulate properties and processes of complex systems. Many alternative formulations have been developed, and they are now available in all of the most widely used quantum chemistry packages. Their application to the study of light-driven processes, however, is more recent, and some methodological and numerical problems have yet to be solved. This is especially the case for the polarizable formulation of these models, the recent advances in which we review here. Specifically, we identify and describe the most important specificities that the polarizable formulation introduces into both the simulation of excited-state dynamics and the modeling of excitation energy and electron transfer processes.