Abstract
Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his ...discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on another major challenge, the discovery of advanced materials against the exceedingly complex synthesis-processes-structure-property landscape. We demonstrate an autonomous materials discovery methodology for functional inorganic compounds which allow scientists to fail smarter, learn faster, and spend less resources in their studies, while simultaneously improving trust in scientific results and machine learning tools. This robot science enables science-over-the-network, reducing the economic impact of scientists being physically separated from their labs. The real-time closed-loop, autonomous system for materials exploration and optimization (CAMEO) is implemented at the synchrotron beamline to accelerate the interconnected tasks of phase mapping and property optimization, with each cycle taking seconds to minutes. We also demonstrate an embodiment of human-machine interaction, where human-in-the-loop is called to play a contributing role within each cycle. This work has resulted in the discovery of a novel epitaxial nanocomposite phase-change memory material.
In two-dimensional chiral metal-halide perovskites, chiral organic spacers endow structural and optical chirality to the metal-halide sublattice, enabling exquisite control of light, charge, and ...electron spin. The chiroptical properties of metal-halide perovskites have been measured by transmissive circular dichroism spectroscopy, which necessitates thin-film samples. Here, by developing a reflection-based approach, we characterize the intrinsic, circular polarization-dependent complex refractive index for a prototypical two-dimensional chiral lead-bromide perovskite and report large circular dichroism for single crystals. Comparison with ab initio theory reveals the large circular dichroism arises from the inorganic sublattice rather than the chiral ligand and is an excitonic phenomenon driven by electron-hole exchange interactions, which breaks the degeneracy of transitions between Rashba-Dresselhaus-split bands, resulting in a Cotton effect. Our study suggests that previous data for spin-coated films largely underestimate the optical chirality and provides quantitative insights into the intrinsic optical properties of chiral perovskites for chiroptical and spintronic applications.
Thin films of two types of high-entropy oxides (HEOs) have been deposited on 76.2 mm Si wafers using combinatorial sputter deposition. In one type of the oxides, (MgZnMnCoNi)O
, all the metals have a ...stable divalent oxidation state and similar cationic radii. In the second type of oxides, (CrFeMnCoNi)O
, the metals are more diverse in the atomic radius and valence state, and have good solubility in their sub-binary and ternary oxide systems. The resulting HEO thin films were characterized using several high-throughput analytical techniques. The microstructure, composition, and electrical conductivity obtained on defined grid maps were obtained for the first time across large compositional ranges. The crystalline structure of the films was observed as a function of the metallic elements in the composition spreads, that is, the Mn and Zn in (MgZnMnCoNi)O
and Mn and Ni in (CrFeMnCoNi)O
. The (MgZnMnCoNi)O
sample was observed to form two-phase structures, except single spinel structure was found in (MgZnMnCoNi)O
over a range of Mn > 12 at. % and Zn < 44 at. %, while (CrFeMnCoNi)O
was always observed to form two-phase structures. Composition-controlled crystalline structure is not only experimentally demonstrated but also supported by density function theory calculation.
Abstract
A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s ...synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.
Ni-Nb-Zr amorphous membranes, prepared by melt-spinning, show great potential for replacing crystalline Pd-based materials in the field of hydrogen purification to an ultrapure grade (>99.999%). In ...this study, we investigate the temperature evolution of the structure of an amorphous ribbon with the composition Ni32Nb28Zr30Cu10 (expressed in atom %) by means of XRD and DTA measurements. An abrupt structural expansion is induced between 240 and 300 °C by hydrogenation. This structural modification deeply modifies the hydrogen sorption properties of the membrane, which indeed shows a strong reduction of the hydrogen capacity above 270 °C.
Human placenta releases specific nanovesicles (i.e. exosomes) into the maternal circulation during pregnancy, however, the presence of placenta-derived exosomes in maternal blood during early ...pregnancy remains to be established. The aim of this study was to characterise gestational age related changes in the concentration of placenta-derived exosomes during the first trimester of pregnancy (i.e. from 6 to 12 weeks) in plasma from women with normal pregnancies.
A time-series experimental design was used to establish pregnancy-associated changes in maternal plasma exosome concentrations during the first trimester. A series of plasma were collected from normal healthy women (10 patients) at 6, 7, 8, 9, 10, 11 and 12 weeks of gestation (n = 70). We measured the stability of these vesicles by quantifying and observing their protein and miRNA contents after the freeze/thawing processes. Exosomes were isolated by differential and buoyant density centrifugation using a sucrose continuous gradient and characterised by their size distribution and morphology using the nanoparticles tracking analysis (NTA; Nanosight™) and electron microscopy (EM), respectively. The total number of exosomes and placenta-derived exosomes were determined by quantifying the immunoreactive exosomal marker, CD63 and a placenta-specific marker (Placental Alkaline Phosphatase PLAP).
These nanoparticles are extraordinarily stable. There is no significant decline in their yield with the freeze/thawing processes or change in their EM morphology. NTA identified the presence of 50-150 nm spherical vesicles in maternal plasma as early as 6 weeks of pregnancy. The number of exosomes in maternal circulation increased significantly (ANOVA, p = 0.002) with the progression of pregnancy (from 6 to 12 weeks). The concentration of placenta-derived exosomes in maternal plasma (i.e. PLAP+) increased progressively with gestational age, from 6 weeks 70.6 ± 5.7 pg/ml to 12 weeks 117.5 ± 13.4 pg/ml. Regression analysis showed that weeks is a factor that explains for >70% of the observed variation in plasma exosomal PLAP concentration while the total exosome number only explains 20%.
During normal healthy pregnancy, the number of exosomes present in the maternal plasma increased significantly with gestational age across the first trimester of pregnancy. This study is a baseline that provides an ideal starting point for developing early detection method for women who subsequently develop pregnancy complications, clinically detected during the second trimester. Early detection of women at risk of pregnancy complications would provide an opportunity to develop and evaluate appropriate intervention strategies to limit acute adverse sequel.
Although there is significant interest in elucidating the role of placenta-derived exosomes (PdEs) during pregnancy, the exosomal profile in pregnancies complicated by gestational diabetes mellitus ...(GDM) remains to be established. The aim of this study was to compare the gestational-age profile of PdEs in maternal plasma of GDM with normal pregnancies and to determine the effect of exosomes on cytokine release from human umbilical vein endothelial cells. A prospective cohort of patients was sampled at three time points during pregnancy for each patient (i.e., 11-14, 22-24, and 32-36 weeks' gestation). A retrospective stratified study design was used to quantify exosomes present in maternal plasma of normal (n = 13) and GDM (n = 7) pregnancies. Gestational age and pregnancy status were identified as significant factors contributing to variation in plasma exosome concentration (ANOVA, P < 0.05). Post hoc analyses established that PdE concentration increased during gestation in both normal and GDM pregnancies; however, the increase was significantly greater in GDM (∼2.2-fold, ∼1.5-fold, and ∼1.8-fold greater at each gestational age compared with normal pregnancies). Exosomes isolated from GDM pregnancies significantly increased the release of proinflammatory cytokines from endothelial cells. Although the role of exosomes during GDM remains to be fully elucidated, exosome profiles may be of diagnostic utility for screening asymptomatic populations.
Amorphous metallic membranes display promising properties for hydrogen purification up to an ultrapure grade (purity > 99.999%). The hydrogen permeability through amorphous membranes has been widely ...studied in the literature. In this work we focus on two additional properties, which should be considered before possible application of such materials: the propensity to crystallize at high temperatures should be avoided, as the crystallized membranes can become brittle; the hydrogen solubility should be high, as solubility and permeability are proportional. We investigate the crystallization process and the hydrogen solubility of some membranes based on Ni, Nb, and Zr metals, as a function of Zr content, and with the addition of Ta or B. The boron doping does not significantly affect the crystallization temperature and the thermal stability of the membrane. However, the hydrogen solubility for p ~7 bar is as high as H/M ~0.31 at T = 440 °C and H/M ~0.27 at T = 485 °C. Moreover, the membrane does not pulverize even after repeated thermal cycles and hydrogenation processes up to 485 °C and 7 bar, and it retains its initial shape.
We present an autonomous scanning droplet cell platform designed for on-demand alloy electrodeposition and real-time electrochemical characterization. Automation and machine learning are currently ...driving rapid innovation in high-throughput and autonomous materials design and discovery. We present two alloy design vignettes: one focusing on a multi-objective corrosion resistant alloy optimization and a study highlighting the complexity of the multimodal characterization needed to provide insight into the underlying structural and chemical factors that drive observed material behavior. This motivates a close coupling between autonomous research platforms and scientific machine learning methodology that blends mechanistic physical models and black box machine learning models. Finally, we reflect on our early efforts in on-demand alloy deposition, highlighting some of the challenges. This emerging research area presents new opportunities to accelerate materials synthesis, evaluation, and hence discovery and design.
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