Geometry optimization in Cartesian coordinates: Constrained optimization

An efficient algorithm for constrained geometry optimization in Cartesian coordinates is presented. It incorporates mode-following techniques within both the classical method of Lagrange multipliers and the penalty function method. Both constrained minima and transition states can be located and, unlike the standard Z-matrix using internal coordinates, the desired constraints do not have to be satisfied in the initial structure. The algorithm is as efficient as a Z-matrix optimization while presenting several additional advantages.     

Information theory of optimization in chromatography: Analytical structure of optimization

Summary The analytical roles of chromatographic variables (column length, etc.) can be soundly comprehended and compared in terms of the precision (Φ) of measurements and efficiency (ϑ) of analysis which are described as Shannon information and information flow, respectively. The φϑ plots of the optimization process and the information Φ transmitted by a single peak are useful to understand the analytical structure of optimization. Variables treated here are mobile phase composition (X), column length (L), mobile phase velocity rate (u), detection wavelength (λ) and plate number (N).     

Structural optimization of Cu-Ag-Au trimetallic clusters by adaptive immune optimization algorithm

The putative global minimum structures of Cu-Ag-Au trimetallic clusters with 19 and 55 atoms are obtained by adaptive immune optimization algorithm (AIOA) with the Gupta potential. For the 19-atom trimetallic clusters, the results indicate that all of them have double-icosahedral motifs. For the optimized structures of Cu(13)Ag(n)Au(42-n) (n = 1-41), the clusters can be categorized into 19 Mackay icosahedral structures, 1 6-fold pancake structure, and 21 ring-like structures linked by three face-sharing double-icosahedra. Furthermore, the segregation phenomena of the Cu, Ag, and Au atoms in the Cu-Ag-Au trimetallic clusters are studied to provide useful information for geometric character. Results show that Cu and Ag atoms prefer to locate in the inner-shell and on the surface, respectively, whereas Au atoms mainly locate in the middle-shell and tend to solve into Cu and Ag atoms.     

Bottom-up optimization of SERS hot-spots

The bottom-up optimization of signal-to-noise ratios for SERS tags employing SAMSA fluorescein as the reporter was achieved using a bifunctional linker with low Raman cross section. By holding the nanoparticles at subnanometer separation, the linker allowed us to optimize the hot-spot thereby significantly reducing the fluorescence background.     

Lead optimization mapper: automating free energy calculations for lead optimization

Alchemical free energy calculations hold increasing promise as an aid to drug discovery efforts. However, applications of these techniques in discovery projects have been relatively few, partly because of the difficulty of planning and setting up calculations. Here, we introduce lead optimization mapper, LOMAP, an automated algorithm to plan efficient relative free energy calculations between potential ligands within a substantial library of perhaps hundreds of compounds. In this approach, ligands are first grouped by structural similarity primarily based on the size of a (loosely defined) maximal common substructure, and then calculations are planned within and between sets of structurally related compounds. An emphasis is placed on ensuring that relative free energies can be obtained between any pair of compounds without combining the results of too many different relative free energy calculations (to avoid accumulation of error) and by providing some redundancy to allow for the possibility of error and consistency checking and provide some insight into when results can be expected to be unreliable. The algorithm is discussed in detail and a Python implementation, based on both Schrödinger’s and OpenEye’s APIs, has been made available freely under the BSD license.     

Multiobjective optimization of combinatorial libraries

Combinatorial chemistry and high-throughput screening have caused a fundamental shift in the way chemists contemplate experiments. Designing a combinatorial library is a controversial art that involves a heterogeneous mix of chemistry, mathematics, economics, experience, and intuition. Although there seems to be little agreement as to what constitutes an ideal library, one thing is certain: only one property or measure seldom defines the quality of the design. In most real-world applications, a good experiment requires the simultaneous optimization of several, often conflicting, design objectives, some of which may be vague and uncertain. In this paper, we discuss a class of algorithms for subset selection rooted in the principles of multiobjective optimization. Our approach is to employ an objective function that encodes all of the desired selection criteria, and then use a simulated annealing or evolutionary approach to identify the optimal (or a nearly optimal) subset from among the vast number of possibilities. Many design criteria can be accommodated, including diversity, similarity to known actives, predicted activity and/or selectivity determined by quantitative structure-activity relationship (QSAR) models or receptor binding models, enforcement of certain property distributions, reagent cost and availability, and many others. The method is robust, convergent, and extensible, offers the user full control over the relative significance of the various objectives in the final design, and permits the simultaneous selection of compounds from multiple libraries in full- or sparse-array format.     

Controlled-advancement rigid-body optimization of nanosystems

In this study, we propose a novel optimization algorithm, with application to the refinement of molecular complexes. Particularly, we consider optimization problem as the calculation of quasi-static trajectories of rigid bodies influenced by the inverse-inertia-weighted energy gradient and introduce the concept of advancement region that guarantees displacement of a molecule strictly within a relevant region of conformational space. The advancement region helps to avoid typical energy minimization pitfalls, thus, the algorithm is suitable to work with arbitrary energy functions and arbitrary types of molecular complexes without necessary tuning of its hyper-parameters. Our method, called controlled-advancement rigid-body optimization of nanosystems (Carbon), is particularly useful for the large-scale molecular refinement, as for example, the putative binding candidates obtained with protein–protein docking pipelines. Implementation of Carbon with user-friendly interface is available in the SAMSON platform for molecular modeling at https://www.samson-connect.net . © 2019 Wiley Periodicals, Inc.     

Computer optimization of separation in gas-solid chromatography,optimization model and computer-modified mapping procedure

Summary This paper proposes an optimization model for gas-solid chromatographic separations in a non-linear programming form and an approximate equation of the plate height for the model. A computer-modified mapping procedure is also described for searching the optimum separation conditions. Just five experiments and about 20 minutes of the computer time are needed to establish the optima of column temperature and of the carrier gas linear velocity. The relative deviation between the predicted and the experimental values was found to be within 20% for the plate heights, and within 1.5% for the retention times.     

Rotation in simplex optimization

A modification of the modified simplex method of optimization was tested. This modification involves rotation of the simplex when the standard simplex motion by reflection, expansion and contraction, fails to lead to continued progress of the simplex. Two other methods and several kinds of rotation are compared for four response surfaces. Certain rotations are shown to be superior to others and to two previously reported operations that do not involve rotation.     

Signal-to-noise optimization in polarimetry

The signal-to-noise ratio of a polarimeter is considered for cases which include flicker noise. It is found that using good quality polarizers is essential for detecting small rotations. A high-intensity light-source is also desirable, provided that the intensity can be stabilized. The predicted detectability of 2.8 × 10⁻⁷ degree with current instruments agrees with previously published experimental results.     

Bi-fidelity fitting and optimization

A common feature in computations of chemical and physical properties is the investigation of phenomena at different levels of computational accuracy. Less accurate computations are used to provide a relatively quick understanding of the behavior of a system and allow a researcher to focus on regions of initial conditions and parameter space where interesting phenomena are likely to occur. These inexpensive calculations are often discarded when more accurate calculations are performed. This paper demonstrates how computations at different levels of accuracy can be simultaneously incorporated to study chemical and physical phenomena with less overall computational effort than the most expensive level of computation. A smaller set of computationally expensive calculations is needed because the set of expensive calculations is correlated with the larger set of less expensive calculations. We present two applications. First, we demonstrate how potential energy surfaces can be fit by simultaneously using results from two different levels of accuracy in electronic structure calculations. In the second application, we study the optical response of metallic nanostructures. The optical response is generated with calculations at two different grid resolutions, and we demonstrate how using these two levels of computation in a correlated fashion can more efficiently optimize the response.     

Computer-selected optimization of activation analysis methods

The possibilities of using a computer to optimize the conditions of gamma-activation analysis are considered. Criteria of optimum conditions are formulated. The optimization program is constructed of the following operations being automatically performed: (1) determination of a list of isotopes and their gamma-lines formed during the interaction between the activating bremsstrahlung and the substance whose elemental composition elements to be analyzed plus matrix is preliminarily given; (2) optimization of the analysis time regimes and the value of the maximum energy of the activating bremsstrahlung; (3) choice of a gamma-line of the isotope of an element to be analyzed by which the quantitative determination of this element is expedient. For these purposes a catalogue of nuclear-physical constants (half-lives and energies which was compiled from published data tables of gamma-line outputs obtained experimentally under standardized conditions for different values of the maximum energy of the bremsstrahlung as well as mathematical models of the monoenergetic gamma-ray spectra) has been used.     

Performance optimization of k0-INAA

A spreadsheet application is developed for the prediction and optimization of the analytical performance of instrumental neutron activation analysis for matrices of more or less known composition. It assists in feasibility testing, sensivitity enhancement and cost reduction.     

Modeling and optimization of energy systems

Journal of Thermal Analysis and Calorimetry -     

Dynamic optimization of a gas-liquid reactor

A dynamic gas-liquid transfer model without chemical reaction based on unsteady film theory is considered. In this case, the mathematical model presented for gas-liquid mass-transfer processes is based on mass balances of the transferred substance in both phases. The identificability property of this model is studied in order to confirm the possible identifiable parameters of the model from a given set of experimental data. For that, a different modeled of the system is given. A procedure for the identification is proposed. On the other hand, the aim of this work is to solve the quadratic optimal control problem, using an explicit representation of the model. The problem includes some results on controllability, observability and stability criteria and the relation between these properties and the parameters of the model. Using the optimal control problem we study the stability of the system and show how the choice of the weighting matrices can improve the behavior of the system but with an increase of the energy control cost.