Combinatorial Materials Science and Catalysis

In this paper, the slow evolution of combinatorial chemistry from its dawn in 1980’s to today’s oil field product development is discussed. Combinatorial chemistry comprises chemical synthetic methods that make it possible to prepare a vast number of compounds in a single process. These compound libraries can be made as mixtures, sets of individual compounds or chemical structures generated by computer software. This phenomenon was first invented by Arpad Furka (Lorand University, Budapest) in 1982. He described the principle of it, the combinatorial synthesis and a deconvolution procedure. The methodology was first used in drug discovery using a wide range of linear or wide range of macrocyclic chemical molecules: peptides, non-peptide oligomers, peptidomimetics, small-molecules, and natural product-like organic molecules. However, handling vast amounts of data and extremely small chemical recovery were a very difficult endeavor. To avoid this problem and help to refine the size of the chemical libraries, various software programs were utilized. This was achieved by utilizing a tool known as Design of Experiment (DoE). In this paper, the high throughput product screening to identify corrosion inhibitors was performed by utilizing critical micelle concentration (CMC). CMC was used to differentiate performance of libraries of chemical blends. Combinatorial synthesis (or blends) and combinatorial screening were performed by utilizing robotics methodologies. The corrosion inhibitor formulations predicted by DoE were built out by using combinatorial chemical methods and the arrays of chemical formulations were screened by utilizing high throughput robotics, using CMC as the selection guide. To validate the concept, several known corrosion inhibitor formulas were selected to optimize their efficacy. Each formula contained several active ingredients and a solvent package. These raw materials were blended in random but in a control, manner using combinatorial methodologies. After formulation of a vast array of formulation by using Design Expert solvent package. These raw materials were blended in random but in a control, manner using combinatorial methodologies. After formulation of a vast array of formulation by using Design Expert (DE) software, the products were screened for by CMC using automated surface tension workstation. Several formulations with lower CMC than the reference products were selected. The selected corrosion inhibitor formulations were identified and blended in larger scales. The efficacy of these products was tested by classical laboratory testing methods such as rotating cylinder electrode (RCE) and rotating cage autoclave (RCA) to determine their performance as anti-corrosion agents. These tests were performed against the original reference corrosion inhibitor. The testing indicated that several corrosion inhibitor formulations outperform the original blend thus validating the proof of concept.

Conventional ‘one by one’ synthesis approach has been a major rate limiting step in the systematic exploration of increasingly complex materials for the demanding new technologies. New concepts of ‘combinatorial chemistry’ are presented for the substantially efficient and cost-effective parallel synthesis and optimization of variety of multicomponent compounds as well as artificially designed lattices and devices. Effectiveness of variety of application areas developed by us is discussed with typical examples and brief review of the merits, challenges, current status and the future directions.

This paper briefly reviews the applications of materials science and engineering in the pharmaceutical industry. The materials characterization techniques highlighted in the paper as being utilized in the pharmaceutical industry are dynamic light scattering and photon correlation spectroscopy, mercury intrusion, gas density pycnometry and energy density analysis, thermogravimetric analysis and differential scanning calorimetry, x-ray diffraction, nuclear magnetic resonance and Raman microscopy. The other areas of applications of materials science and engineering in the pharmaceutical industry briefly discussed are materials processing, materials research and development, and materials selection. This paper further highlighted that the program as it is currently offered by various institutions in Nigeria is yet to incorporate the courses in pharmaceutical materials. It concluded by pointing out that some institutions outside Nigeria have incorporated pharmaceutical materials in the programs of materials science and engineering. Suggestions were made for the materials science and engineering programs in Nigeria to build further capacity for effective applications in the pharmaceutical industry. Keywords— Applications, materials engineering, pharmaceutical industry

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Poorly aqueous soluble active pharmaceutical ingredients are highly risky development candidates and remain a concern of pharmaceutical industries in drug discovery and development processes. Pharmaceutical industries are putting significant efforts into the target identification and lead candidate development using combinatorial chemistry. About 40% of compounds arising from combinatorial screening are poorly water soluble. Pharmaceutical industries evolved over this challenge by coming up with reproducible and scalable particle size reduction or by identifying alternate morphs. Another important area where pharmaceutical industries are working is solid dispersion technology. With the emergence of the hot-melt extrusion and spray drying approach, many molecules have been brought to the market using solid dispersion technology from the discovery phase by improving bioavailability and thereby efficacy. Although the solid solution technology in the last 60 years evolved from eutectic mixtures, solid dispersions using water-soluble polymers, and enteric polymers especially hydroxypropyl methylcellulose acetate succinate (HPMCAS), still there is no preformulation tool to identify correct polymer or polymer combination at the early stage of development. Thus, this leads to the urgent need to focus on the design and development of third-generation solid dispersions for the unmet needs of the industries and society.

The life cycle application of intelligent software modeling for the First Materials Science Research Rack

The effective utilization of clean energy and finding alternatives to fossil resources are highly important to ensure the sustainability of human society and are always among the major goals of both chemistry and material science research. Advanced electrochemical devices, such as fuel cells, water electrolysers and metal-air batteries, represent the most promising strategies for clean-energy utilization. In an electrochemical device, the redox reactions are spatially separated by a membrane, allowing direct extraction/transfer of electrons at an electrode-electrolyte interface, which leads to higher intrinsic energy conversion efficiencies, milder process conditions, easy product separation and excellent design features for coupling to renewable energy infrastructure. The performance of such electrochemical processes is fundamentally determined by the physicochemical properties of the electrochemical interfaces, encompassing both the electrocatalyst and the structure of the adjacent electrochemical double layer. Specifically, electrocatalysts play key roles in electrochemical reactions and often limit the performance of entire systems due to their insufficient activity, low durability or high cost. Ideally, the rate, efficiency, and selectivity of the above electrochemical reactions can be substantially improved by developing high-performance electrocatalyst. One of the central tasks for chemists and material scientists is to design and fabricate the high-efficient efficiency but low-cost electrocatalysts systems. The current promising electrochemical reactions mainly focus on the realization of the reversible conversion between chemical and electricity energy, e.g., the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen oxidation reaction (HOR), and hydrogen evolution reaction (HER). Coupling of the above electrochemical reactions provide a solid foundation for various essential electrochemical devices, such as direct hydrogen fuel cells (HOR + ORR); electrolysers (OER + HER); rechargeable zinc (Zn)-air battery (ORR + OER). Therefore, this thesis aims to design and synthesize high-performance electrocatalysts for HER, ORR and OER based on earth-abundant materials with proper hierarchical 2D or 3D nanostructures. Combined with the advanced characterization techniques and density functional theory (DFT) calculations, the relationship between the electrochemical activity and active sites of these earth-abundant electrocatalysts were detailedly explored and confirmed. Furthermore, to emphasize the hierarchical 2D or 3D nanostructures, the actual performance of these electrocatalysts was all evaluated in practical devices including Zn-air battery and proton exchange membrane fuel cell (PEMFC), specifically as follows: (1) The vast majority of the reported HER electrocatalysts performs poorly under alkaline conditions due to the sluggish water dissociation kinetics. In the first work, a hybridization catalyst construction concept is presented to dramatically enhance the alkaline HER activities of catalysts based on 2D transition metal dichalcogenides (TMDs) (MoS2 and WS2). A series of ultrathin 2D-hybrids are synthesized via facile controllable growth of 3d metal (Ni, Co, Fe, Mn) hydroxides on the monolayer 2D-TMD nanosheets. The resultant Ni(OH)2 and Co(OH)2 hybridized ultrathin MoS2 and WS2 nanosheet catalysts exhibit significantly enhanced alkaline HER activity and stability compared to their bare counterparts. The combined theoretical and experimental studies confirm that the formation of the heterostructured boundaries by suitable hybridization of the TMD and 3d metal hydroxides is responsible for the improved alkaline HER activities because of the enhanced water dissociation step and lowers the corresponding kinetic energy barrier by the hybridized 3d metal hydroxides. (2) Nitrogen-coordinated iron atoms on carbon matrix (Fe-N-C) materials are the most active Pt-group-metal-free ORR catalysts but still suffering their low stability and relatively lower activity compared to platinum-based materials. In the second work, Fe and Ni dual sites atomically dispersed in hierarchically ordered macroporous carbon support (Fe-Ni/N-HOMC) was designed and successfully prepared. Isolated atomic Fe- N4 and Ni-N4 active sites were confirmed via various characterizations. The ORR activity and stability of Fe-Ni/N-HOMC in both acid and alkaline electrolyte were much higher than commercial Pt/C and the mono-Fe doping counterpart, which was among the state-of-the-art ORR electrocatalysts. In addition, this 3D ordered interconnected macroporous structure with abundant mesopores and micropores could greatly increase the accessible ORR active site and also enhance the mass transport during the ORR process. When employed as cathodes for PEMFC, we found the excellent ORR activity of Fe-Ni/N-HOMC was completely translated to the cathode in the fuel cell. (3) High-performance bifunctional electrocatalysts with ORR and OER activity is the key to developing efficient rechargeable Zn-air batteries. In the third work, a high-performance bifunctional electrocatalysts for both OER and ORR were synthesized via further hybridizing as-prepared Fe-Ni/N-HOMC with NiFe layer double hydroxides (LDHs). Layered double hydroxides (LDHs) have been reported to be promising OER electrocatalysts with ultrahigh OER performances. The as-synthesized new composites exhibited almost the same ORR activity as Fe-Ni/N-HOMC, revealing that hybridization of NiFe-LDHs would not deteriorate the initial ORR activity. Moreover, the remarkable enhancement of OER activity was observed after the hybridization, which was attributed to the strong coupling of uniformly dispersed small NiFe-LDH nanoparticles with the carbon substrate. The prototype Zn-air battery was assembled using these new composites, which displayed the ultralow voltage gap and long-term stability. (4) Compared with Fe-N-C or Co-N-C based ORR electrocatalysts, the Cu-nitrogen-carbon composites were attracted little attention. However, the natural multicopper oxidases (MCOs) enzymes, such as laccase, can serve as efficient ORR catalyst with almost no overpotential. Inspired by their tris-copper centers in MCO, one novel Cu-nitrogen-carbon composite (Cu SAs/N-CS) with atomic Cu coordination sites were synthesized via the pyrolysis of the Cu-involved metal-organic-framework. The copper contents in Cu SAs/N-CS reaches as high as 3.17 wt.%, and the average distances of adjacent copper sites was around only 3.1 Å. Due to the synergetic effect of abundant single atomic copper active sites with closer distance and ultrathin carbon nanosheet structure, Cu SAs/N-CS exhibited superior ORR activity exceeding commercial Pt/C catalyst, methanol tolerance, and long-term stability in both alkaline and neutral electrolyte. In summary, four kinds of new composites were successfully designed and prepared as high-performance electrocatalysts for HER, ORR and OER. Multi-dimensional heterostructures, atomic metal coordination sites and 3D hierarchically porous structure were designed and observed, which contributed greatly to improve activities of these composites. This thesis suggests several new viewpoints in the design of electrocatalysts based on earth-abundant materials: (i) offering new strategies for the preparation of novel 2D and 3D heterostructures as electrocatalysts; (ii) expanding methods for the synthesis of atomic metal coordination sites and evaluating their activities for ORR; (iii) evaluating the practical performances of achieved electrocatalysts in proton exchange membrane fuel cell and Zn-air battery; (iv) attempting to explain reaction mechanisms of some electrocatalysts by DFT calculation.

Webster’s New Collegiate Dictionary defines promise as ‘... a right to expect or to claim the performance or forbearance of a specified act; ground for hope, expectation or assurance of eventual success ...’. Combinatorial chemistry has certainly generated very high expectations in the drug discovery community, but has the technique of combinatorial chemistry, and the practitioners of the technique, really delivered on that promise? The real promise of combinatorial chemistry should be defined in terms of a drug discovery and not a preclinical or, for that matter, a clinical candidate. Quite clearly, combinatorial methodology has yet to deliver on that promise, since no drugs have yet to emerge from clinical trials. However, for the purposes of this chapter, the editors of this series hope to document the continued advance of drug candidates generated by combinatorial methods through the clinic and, ultimately, to the market place. That is, the promise fulfilled. At this stage in the development of combinatorial methods, this chapter represents more of a place holder than a chapter of substance. In a sense, this chapter is as much an unfulfilled promise as the technique it reports upon, since there is really very little accessible clinical data to report. Therefore, we will outline the seemingly ever-expanding list of practicing combinatorial chemistry companies, report anecdotal information concerning pre-clinical discoveries and, most significantly, summarize the progress of those candidates actually in clinical development. In some respects the pre-clinical information would be very useful, but, not too surprisingly, this is very difficult information to document and to verify. Hopefully, in the not too distant future, there will be a detailed drug discovery story, with combinatorial chemistry as the centerpiece, which will appear in this chapter.KeywordsDrug DiscoveryStructural ClassCombinatorial MethodCombinatorial ChemistryLead StructureThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

5,6,7,8-Tetrahydroquinazolin-2-(thio)-ones (THQ) fits the class of N-heterocycles as a structural core in numerous bioactive compounds. They promptly extended previous decades. They were significantly recognized in combinatorial chemistry and materials science to determine the drug discovery, antioxidants, and pharmaceuticals fields. In the present work, one-pot multicomponent sustainable synthesis of THQ with easily accessible starting materials, i.e., cyclohexanone, different aromatic aldehydes and (thio)urea, has been performed to determine the proposed Biginelli mechanism that is supported by DFT. It is found that the THQs are synthesized by a mechano-chemical (grinding) tool to achieve a yield of 85.2% within 3.5 min, i.e., YE (% yield/time) 24.34 differs from the conventional method in which lower % yield (YE = 0.72) of THQ was achieved. This confirmed that in the green chemistry principle, the determination of % yield according to saving reaction time must be considered. Moreover, DFT-based antioxidant properties of the THQ were also studied in which the most potent antioxidant compounds were 7b > 6d > 2f. Softness (σ, eV−1) and hardness (η, eV mol−1) can approve the soft molecule that stays more reactive as a result of decreasing the energy gap along heterocyclic with values 0.1491 > 0.1300 > 0.1168 eV−1 one-to-one with the efficiency of antioxidant.

A promising avenue of research in materials science is to follow the strategies used by Mother Nature to fabricate ornate hierarchical structures as exemplified by organisms such as diatoms, sponges and magnetotactic bacteria. Some of the strategies used in the biological world to create functional inorganic materials may well have practical implications in the world of nanomaterials. The aim of our work is to examine the synthetic of magnetite nanoparticles under different conditions to show the influence in magnetic properties of magnetite nanoparticles. Magnetospirillum strain AMB-1 was used in this study in order to produce magnetite nanoparticles. Magnetite nanoparticles of average size~47 nm were obtained. The magnetic properties of magnetite nanoparticles under different incubation temperature were examined and a small influence in magnetic properties of magnetite nanoparticles was indicated.

A combinatorial approach to the optimization of metastable multicomponent hard coatings

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There has been an explosion of interest in combinatorial chemistry, where the combinatorial approach allows the simultaneous preparation of millions of new compounds in a relatively small confined volume followed by decoding of the active structures in this small volume.1 This aspect of combinatorial chemistry has led to a revolution in pharmaceutical industry and in material research, where it is suddenly possible to screen an incredible number of compounds in newly developed fast assays.2,3 The combinatorial principle does not only involve the chemistry, but also the biological and physical conditions under which the compounds are tested. These have to keep pace with the development of the new chemical methodology for combinatorial synthesis in order to be useful for the testing of the large arrays of compounds synthesised and to be used quickly and effectively.3 The analytical methods for structural analysis belong to another area, which has to develop in order to match the advances in synthesis.

In this article, we describe a process of the San Francisco collaboration to select optimal measures of linkage to care in response to the Enhanced Comprehensive HIV Prevention Planning program of the Centers for Disease Control and Prevention and to understand the implications of measure selection and the challenges of accessing data sources to measure outcomes along the HIV care continuum. Challenges identified are the variety of definitions of linkage to care and the nonintegrative nature of the multiple data systems necessary to measure linkage to care and other continuum outcomes. The choice of linkage measures, which at the extremes is a choice between higher-resolution measures based on clinical visit data in a subset of patients vs. a lower-resolution proxy measure based on surveillance data, has key implications. Choosing between the options needs to be informed by the primary use of the measure. For representing trends in the overall performance and response to interventions, more generalizable measures based on surveillance data are optimal. For identifying barriers to linkage to care for specific populations and potential intervention targets within the linkage process, higher-resolution measures of linkage that include clinical, laboratory, and social work visit information are optimal. Cataloging the different data systems along the continuum and observations of challenges of data sharing between the systems highlighted the promise of integrated data management systems that span HIV surveillance and care systems. Such integrated data management systems would have the ability to support detailed investigation and would provide simplified data to match newly developed, cross-agency Health and Human Service measures of HIV care continuum outcomes.

Yggdrasil is the largest ongoing project development on the Norwegian Continental Shelf. It includes three production platforms, nine subsea manifolds, and 38 subsea trees. This paper highlights three innovative approaches implemented in the project: the use of optimized subsea templates for lighter well stack-ups, the application of standardized equipment to accelerate project timelines, and the integration of a multidisciplinary data management system that covers the entire project scope. The focus is the project's commitment to standardization. This approach is enabling the team to deliver the megaproject efficiently, minimizing unnecessary engineering hours and maintaining a normal-sized execution team. The engineering team has demonstrated flexibility in meeting specific operator requirements without altering standard deliveries. In addition, standardization has made it possible to integrate newly discovered prospects within the existing project framework. The emphasis on equipment standardization has also enabled rapid execution of the megaproject without compromising quality or timelines. The second improvement centers on the use of an object-oriented data structure, seamlessly integrating a data management system with drawing software within a unified multidisciplinary work environment. This system facilitated the creation of smart piping and instrumentation diagrams, system control diagrams, and top-level assembly drawings while also integrating the master equipment list and project completion management into a single digital platform. This approach ensured coordination and consistency between disciplines and delivery lines. The integrated data management system has provided a unified digital environment, streamlining project execution. It manages complex engineering data and documentation across the entire project from downhole to topside facilities. The third innovative approach involves the use of subsea templates, enabling lighter well stack-ups. Prepared for dual drilling operations, these templates facilitate efficient dual tophole drilling. The application of new subsea templates for lighter well stack-ups and dual drilling in the Yggdrasil project has led to a more efficient drilling process, reducing overall time and costs. The Yggdrasil project showcases the successful integration of advanced drilling techniques, efficient standardization, and comprehensive data management within a single project framework. These contributions are significant in advancing the methodologies used in offshore drilling and project execution.