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Materials with crystal structures containing tetrahedral motifs are preferable for optoelectronic applications because they often have direct band gaps and low electron effective masses. However, crystal structures of manganese chalcogenides typically contain octahedral motifs, such as in rock salt (RS) MnS and MnSe materials. Here, we experimentally show that MnS1−xSex alloys with tetrahedrally bonded wurtzite (WZ) structure can form between MnSe and MnS parent compounds with octahedral RS structures, at S-rich compositions (x < 0.4) and low synthesis temperatures (∼300 °C). The calculated mixing enthalpies of MnS1−xSex alloys in RS and WZ structures cannot explain this experimental observation, so we hypothesize that WZ stabilization may be related to smaller structure density and lower surface energy compared with RS. The resulting WZ MnS1−xSex alloys have 3.0–3.2 eV optical absorption onset and lower electrical conductivity (<0.0001 S/cm) than the parent RS compounds. These experimental measurement results are consistent with computationally predicted band gaps and effective masses.
Machine learning (ML) and artificial intelligence (AI) are quickly becoming commonplace in materials research. In addition to the standard workflow of fitting a model to a large set of data in order to make predictions, the materials community is finding novel and meaningful ways to integrate AI within their work. This has led to an acceleration not only of materials design and discovery, but also of other aspects of materials research as well, including faster computational models, the development of autonomous and intelligent “robot researchers,” and the automatic discovery of physical models. In this issue, we highlight a few of these applications and argue that AI/ML is delivering real-world, practical solutions to materials problems. It is also clear that we need AI/ML methods and models, “dialects” that are better adapted to materials research.
In this study, a three-phased multiwalled scaffold, composed of carbon nanotube (mwCNT), nanocrystalline hydroxyapatite (nHA), and polycaprolactone (PCL), was fabricated by the solvent evaporation technique. The structure character, mechanical properties, and degradation activity in simulated body fluid (SBF), along with osteoproductive ability in human osteosarcoma cell MG63, were investigated thoroughly. Results showed that the three phases in mwCNT/nHA/PCL composite presented excellent miscibility and stronger interfacial force when the weight content was 1/15/84 (wt%). Simultaneously, the composite had smaller porosity and slower degradation rate, and there was massive crystallized hydroxyapatite formed on the surface after being soaked in SBF. With regard to bioactivity, MG63s on this scaffolds presented good proliferation performance and differentiated into the osteogenic lineage by expressing high levels of ALP. It was concluded that mwCNTs/nHA/PCL composite scaffolds might be beneficial for bone tissue engineering at a relatively low concentration of mwCNTs and nHA.
Ongoing, rapid innovations in fields ranging from microelectronics, aerospace, and automotive to defense, energy, and health demand new advanced materials at even greater rates and lower costs. Traditional materials R&D methods offer few paths to achieve both outcomes simultaneously. Materials informatics, while a nascent field, offers such a promise through screening, growing databases of materials for new applications, learning new relationships from existing data resources, and building fast predictive models. We highlight key materials informatics successes from the atomic-scale modeling community, and discuss the ecosystem of open data, software, services, and infrastructure that have led to broad adoption of materials informatics approaches. We then examine emerging opportunities for informatics in materials science and describe an ideal data ecosystem capable of supporting similar widespread adoption of materials informatics, which we believe will enable the faster design of materials.
High-entropy alloys (HEAs) with multiple principal elements open up a practically infinite space for designing novel materials. Probing this huge material universe requires the use of combinatorial and high-throughput synthesis and processing methods. Here, we present and discuss four different combinatorial experimental methods that have been used to accelerate the development of novel HEAs, namely, rapid alloy prototyping, diffusion-multiples, laser additive manufacturing, and combinatorial co-deposition of thin-film materials libraries. While the first three approaches are bulk methods which allow for downstream processing and microstructure adaptation, the latter technique is a thin-film method capable of efficiently synthesizing wider ranges of composition and using high-throughput measurement techniques to characterize their structure and properties. Additional coupling of these high-throughput experimental methodologies with theoretical guidance regarding specific target features such as phase (meta)stability allows for effective screening of novel HEAs with beneficial property profiles.
An as-deposited film with a Cr compositional gradient (22–15 at.% Cr) was immersed in 22.5% HNO3 for 15 hours. In the part of the film with initial Cr content in the range of 22–18 at.%, Cu dealloying resulted in sufficient Cu dealloying (final Cr content = 33–80 at.%) without film dissolution. Using the film with optimal initial composition Cu82Cr18, we successfully fabricated a nanoporous film with a pore size in the range of 20–40 nm. As a result of the formation of Cr2O3 during dealloying, this film was transparent and exhibited an insulation state. The novel nanoporous film is expected to be applied as a nanofilter in moisture-in-oil sensors.
Robot assisted synthesis as part of high-throughput (HT) technology can assist in the creation of polymer libraries, e.g. polymers with a variety of molecular weights, by automatizing similar reactions. Especially for multiblock copolymers like polyurethanes (PUs) synthesized from telechels via polyaddition reaction, the adjustment of equivalent molar amounts of reactants requires a comprehensive investigation of end group functionality.
In this work, PUs based on oligo(ε-caprolactone) (OCL) / oligotetrahydrofuran (OTHF) as model components were designed utilizing HT synthesis enabling the quantitative determination of the optimized ratio between reactive end-groups via fully automated syntheses without major characterization effort of end group functionality. The semi-crystalline oligomeric telechelics were connected with a diisocyanate and OCL with a molecular weight of 2, 4, or 8 kg∙mol-1 was integrated. Here, optimized molecular weights between 90 ± 10 kg∙mol-1 (in case of OCL 8 kg∙mol-1) and 260 ± 30 kg∙mol-1 (in case of OCL 2 kg∙mol-1) were obtained with an isocyanate content of 120 mol%, whereby 100 mol% of isocyanate groups resulted only in molecular weights between 60 ± 6 kg∙mol-1 (OCL 8 kg∙mol-1) and 80 ± 10 kg∙mol-1 (OCL 2 kg∙mol-1). In addition to the optimized ratio between isocyanate and hydroxy end groups, quantitative influences of the OCL chain length and overall molecular weights of PUs on thermal and mechanical properties were detected. The melting temperatures (Tms) of OCL and OTHF domains were well separated for PUs of low molecular weight, the temperature interval between the Tms decreased when the molecular weight of the PUs was increased, and were even overlapping towards one broad Tm, when OCL 2 kg∙mol-1 was incorporated. The storage modulus E’ was highly dependent on OCL chain length exhibiting an increase with increasing molecular weight of OCL from 220 MPa to 440 MPa at 0 °C and decreased with increasing chain length of PUs. The elongation at break (εb) was analyzed below and above Tm of OTHF resulting in εb = 780-870% at 0 °C and εb = 510-830% at 30 °C for PUs of high molecular weight. Accordingly, stretchability of PUs was almost independent of the state of OTHF (semi crystalline or amorphous) but correlated with the OCL precursor chain length (increasing εb with increasing chain length) and overall molecular weight of PUs (PUs at higher molecular weight exhibited higher εb). Hence, the analysis of these quantitative influences between macromolecular structure of multiblock copolymers and the resulting properties (well separated Tms versus overlapping melting transition, improvement of stretchability) would enable the design of new tailored PUs.
The Materials Genome Initiative (MGI) calls for the acceleration of the materials development cycle through the integration of experiments and simulations within a data-aware/enabling framework. To realize this vision, MGI recognizes the need for the creation of a new kind of workforce capable of creating and/or deploying advanced informatics tools and methods into the materials discovery/development cycle. An interdisciplinary team at Texas A&M seeks to address this challenge by creating an interdisciplinary program that goes beyond MGI in that it incorporates the discipline of engineering systems design as an essential component of the new accelerated materials development paradigm. The Data-Enabled Discovery and Development of Energy Materials (D3EM) program seeks to create an interdisciplinary graduate program at the intersection of materials science, informatics, and design. In this paper, we describe the rationale for the creation of such a program, present the pedagogical model that forms the basis of the program, and describe some of the major elements of the program.
We have investigated plant growth response to atmospheric air plasma treatments of seeds on their growth for 5 plant speces; Radish sprout (Raphanus sativus L.), rice (Oryza Sativa), Zinnia, Arabidopsis L. Thaliana and Plumeri. The average length of Radish sprout, rice, Arabidopsis Thaliana, Plumeria and Zinnia, are 250%, 80%, 60%, 30% and 20% longer than those without plasma treatments, respectively. We have obtained correlation between the growth enhancement and O3 and NOx concentration. The optimum radical dose for the growth enhancement depends on plant species.
Depsipeptide-based multiblock copolymers synthesized from dihydroxy telechelic oligodepsipeptide precursors are promising candidate materials for biomedical and pharmaceutical applications. High molecular weight polymers in polyaddition reactions e.g. of diols with diisocyanates can only be reached when reactive groups are equivalent and a high conversion for this step growth polymerization is obtained. However, in depsipeptide-based multiblock urethanes reported so far, the stoichiometric ratio of the diisocyanate compound exceeded the theoretical value of 100% by far. In order to investigate the influence of the dosing system in this unusual behavior of the stoichiometric reaction two dosing devices, a solid dosing unit (SDU) and a gravimetric dosing unit (GDU) were used for a gravimetric transfer of an oligo(3-sec-butylmorpholine-2.5-dione) (OBMD) as model oligodepsipeptide. The OBMD precursor, which was transferred as a solid or as a highly viscous solution, was reacted with an isomeric mixture of 2,2,4- and 2,4,4-trimethylhexamethylene diisocyanate (TMDI) as chain extender. Two series of 49 reactions were performed and the chain extension efficacy of the building block was compared between the SDU and GDU as well as with respect to the Carothers equation. When the GDU was used the chain extension yielded higher molecular weights, proving the high accuracy of the dosing device, and the molar ratio of TMDI required for the high-throughput synthesis of the depsipeptide-based multiblock copolymers was similar to depsipeptide-based multiblock copolymers created in a classical synthesis approach.
We established a Ca1-xBixMn1-yNiyO3 (0 ≤ x, y ≤ 0.1) powder library using a combinatorial system based on the electrostatic spray deposition method. Single phase perovskite-type structures were identified in all of the powders. To measure electrical conductivity, the powder library was subjected to high-pressure (200 MPa) and heat-treated at 950°C for 1 hour in an oxygen atmosphere. As a representative example, the electrical conductivity of 5%-Bi-substituted CaMnO3-δ showed a higher value (63 S·cm-1) than an unsubstituted powder (13 S·cm-1). The improved electrical conductivity, on the other hand, was still very far from the ideal result (167 S·cm-1).
The complete ternary system Co-Al-W was fabricated as a thin film materials library by combinatorial magnetron sputtering. The materials library was investigated using high-throughput characterization methods such as optical measurements as well as automated resistance screening. The obtained data indicate possible phase regions and compositional regions which show early surface oxidation. The demonstrated approach illustrates that using high-throughput measurement methods provides a fast access to data of relatively unexplored materials systems. The gained data provides a valuable basis for further in-depth studies of the investigated materials systems.
Many solar fuel generator designs involve illumination of a photoabsorber stack coated with a catalyst for the oxygen evolution reaction (OER). In this design, impinging light must pass through the catalyst layer before reaching the photoabsorber(s), and thus optical transmission is an important function of the OER catalyst layer. Many oxide catalysts, such as those containing elements Ni and Co, form oxide or oxyhydroxide phases in alkaline solution at operational potentials that differ from the phases observed in ambient conditions. To characterize the transparency of such catalysts during OER operation, 1031 unique compositions containing the elements Ni, Co, Ce, La, and Fe were prepared by a high throughput inkjet printing technique. The catalytic current of each composition was recorded at an OER overpotential of 0.33 V with simultaneous measurement of the spectral transmission. By combining the optical and catalytic properties, the combined catalyst efficiency was calculated to identify the optimal catalysts for solar fuel applications within the material library. The measurements required development of a new high throughput instrument with integrated electrochemistry and spectroscopy measurements, which enables various spectroelectrochemistry experiments.
The goal of the work reported in this paper is to use automated, combinatorial synthesis to generate alternative solutions to be used as stimuli by designers for ideation. FuncSION, a computational synthesis tool that can automatically synthesize solution concepts for mechanical devices by combining building blocks from a library, is used for this purpose. The objectives of FuncSION are to help generate a variety of functional requirements for a given problem and a variety of concepts to fulfill these functions. A distinctive feature of FuncSION is its focus on automated generation of spatial configurations, an aspect rarely addressed by other computational synthesis programs. This paper provides an overview of FuncSION in terms of representation of design problems, representation of building blocks, and rules with which building blocks are combined to generate concepts at three levels of abstraction: topological, spatial, and physical. The paper then provides a detailed account of evaluating FuncSION for its effectiveness in providing stimuli for enhanced ideation.
We analyze photoluminescence (PL) and electroluminescence (EL) using a hyperspectral imager that records spectrally resolved luminescence images of solar cell absorbers. The system is calibrated to yield the luminescence flux in absolute values. This system enables to quantitatively image physical parameters such as the photovoltage with an uncertainty of less than 30mV. The wide field illumination, low power excitation and fast acquisition brings new insights compare to classical setups such as confocal microscope. Several types of absorbers have been analyzed. For instance, we can investigate spatial fluctuations of the Quasi Fermi Levels splitting in CIGS polycristalline absorbers and link those fluctuations to transport properties. The method is general to the point that third generation PV cells absorbers can also be evaluated. We illustrate the great potential of our setup by imaging quasi Fermi levels splitting in Intermediate Band Solar cells. Such techniques, directly evaluating the performance of photovoltaic absorbers and devices are needed for fast, high throughput investigations of combinatorial experiments such as the projects carried out for the material genomics programme.
The High Throughput Experimentation (HTE) project of the Joint Center for Artificial Photosynthesis (JCAP, http://solarfuelshub.org/) performs accelerated discovery of new earth-abundant photoabsorbers and electrocatalysts. Through collaboration within the DOE solar fuels hub and with the broader research community, the new materials will be utilized in devices that efficiently convert solar energy, water and carbon dioxide into transportation fuels. JCAP-HTE builds high-throughput pipelines for the synthesis, screening and characterization of photoelectrochemical materials. In addition to a summary of these pipelines, we will describe several new screening instruments for high throughput (photo-)electrochemical measurements. These instruments are not only optimized for screening against solar fuels requirements, but also provide new tools for the broader combinatorial materials science community. We will also describe the high throughput discovery, follow-on verification, and device implementation of a new quaternary metal oxide catalyst. This rapid technology development from discovery to device implementation is a hallmark of the multi-faceted JCAP research effort.
Watson and Crick’s discovery of the structure of DNA in 1953 and the near-simultaneous advent of the first silicon transistor in 1954 spurred parallel historic advances over the following decades in molecular biology and materials technology. As these two expansive fields of research have progressed, important areas of overlap have included the extensive use of materials innovations in biological research, such as in microscopy and measurement systems, while materials research has benefited from efforts to mimic design principles utilized in nature. Until relatively recently, however, the molecular mechanisms that underpin nature’s biological orchestra have remained largely outside the purview of materials research. Now, with new abilities to harness and modify biomolecular and cellular systems, evidence is mounting that biology can be fruitfully utilized to directly engineer technological materials. This article aims to highlight the importance of DNA-driven routes to new materials while providing a brief overview of the genetic engineering platforms that make these routes possible. Emphasis is placed on the fact that it is now possible to genetically evolve materials technologies in a manner that mimics the genetic evolution of biominerals in nature.
Combinatorial sputtering is one of the useful methods that can be used to search for optimal composition of alloy materials or for new alloy materials. To search materials more efficiently, it is required that compositions and their distribution on samples can be easily controlled for the evaluation of their properties. Moreover, it is desirable that compositions change linearly to search for novel materials systematically. In conventional combinatorial sputtering method, it is difficult to fabricate samples having linear compositions distribution without moving hard masks or rotating substrate.
In this paper, a novel combinatorial sputtering method with New Facing Targets Sputtering (Combi-NFTS) of material search is introduced. In this method, several sputtering targets are placed in opposite direction, and substrates are placed in vertical direction of these targets. From this structure, thin film with binary/ternary composition distribution could be synthesized onto one single substrate. Moreover, it can fabricate samples having relatively linear composition distribution without moving hard masks or rotating substrate. As an example, Cu, Zr and Ti pure targets were used to confirm the performance of Combi-NFTS. Binary system of Cu-Zr and ternary system of Cu-Zr-Ti thin films were fabricated by using Combi-NFTS. After deposition, compositions of the films were characterized by the energy dispersive X-ray spectroscopy. As a result of Cu-Zr binary system, the composition of the thin film was changed as the power of targets was changed. Moreover, composition distribution was expanded as the distance from substrate to targets was decreased. In the Cu-Zr-Ti ternary system, it was obtained similar trend for composition distribution. Moreover, the composition changed two dimensional by changing the substrate position.
These results indicate that combi-NFTS can easily control the composition and composition distribution of thin films by changing the power of targets or the distance from substrate to targets which make combi-NFTS very suitable for combinatorial materials search.
We discuss our current research focus on photovoltaic (PV) informatics, which is dedicated to functionality enhancement of solar materials through data management and data mining-aided, integrated computational materials engineering (ICME) for rapid screening and identification of multi-scale processing/structure/property/performance relationships. Our current PV informatics research ranges from transparent conducting oxides (TCO) to solar absorber materials. As a test bed, we report on examples of our current data management system for PV research and advanced data mining to improve the performance of solar cells such as CuInxGa1-xSe2 (CIGS) aiming at low-cost and high-rate processes. For the PV data management, we show recent developments of a strategy for data modeling, collection and aggregation methods, and construction of data interfaces, which enable proper archiving and data handling for data mining. For scientific data mining, the value of high-dimensional visualizations and non-linear dimensionality reduction is demonstrated to quantitatively assess how process conditions or properties are interconnected in the context of the development of Al-doped ZnO (AZO) thin films as the TCO layers for CIGS devices. Such relationships between processing and property of TCOs lead to optimal process design toward enhanced performance of CIGS cells/devices.