R-3 Repository :: Browsing by Author "Tang, Ming"

Browsing by Author "Tang, Ming"

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A Machine Learning-Based Approach for Materials Microstructure Analysis and Prediction
(2020-04-24) Yang, Xiting; Tang, Ming
As the amount of data generated by experimental and computational works in the field of material science has exploded in the past decade, there is a pressing need for the development of advanced data analytics methods to address the “curse” of data overabundance. In this context, machine learning techniques have been increasingly employed in materials research in recent years. In this work, we explore several applications of generative adversarial networks (GAN), a class of emerging machine learning frameworks, to the digital synthesis and enhancement of material microstructure and the accelerated prediction of microstructure evolution. Using physics-based phase-field simulations to provide training data, the deep convolutational GAN (DCGAN) method is employed to generate realistic-looking microstructures resulting from three distinct physical processes: grain growth, spinodal decomposition and dendrite growth during solidification. In the second application, we apply the super-resolution GAN (SRGAN) method to upsample low-resolution microstructure images to restore the structural details. A multi-level SRGAN scheme is developed to enable an upscaling factor of 16x with acceptable tolerance, which significantly reduces the data sampling need for both experiments and computational modeling. Finally, combining recurrent neural networks (RNN) with DCGAN and SRGAN, we demonstrate a hybrid machine learning model for predicting microstructure evolution. Trained by physics-based simulations, the hybrid model is capable of making reliable predictions at only a small fraction of computational cost by representing the microstructure on coarse mesh grids and increasing the time step size. Our work showcases the significant promise of GAN-related machine learning techniques for materials microstructure analysis and prediction to accelerate materials design and discovery.
A mechanism of defect-enhanced phase transformation kinetics in lithium iron phosphate olivine
(Springer Nature, 2019) Hong, Liang; Yang, Kaiqi; Tang, Ming
Antisite defects are a type of point defect ubiquitously present in intercalation compounds for energy storage applications. While they are often considered a deleterious feature, here we elucidate a mechanism of antisite defects enhancing lithium intercalation kinetics in LiFePO4 by accelerating the FePO4 → LiFePO4 phase transformation. Although FeLi antisites block Li movement along the [010] migration channels in LiFePO4, phase-field modeling reveals that their ability to enhance Li diffusion in other directions significantly increases the active surface area for Li intercalation in the surface-reaction-limited kinetic regime, which results in order-of-magnitude improvement in the phase transformation rate compared to defect-free particles. Antisite defects also promote a more uniform reaction flux on (010) surface and prevent the formation of current hotspots under galvanostatic (dis)charging conditions. We analyze the scaling relation between the phase boundary speed, Li diffusivity and particle dimensions and derive the criteria for the co-optimization of defect content and particle geometry. A surprising prediction is that (100)-oriented LiFePO4 plates could potentially deliver better performance than (010)-oriented plates when the Li intercalation process is surface-reaction-limited. Our work suggests tailoring antisite defects as a general strategy to improve the rate performance of phase-changing battery compounds with strong diffusion anisotropy.
A Mechanistic Study of Mossy Electroplating Structure In Zinc And Lithium Metal Electrodes
(2023-12-01) Savsatli, Yavuz; Tang, Ming
This research offers an in-depth exploration of the formation of mossy structures in the electrochemical deposition of zinc and lithium, a phenomenon with significant implications for energy storage technologies. Utilizing nano-tomography, we present groundbreaking visualizations of mossy zinc growth and dissolution. This novel approach brings fresh perspectives to metal deposition mechanisms and electrolyte interactions, extending our understanding to include other metals like sodium. Stress dynamics during the electrodeposition process are elucidated using Multi Optical Beam Stress Sensing (MOSS). Our findings demonstrate that plating stress, influenced by the type of electrolyte, plays a pivotal role in the formation of morphological instabilities. Through this, the research sheds light on the relationship between stress and morphology, contributing valuable insights into the engineering of next-generation rechargeable batteries. Furthermore, the research delves into the morphological behaviors of lithium anode under varying experimental conditions—such as current density, seed layers, and formation cycles. The study not only highlights the adaptability of these metals but also outlines strategies to optimize their morphology, thereby enhancing Coulombic efficiency. Collectively, this research fills critical gaps in the field of metal electrodeposition, offering innovative insights that have broad relevance in material science and the burgeoning field of energy storage solutions.
Accelerate microstructure evolution simulation using graph neural networks with adaptive spatiotemporal resolution
(IOP Publishing, 2024) Fan, Shaoxun; Hitt, Andrew L.; Tang, Ming; Sadigh, Babak; Zhou, Fei
Surrogate models driven by sizeable datasets and scientific machine-learning methods have emerged as an attractive microstructure simulation tool with the potential to deliver predictive microstructure evolution dynamics with huge savings in computational costs. Taking 2D and 3D grain growth simulations as an example, we present a completely overhauled computational framework based on graph neural networks with not only excellent agreement to both the ground truth phase-field methods and theoretical predictions, but enhanced accuracy and efficiency compared to previous works based on convolutional neural networks. These improvements can be attributed to the graph representation, both improved predictive power and a more flexible data structure amenable to adaptive mesh refinement. As the simulated microstructures coarsen, our method can adaptively adopt remeshed grids and larger timesteps to achieve further speedup. The data-to-model pipeline with training procedures together with the source codes are provided.
Aluminum Nitride Memristors: The Fabrication and Analysis of a Next Generation Processor
(2024-04-21) Attarwala, Ali; Spanos, Pol D; Ghorbel, Fathi; Tang, Ming
This thesis details the experimental development of memristors with an Aluminum Nitride (AlN) insulative layer that can switch its resistance by adjusting its phase. Upon conducting an exhaustive literature review, the opportunity to study the ferroelectric properties of AlN in a resistive switching setting came about. The experimental study starts by detailing the fabrication of memristors utilizing atomic layer deposition (ALD) and electrode deposition. To study the characteristics of the device, relevant AlN memristor samples underwent a full electrical characterization. While there were some interesting results, the current-voltage (I-V) data did not match the expected behavior and results. To further investigate the data, transmission electron microscopy (TEM) analysis was conducted to look inside the device at the nanometer scale. The TEM data highlights the difficulties of memristor fabrication and processing. The experimental process provided insight into the behavior of the ferroelectric properties of AlN suggesting resistive switching applications. However, further exploration of the fabrication and processing of AlN in memristors is required, before any industrial applications are pursued.
Continuous plate subduction marked by the rise of alkali magmatism 2.1 billion years ago
(Springer Nature, 2019) Liu, He; Sun, Wei-dong; Zartman, Robert; Tang, Ming
Over the Earth’s evolutionary history, the style of plate subduction has evolved through time due to the secular cooling of the mantle. While continuous subduction is a typical feature of modern plate tectonics, a stagnant-lid tectonic regime with localized episodic subduction likely characterized the early Earth. The timing of the transition between these two subduction styles bears important insights into Earth’s cooling history. Here we apply a statistical analysis to a large geochemical dataset of mafic rocks spanning the last 3.5 Ga, which shows an increasing magnitude of alkali basaltic magmatism beginning at ca. 2.1 Ga. We propose that the rapid rise of continental alkali basalts correlates with an abruptly decreasing degree of mantle melting resulting from the enhanced cooling of the mantle at ca. 2.1 Ga. This might be a consequence of the initiation of continuous subduction, which recycled increasing volumes of cold oceanic crust into the mantle.
Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning
(Springer Nature, 2024) Li, Zeyuan; Flynn, Thomas; Liu, Tongchao; Liu, Sizhan; Lee, Wah-Keat; Tang, Ming; Ge, Mingyuan
Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNixMnyCo1-x-yO2 systems with high confidence.
Lithium systematics in global arc magmas and the importance of crustal thickening for lithium enrichment
(Springer Nature, 2020) Chen, Chen; Lee, Cin-Ty A.; Tang, Ming; Biddle, Kevin; Sun, Weidong
Much of the world’s Li deposits occurs as basinal brines in magmatic orogens, particularly in continental volcanic arcs. However, the exact origin of Li enrichment in arc magmatic systems is not clear. Here, we show that, globally, primitive arc magmas have Li contents and Li/Y ratios similar to mid-ocean ridge basalts, indicating that the subducting slab has limited contribution to Li enrichment in arc magmas. Instead, we find that Li enrichment is enhanced by lower degrees of sub-arc mantle melting and higher extents of intracrustal differentiation. These enrichment effects are favored in arcs with thick crust, which explains why magmatism and differentiation in continental arcs, like the Andes, reach greater Li contents than their island arc counterparts. Weathering of these enriched source rocks mobilizes and transports such Li into the hydrologic system, ultimately developing Li brines with the combination of arid climate and the presence of landlocked extensional basins in thickened orogenic settings.
Material engineering for Li-ion capacitors and Li-ion batteries
(2019-12-05) Kato, Keiko; Ajayan, Pulickel M; Tang, Ming
Electrochemical energy storage devices are fundamental driving force behind personal and industrial electronics. Li-ion batteries became the most prevalent rechargeable energy storage technology in market because of a high energy density. However, a power density (especially charging) of Li-ion batteries is not satisfactory for certain applications. In this regard, supercapacitors serve as a complementary role. To combine the advantages of Li-ion batteries and supercapacitors and bridge the technological gap, Li-ion capacitors (LICs) are invented. A typical Li-ion capacitor consists of a battery-type anode and supercapacitor-type cathode in Li-ion containing carbonate-based electrolytes. The major challenge of LICs arises from such disparity in charge-storage mechanism and kinetic. The present work addresses the issue by engineering electrode and electrolyte materials. 1) Two-dimensional material (vanadium disulfide anode and nitrogen-doped reduced graphene oxide cathode) are developed to combat the low power density of battery-type electrodes and the low energy density of supercapacitor-type electrodes. 2) We demonstrated that the energy and power densities achievable by LICs are largely influenced (and perhaps determined) by the anion adsorption at the positive electrodes, and by the ion transport within the electrolytes. Another challenge of the current Li-ion battery technology is an environmental and sustainability aspects because of a use of toxic and scarce transitional metals. Electroactive organic molecule-based cathodes which can reversibly store Li-ions are environmentally benign alternatives. Here, we assessed electrochemical performance of a plant-based organic molecule (lawsone) and showed that its oligomer structure stabilizes the molecules, which led to an improvement in a capacity retention over repeated cyclings. Next, we exploited the light-harvesting and Li-storing capabilities of the organic molecules to demonstrate light charging capability of the molecule. This work sheds light on the unique capability of organic cathode materials and paves the way for the future development of environmentally friendly and light rechargeable Li-ion batteries.
Mesoscale Modeling of Microstructure Evolution in Lithium Battery Electrode Material
(2021-04-28) Yang, Kaiqi; Tang, Ming
Thirty years after its commercialization, lithium-ion rechargeable battery (LIB) has become a key technology in reducing the society’s dependence on fossil fuels and shifting towards clean, renewable energy sources. Despite tremendous progress, Li- ion batteries still face significant barriers to their wide adoption in electrical vehicles and electric grid storage. Fundamental understanding of the physical phenomena in battery systems at all length scales, including the mesoscopic level, is essential to enable further technological advancement in cost reduction, energy density improvement and cycle life extension. Many battery electrode materials undergo first-order phase transformations upon battery cycling, which frequently control the lithium intercalation kinetics and significantly impact on the degradation process. Extensive research reveals that phase transformations in intercalation compounds exhibit distinct characteristics from other types of material systems, many of which are still under debate and remain to be fully understood. A clear elucidation of these unique features has important implications for discovering and designing better battery materials. In this thesis, computational modeling is applied to investigate the mesoscale phase transformation kinetics in lithium battery electrodes, using lithium iron phosphate olivine (LiFePO4) cathode as the model system. Phase-field models are developed and implemented to simulate the concurrent lithium transport, phase transition and stress evolution in LiFePO4 during (de)lithiation, which generates several significant findings including: 1) The coherency stress between the LiFePO4 and FePO4 phases induces the morphological instability in the phase growth front and results in non-uniform intercalation in single crystalline particles. 2) Phase transition in LiFePO4 secondary particles exhibits one-dimensional growth behavior, which can be attributed to the anisotropic stress generated by the LiFePO4 /FePO4 lattice misfit and the strong elastic interaction between primary particles, 3) Antisite defects have the surprising effect of accelerating the phase growth kinetics by increasing the surface area of active Li intercalation during battery charge/discharge. Due to high computational cost, simulating microstructure evolution in battery systems is still limited in spatiotemporal scales. To address this challenge, we develop a data-driven modeling approach by replacing PDE-based simulations with machine learning algorithms based on convolutional recurrent neural networks (ConvRNN). The ConvRNN model is demonstrated to accelerate predictions up to 1000 folds for several classical microstructure evolution examples. It offers a promising alternative for efficient battery simulation at the mesoscale level in the future.
Nb/Ta systematics in arc magma differentiation and the role of arclogites in continent formation
(Springer Nature, 2019) Tang, Ming; Lee, Cin-Ty A.; Chen, Kang; Erdman, Monica; Costin, Gelu; Jiang, Hehe
The surfaces of rocky planets are mostly covered by basaltic crust, but Earth is unique in that it also has extensive regions of felsic crust, manifested in the form of continents. Exactly how felsic crust forms when basaltic magmas are the dominant products of melting the mantles of rocky planets is unclear. A fundamental part of the debate is centered on the low Nb/Ta of Earth’s continental crust (11–13) compared to basalts (15–16). Here, we show that during arc magma differentiation, the extent of Nb/Ta fractionation varies with crustal thickness with the lowest Nb/Ta seen in continental arc magmas. Deep arc cumulates (arclogites) are found to have high Nb/Ta (average ~19) due to the presence of high Nb/Ta magmatic rutiles. We show that the crustal thickness control of Nb/Ta can be explained by rutile saturation being favored at higher pressures. Deep-seated magmatic differentiation, such as in continental arcs and other magmatic orogens, is thus necessary for making continents.
Nb/Ta systematics in arc magma differentiation and the role of arclogites in continent formation
(Springer Nature, 2019) Tang, Ming; Lee, Cin-Ty A.; Chen, Kang; Erdman, Monica; Costin, Gelu; Jiang, Hehe
The surfaces of rocky planets are mostly covered by basaltic crust, but Earth is unique in that it also has extensive regions of felsic crust, manifested in the form of continents. Exactly how felsic crust forms when basaltic magmas are the dominant products of melting the mantles of rocky planets is unclear. A fundamental part of the debate is centered on the low Nb/Ta of Earth’s continental crust (11–13) compared to basalts (15–16). Here, we show that during arc magma differentiation, the extent of Nb/Ta fractionation varies with crustal thickness with the lowest Nb/Ta seen in continental arc magmas. Deep arc cumulates (arclogites) are found to have high Nb/Ta (average ~19) due to the presence of high Nb/Ta magmatic rutiles. We show that the crustal thickness control of Nb/Ta can be explained by rutile saturation being favored at higher pressures. Deep-seated magmatic differentiation, such as in continental arcs and other magmatic orogens, is thus necessary for making continents.
Non-uniform Stress-free Strains in a Spherically Symmetrical Nano-sized Particle and Its Applications to Lithium-ion Batteries
(Springer Nature, 2018) Meng, Qingping; Wu, Lijun; Welch, David O.; Tang, Ming; Zhu, Yimei
The stress-free strain originated from local chemical composition and phase transformation can significantly alter the microstructures of materials; and then affect their properties. In this paper, we developed an analytical method to calculate stress-strain field due to the non-uniform stress-free strain in a spherically symmetrical particle. Applying the method to a lithium ion (Li-ion) battery electrode, the evolution of Li-ion concentration and strain field during the lithiation process is studied. Our studies reveal that the maximum strain in the electrode generally occurs on surface of sample, and is mainly dependent on the difference of Li-ion concentration of surface and of center in sample. Decreasing the difference of Li-ion concentration can efficiently decrease the maximum strain so that cracks of electrodes can been prevented. Our analytical results provide a useful guidance for practical applications of energy storage materials.
Rapid endogenic rock recycling in magmatic arcs
(Springer Nature, 2021) Li, Jun-Yong; Tang, Ming; Lee, Cin-Ty A.; Wang, Xiao-Lei; Gu, Zhi-Dong; Xia, Xiao-Ping; Wang, Di; Du, De-Hong; Li, Lin-Sen
In subduction zones, materials on Earth’s surface can be transported to the deep crust or mantle, but the exact mechanisms and the nature of the recycled materials are not fully understood. Here, we report a set of migmatites from western Yangtze Block, China. These migmatites have similar bulk compositions as forearc sediments. Zircon age distributions and Hf–O isotopes indicate that the precursors of the sediments were predominantly derived from juvenile arc crust itself. Using phase equilibria modeling, we show that the sediments experienced high temperature-to-pressure ratio metamorphism and were most likely transported to deep arc crust by intracrustal thrust faults. By dating the magmatic zircon cores and overgrowth rims, we find that the entire rock cycle, from arc magmatism, to weathering at the surface, then to burial and remelting in the deep crust, took place within ~10 Myr. Our findings highlight thrust faults as an efficient recycling channel in compressional arcs and endogenic recycling as an important mechanism driving internal redistribution and differentiation of arc crust.
Reaction Heterogeneities in Lithium Ion Batteries
(2021-03-10) Wang, Fan; Tang, Ming
Lithium ion batteries (LIBs) are an indispensable component of personal electronics, electric vehicles, and back-up power source for many critical infrastructures. A series of kinetic processes occur at different length scales within LIBs during their operation. Spatially non-uniform reaction resulting from these processes may lead to inferior performance and even degradation or failure of LIBs. This thesis aims to quantitatively understand the nature of such inhomogeneous phenomena during the operation of LIBs and identify effective ways to prevent their occurrence. At the electrode level, we introduce an analytical model to predict the rate performance of LIBs when reaction non-uniformity results from kinetic limitation in electrolyte transport. The model is built upon the assumption of two prototypical reaction behaviors, uniform vs moving zone reaction, which are idealized based on observations from pseudo two-dimensional (P2D) simulations. Predictions of the analytical model exhibit high accuracy over a wide range of battery design parameters with a computational speed-up of more than 105 times compared to P2D simulations. The model also offers valuable insights on the effects of electrode reaction behavior and cell format (half vs full cells) on the battery cell performance. The analytical model is subsequently applied to optimize battery cell configurations with different objectives, and further extended to consider concentration-dependent electrolyte diffusivity and electrodes with spatially varied properties. Next, we employ a simplified circuit model to elucidate the thermodynamic origin of the reaction heterogeneity within porous electrodes. It is found that the state-of-charge (SOC) dependence of the equilibrium potential of the electrode material strongly influences the degree of reaction non-uniformity across the porous electrode, which can be accurately characterized by a dimensionless parameter deduced from the circuit model. The analysis motivates several potential approaches to mitigating localized reaction in phase-changing electrodes. At the particle level, we employ synchrotron-based transmission X-ray microscopy to study the reaction heterogeneity in LiFePO4 secondary particles. Unlike the core-shell reaction geometry often assumed in literature, we observe ubiquitous stripe-like phase pattern on the secondary particle surface, which is independent of the (dis)charging rate and also persists over a wide range of SOC. The experimentally observations are well captured by phase-field simulations, based on which we suggest that the heterogeneous reaction pathway results from the misfit stress induced by the incompatible volume changes between neighbor primary particles of different crystallographic orientations upon lithium insertion / extraction.
Self-supervised learning and prediction of microstructure evolution with convolutional recurrent neural networks
(Elsevier, 2021) Yang, Kaiqi; Cao, Yifan; Zhang, Youtian; Fan, Shaoxun; Tang, Ming; Aberg, Daniel; Sadigh, Babak; Zhou, Fei
Microstructural evolution is a key aspect of understanding and exploiting the processing-structure-property relationship of materials. Modeling microstructure evolution usually relies on coarse-grained simulations with evolution principles described by partial differential equations (PDEs). Here we demonstrate that convolutional recurrent neural networks can learn the underlying physical rules and replace PDE-based simulations in the prediction of microstructure phenomena. Neural nets are trained by self-supervised learning with image sequences from simulations of several common processes, including plane-wave propagation, grain growth, spinodal decomposition, and dendritic crystal growth. The trained networks can accurately predict both short-term local dynamics and long-term statistical properties of microstructures assessed herein and are capable of extrapolating beyond the training datasets in spatiotemporal domains and configurational and parametric spaces. Such a data-driven approach offers significant advantages over PDE-based simulations in time-stepping efficiency and offers a useful alternative, especially when the material parameters or governing PDEs are not well determined.
Stress Effects on Phase Morphological and Compositional Non-uniformity in Intercalation Compounds
(2022-04-22) Zhang, Youtian; Tang, Ming
Intercalation compounds have important applications in rechargeable batteries and hydrogen storage systems. Solute insertion into or extraction from these compounds frequently induces phase transformations, and the resultant microstructure evolution plays an important role in the (de)intercalation kinetics, performance and reliability of the systems. In this thesis, theoretical analyses and mesoscale simulations are carried out to elucidate and predict how coherency stress, which usually arises due to the solute concentration dependence of lattice parameter, impacts the evolution of phase morphology and solute composition distribution in intercalation compounds. In the first topic, the effect of coherency stress on the stability of the intercalation front in both isotropic and anisotropic systems is investigated by linear stability analysis and numerical simulations. Theoretical analysis shows that the misfit strain between solute-rich and solute-poor phases could cause the flat interface between them to become unstable and develop non-planar morphology during interface- and diffusion-limited intercalation processes, which is analogous to the well-known Asaro-Tiller-Grinfeld instability in epitaxial thin film growth. Predictions of the analysis is corroborated by phase-field simulations, which further reveals the phase morphology evolution at the late stage of interface instability development. Because this phenomenon leads to non-uniform solute intercalation and stress concentration, it is detrimental to the rate performance and reliability of intercalation compounds used as electrode materials in lithium- or sodium-ion batteries. For systems with strongly anisotropic misfit strains, it is discovered that the interface could be destablized by two different modes of perturbation, i.e. surface vs bulk mode. While the surface-mode interface perturbations could be suppressed when interface moves far away from particle surface, unstable bulk-mode perturbations persist throughout the (de)intercalation process. Our predictions provide satisfactory explanation to experimentally observed phase boundary morphologies in various battery electrodes. Furthermore, an interface stability diagram is derived from the analysis, which provides guidance in choosing the proper particle sizes, elastic anisotropy and/or (dis)charge conditions to avoid the instability. The second topic concerns the effect of coherency stress on the metastability of solid solution in nanoscale intercalation compounds that are increasingly employed in batteries. Previous theoretical works predict that stress can significantly suppress phase separation and extend the solid solution regime in nanosized electrode particles. However, these works do not consider how the solid solution stability is impacted by the recently discovered surface-driven coherent spinodal decomposition. We comprehensively analyze the phase separation kinetics in nanosized systems by considering both the bulk and surface modes of coherent spinodal decomposition within the linear stability theory. It shows that the stress effect on stabilizing solid solution is considerably weakened by stress relaxation near free surface. The dominant composition modulation pattern emerging from the spinodal decomposition is predicted as a function of particle size, solute supersaturation and misfit strain, which could be compared against experiments. An analytical expression is derived for the minimum particle size below which phase separation is suppressed in the presence of coherency stress. It is found to be only slightly larger than the critical particle size in the absence of stress. As a result, coherency stress only modestly improve the metastability of solid solution in nanoscale particles as against common beliefs. Lastly, the coupling between coherency stress and microstructure evolution in technically important battery electrode systems is investigated. Using micromechanical-microstructure modeling, we examine the interplay between coherency stress, particle size and morphology and its role in the lithium insertion dynamics in electrochromic Titanium dioxide nanocrystal ensembles, intragranular fracture in single-crystal nickel-rich layered oxides (NMC) and intergranular cracking in polycrystalline NMC particles.
Subaerial crust emergence hindered by phase-driven lower crust densification on early Earth
(AAAS, 2024) Tang, Ming; Chen, Hao; Lee, Cin-Ty A.; Cao, Wenrong
Earth owes much of its dynamic surface to its bimodal hypsometry, manifested by high-riding continents and low-riding ocean basins. The thickness of the crust in the lithosphere exerts the dominant control on the long-wavelength elevations of continents. However, there is a limit to how high elevations can rise by crustal thickening. With continuous crustal thickening, the mafic lower crust eventually undergoes a densifying phase transition, arresting further elevation gain—an effect clearly observed in modern orogenic belts. On early Earth, lower crust densification should also limit how high a thickening crust can rise, regardless of the thickening mechanisms. We suggest that lower crust densification combined with a thicker oceanic crust in the Archean may have limited the whole-Earth topographic relief to 3 to 5 kilometers at most—half that of the present day. Unless the oceans were far less voluminous, limited relief would inevitably lead to a water world on early Earth.
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Synthesis of Halide 2D perovskite via kinetics and thermodynamics control
(2024-04-15) Hou, Jin; Mohite, Aditya D.; Tang, Ming
Two-dimensional halide perovskites have emerged as a “trending topic” low-dimensional semiconductors material in the past decade, for they exhibit a combination of properties – high structure tunability, flexible composition engineering, quantum wells, 2D materials, organic semiconductors, high stability, etc. Its unique structure and property have offered enormous research potential in fundamental physics, material science, chemistry, and photovoltaic device engineering. This thesis aims to explore and develop the synthesis of 2D perovskites, including improving the phase purity of 2D perovskites crystals, realizing the synthesis of 2D perovskite with high perovskite layer-thickness, and inventing novel 2D perovskites with various strategies. Firstly, this thesis addressed a major challenge in the 2D perovskite synthesis which is producing 2D perovskite crystals with desired perovskite-layer thicknesses (quantum well thickness, also known as n values) greater than two. A novel method termed kinetically controlled space confinement (KCSC) for the growth of phase pure 2D perovskites of desired n values for both RP and DJ is introduced. Through this method a transformation from lower n to higher n in 2D perovskites is also demonstrated. Those finding will enable reproducible synthesis of 2D perovskites, specifically for n>4, which is very significant as the higher n 2D perovskites have narrower band gap and higher electrical conductivity, and those parameters are the most crucial factors for application in electronic devices. In the second part, a novel 2D perovskite series with formamidinium (FA) as cage cation is demonstrated. This series of 2D perovskite has the smallest bandgap among all the reported 2D perovskite. Its structure is perfectly linear with no distortion, taking a space group of p4/mmm (tetragonal) which is the maximum symmetry that can be achieved theoretically in 2D perovskite. This novel 2D behaves like a 3D one from all the perspectives, including structure, lattice softness, charge transport. The combination of low band gap with high stability makes it an outstanding candidate for solar cells, both single junction and tandems. Finally, this thesis presents a unique “n=1.5” 2D perovskites, which exhibit an intrinsic multi-layer thickness structure, consisting of alternating n=1 and n=2 layers. This unique structure provides an exciting platform to study the excitons, energy funneling and has huge potential for lasering applications. A new horizon for perovskites research is opened up with a lot of exploration and development on the way.
The redox “filter” beneath magmatic orogens and the formation of continental crust
(AAAS, 2018) Tang, Ming; Erdman, Monica; Eldridge, Graham; Lee, Cin-Ty A.
The two most important magmatic differentiation series on Earth are the Fe-enriching tholeiitic series, which dominates the oceanic crust and island arcs, and the Fe-depleting calc-alkaline series, which dominates the continental crust and continental arcs. It is well known that calc-alkaline magmas are more oxidized when they erupt and are preferentially found in regions of thick crust, but why these quantities should be related remains unexplained. We use the redox-sensitive behavior of europium (Eu) in deep-seated, plagioclase-free arc cumulates to directly constrain the redox evolution of arc magmas at depth. Primitive arc cumulates have negative Eu anomalies, which, in the absence of plagioclase, can only be explained by Eu being partly reduced. We show that primitive arc magmas begin with low oxygen fugacities, similar to that of mid-ocean ridge basalts, but increase in oxygen fugacity by over two orders of magnitude during magmatic differentiation. This intracrustal oxidation is attended by Fe depletion coupled with fractionation of Fe-rich garnet. We conclude that garnet fractionation, owing to its preference for ferrous over ferric iron, results in simultaneous oxidation and Fe depletion of the magma. Favored at high pressure and water content, garnet fractionation explains the correlation between crustal thickness, oxygen fugacity, and the calc-alkaline character of arc magmas.

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