Circulating tumor cell clusters (CTC clusters) are present in the blood of patients with cancer but their contribution to metastasis is not well defined. Using mouse models with tagged mammary ...tumors, we demonstrate that CTC clusters arise from oligoclonal tumor cell groupings and not from intravascular aggregation events. Although rare in the circulation compared with single CTCs, CTC clusters have 23- to 50-fold increased metastatic potential. In patients with breast cancer, single-cell resolution RNA sequencing of CTC clusters and single CTCs, matched within individual blood samples, identifies the cell junction component plakoglobin as highly differentially expressed. In mouse models, knockdown of plakoglobin abrogates CTC cluster formation and suppresses lung metastases. In breast cancer patients, both abundance of CTC clusters and high tumor plakoglobin levels denote adverse outcomes. Thus, CTC clusters are derived from multicellular groupings of primary tumor cells held together through plakoglobin-dependent intercellular adhesion, and though rare, they greatly contribute to the metastatic spread of cancer.
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•CTC clusters originate as oligoclonal groups of cells from the primary tumor•CTC clusters exhibit increased metastatic propensity compared to single CTCs•Abundance of CTC clusters in patients denotes adverse outcome•Plakoglobin mediates CTC cluster formation, enhancing metastatic spread
Circulating tumor cell (CTC) clusters originating from oligoclonal primary tumor cells exhibit increased metastatic potential compared to single CTCs and indicate adverse outcome in cancer patients.
Sequential learning (SL) strategies,
i.e.
iteratively updating a machine learning model to guide experiments, have been proposed to significantly accelerate materials discovery and research. ...Applications on computational datasets and a handful of optimization experiments have demonstrated the promise of SL, motivating a quantitative evaluation of its ability to accelerate materials discovery, specifically in the case of physical experiments. The benchmarking effort in the present work quantifies the performance of SL algorithms with respect to a breadth of research goals: discovery of any "good" material, discovery of all "good" materials, and discovery of a model that accurately predicts the performance of new materials. To benchmark the effectiveness of different machine learning models against these goals, we use datasets in which the performance of all materials in the search space is known from high-throughput synthesis and electrochemistry experiments. Each dataset contains all pseudo-quaternary metal oxide combinations from a set of six elements (chemical space), the performance metric chosen is the electrocatalytic activity (overpotential) for the oxygen evolution reaction (OER). A diverse set of SL schemes is tested on four chemical spaces, each containing 2121 catalysts. The presented work suggests that research can be accelerated by up to a factor of 20 compared to random acquisition in specific scenarios. The results also show that certain choices of SL models are ill-suited for a given research goal resulting in substantial deceleration compared to random acquisition methods. The results provide quantitative guidance on how to tune an SL strategy for a given research goal and demonstrate the need for a new generation of materials-aware SL algorithms to further accelerate materials discovery.
Benchmarking metrics for materials discovery
via
sequential learning are presented, to assess the efficacy of existing algorithms and to be scientific in our assessment of accelerated science.
We report a new Ce-rich family of active oxygen evolution reaction (OER) catalysts composed of earth abundant elements, discovered using high-throughput methods. High resolution inkjet printing was ...used to produce 5456 discrete oxide compositions containing the elements nickel, iron, cobalt and cerium. The catalytic performance of each of these compositions was measured under conditions applicable to distributed solar fuels generation using a three-electrode scanning drop electrochemical cell. The catalytic activity and stability of representative compositions (Ni sub(0.5)Fe sub(0.3)Co sub(0.17)Ce sub(0.03)O sub(x) and Ni sub(0.3)Fe sub(0.07)Co sub(0.2)Ce sub(0.43)O sub(x)) from 2 distinct regions were verified by resynthesizing these compositions on glassy carbon rods for electrochemical testing. The activity of the new Ce-rich catalysts was further verified using an unrelated synthetic method to electrodeposit a pseudo-ternary composition Ni sub(0.2)Co sub(0.3)Ce sub(0.5)O sub(x), which produced a catalyst with 10 mA cm super(-2) oxygen evolution current at 310 mV overpotential. The unique Tafel behavior of these Ce-rich catalysts affords the opportunity for further improvement.
Smooth and compact thin films of amorphous and crystalline antimony sulfide (Sb
2S
3) were prepared by radio frequency sputtering of an Sb
2S
3 target. As-deposited films are amorphous. ...Polycrystalline antimony sulfide films composed of ∼
500 nm grains are obtained by annealing the as-deposited films at 400 °C in sulfur vapors. Both amorphous and crystalline antimony sulfide have strong absorption coefficients of 1.8
×
10
5 cm
−
1
at 450 nm and 7.5
×
10
4 cm
−
1
at 550 nm, and have direct bandgaps with band energies of 2.24 eV and 1.73 eV, respectively. These results suggest the potential use of both amorphous and crystalline antimony sulfide films in various solid state devices.
Ce‐rich mixed metal oxides comprise a recently discovered class of electrocatalysts for the oxygen evolution reaction (OER). In particular, at current densities below 10 mA cm−2, ...Ni0.3Fe0.07Co0.2Ce0.43Ox exhibits superior activity compared to the corresponding transition metal oxides, despite the relative inactivity of ceria. To elucidate the enhanced activity and underlying catalytic mechanism, detailed structural characterization of this quinary oxide electrocatalyst is reported. Transmission electron microscopy imaging of cross‐section films as‐prepared and after electrochemical testing reveals a stable two‐phase nanostructure composed of 3–5 nm diameter crystallites of fluorite CeO2 intimately mixed with 3–5 nm crystallites of transition metal oxides alloyed in the rock salt NiO structure. Dosing experiments demonstrate that an electron flux greater than ≈1000 e Å−2 s−1 causes the inherently crystalline material to become amorphous. A very low dose rate of 130 e Å−2 s−1 is employed for atomic resolution imaging using inline holography techniques to reveal a nanostructure in which the transition metal oxide nanocrystals form atomically sharp boundaries with the ceria nanocrystals, and these results are corroborated with extensive synchrotron X‐ray absorption spectroscopy measurements. Ceria is a well‐studied cocatalyst for other heterogeneous and electrochemical reactions, and our discovery introduces biphasic cocatalysis as a design concept for improved OER electrocatalysts.
The unique electrochemical behavior of the Ni0.3Fe0.07Co0.2Ce0.43Oxoxygen evolution electrocatalyst motivates detailed structural characterization to elucidate the underlying catalytic mechanism. Atomic resolution transmission electron microscopy imaging using inline holography techniques reveals a nanostructure in which transition metal oxide alloys form atomically sharp boundaries with ceria nanocrystals. Synchrotron X‐ray absorption spectroscopy measurements confirm this unprecedented observation of a multiphase, nanostructured oxygen evolution electrocatalyst.
The quest to identify materials with tailored properties is increasingly expanding into high-order composition spaces, with a corresponding combinatorial explosion in the number of candidate ...materials. A key challenge is to discover regions in composition space where materials have novel properties. Traditional predictive models for material properties are not accurate enough to guide the search. Herein, we use high-throughput measurements of optical properties to identify novel regions in three-cation metal oxide composition spaces by identifying compositions whose optical trends cannot be explained by simple phase mixtures. We screen 376,752 distinct compositions from 108 three-cation oxide systems based on the cation elements Mg, Fe, Co, Ni, Cu, Y, In, Sn, Ce, and Ta. Data models for candidate phase diagrams and three-cation compositions with emergent optical properties guide the discovery of materials with complex phase-dependent properties, as demonstrated by the discovery of a Co-Ta-Sn substitutional alloy oxide with tunable transparency, catalytic activity, and stability in strong acid electrolytes. These results required close coupling of data validation to experiment design to generate a reliable end-to-end high-throughput workflow for accelerating scientific discovery.
The oxygen evolution reaction (OER) is a critical component of industrial processes such as electrowinning of metals and the chlor-alkali process. It also plays a central role in the development of a ...renewable energy field for generation a solar fuels by providing both the protons and electrons needed to generate fuels such as H2 or reduced hydrocarbons from CO2. To improve these processes, it is necessary to expand the fundamental understanding of catalytically active species at low overpotential, which will further the development of electrocatalysts with high activity and durability. In this context, performing experimental investigations of the electrocatalysts under realistic working regimes (i.e., under operando conditions) is of crucial importance. Here, we study a highly active quinary transition-metal-oxide-based OER electrocatalyst by means of operando ambient-pressure X-ray photoelectron spectroscopy and X-ray absorption spectroscopy performed at the solid/liquid interface. We observe that the catalyst undergoes a clear chemical-structural evolution as a function of the applied potential with Ni, Fe, and Co oxyhydroxides comprising the active catalytic species. While CeO2 is redox inactive under catalytic conditions, its influence on the redox processes of the transition metals boosts the catalytic activity at low overpotentials, introducing an important design principle for the optimization of electrocatalysts and tailoring of high-performance materials.
The oxygen evolution reaction (OER) is central to several sustainable energy technologies. Catalyst development has largely focused on lowering the overpotential and eliminating reliance on precious ...metals, revealing stark differences in alkaline and acidic OER. In alkaline electrolyte, precious metal-free catalysts have approached the limiting overpotential from established free energy scaling relationships, and our survey of complex metal oxides shows that this limit can be approached with a broad range of catalysts. In acidic electrolyte, electrochemical instabilities create a dual challenge of a dearth of nonprecious metal OER catalysts with overpotential below 0.5 V and a high dissolved metals concentration for most precious metal-free catalysts. On device-relevant time scales, the high dissolved metals concentrations compromise device stability, for example, through a decrease of performance and due to metal exchange between anode and cathode catalysts due to finite permeability of ion exchange membranes. These considerations motivate a substantial increase in monitoring and reporting of dissolved metals concentrations in OER experiments. To facilitate durability-based screening in continued catalyst discovery campaigns, we introduce a durability descriptor based on the d-electron count of each metal element compared to that of its Pourbaix-stable oxidation state, which enables rapid down-selection of candidate metal oxide catalysts. We discuss the importance of a codesign approach to catalyst development, where a device architecture can set specific requirements for dissolved metals concentrations and/or cathode and anode catalysts can be designed to tolerate cross-contamination. This device-level guidance of basic science will facilitate deployment of new catalysts to meet the societal needs for accelerated sustainable technology development.
Solar photoelectrochemical generation of fuel is a promising energy technology yet the lack of an efficient, robust photoanode remains a primary materials challenge in the development and deployment ...of solar fuels generators. Metal oxides comprise the most promising class of photoanode materials, but no known material meets the demanding requirements of low band gap energy, photoelectrocatalysis of the oxygen evolution reaction (OER), and stability under highly oxidizing conditions. Here, the identification of new photoelectroactive materials is reported through a strategic combination of combinatorial materials synthesis, high‐throughput photoelectrochemistry, optical spectroscopy, and detailed electronic structure calculations. Four photoelectrocatalyst phases, α‐Cu2V2O7, β‐Cu2V2O7,γ‐Cu3V2O8, and Cu11V6O26, are reported with band gap energy at or below 2 eV. The photoelectrochemical properties and 30 min stability of these copper vanadate phases are demonstrated in three different aqueous electrolytes (pH 7, pH 9, and pH 13), with select combinations of phase and electrolyte exhibiting unprecedented photoelectrocatalytic stability for metal oxides with sub‐2 eV band gap. Through integration of experimental and theoretical techniques, new structure‐property relationships are determined and establish CuO–V2O5 as the most prominent composition system for OER photoelectrocatalysts, providing crucial information for materials genomes initiatives and paving the way for continued development of solar fuels photoanodes.
Through integration of high throughput experimental and theoretical techniques, CuO‐V2O5 is established as the most prominent composition system for oxygen evolution reaction photoelectrocatalysts. Four photoelectrocatalyst phases are discovered and structure–property relationships are developed using a strategic combination of combinatorial synthesis, high throughput screening, and detailed electronic structure calculations.
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