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At least 145 records · Page 8

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient, and thermal conductivity, which are further complicated by the presence of defects. This review explores how artificial intelligence (AI) and machine learning (ML) are transforming thermoelectric materials design. Advanced ML approaches including deep neural networks, graph-based models, and transformer architectures, integrated with high-throughput simulations and growing databases, effectively capture structure-property relationships in a complex multiscale defect space and overcome the “curse of dimensionality”. This review discusses AI-enhanced defect engineering strategies such as composition optimization, entropy and dislocation engineering, and grain boundary design, along with emerging inverse design techniques for generating materials with targeted properties. Finally, it outlines future opportunities in novel physics mechanisms and sustainability, highlighting the critical role of AI in accelerating the discovery of thermoelectric materials.

36 MATERIALS SCIENCE↗

Analcime-wairakite formation during experimental cement-bentonite alteration at 200–300 °C

Engineered barrier system materials in nuclear waste repositories may undergo hydrothermal alteration in response to groundwater saturation and heating events over their long operational timescales. Hydrothermal interactions between engineered materials (e.g., bentonite buffers, cements, waste canister materials) and the host rock environment may drive alteration processes that affect the advantageous properties of some barrier materials. However, such alteration will also promote the formation of zeolites, hydrothermally formed minerals that may themselves act to isolate radionuclides. Understanding the environmental conditions that control radionuclide-sorbing properties of zeolites, such as Si/Al ratio or Na content, will be valuable for assessing the changing properties of engineered barrier materials in the case of an in situ heating event. Here, we present experimental work characterizing the formation of zeolites during hydrothermal interactions between generic clay and cement barrier materials, with a focus on the analcime-wairakite zeolite series, which has known radionuclide sorption and exchange properties. We present the results of hydrothermal experiments combining uncured ordinary Portland cement powder with steel and Wyoming bentonite in the presence of Opalinus clay and a synthesized Opalinus clay groundwater to simulate water-saturated conditions in an argillaceous rock repository. The experiments were conducted isothermally at 200 or 300 °C for 8 to 24 weeks. In contrast to analogous studies that did not include cement reactants, we observed the formation of analcime-group minerals in all experiments. The addition of cement resulted in lower Si/Al ratios in the zeolites compared to similar studies that did not include cement. The presence of cement as a reactant was interpreted to promote analcime formation at 200 °C. At 300 °C, we observed higher calcium and silica concentrations in the aqueous solutions as well as increased wairakite formation and decreased analcime formation compared to the experiments at 200 °C. These results show a fully realized analcime-wairakite solid solution that falls between Si/Al = 2 (ideal) and a trend of analcime minerals that have increasing Si/Al ratios with increasing Na/(Na+Ca). Our results show predictable relationships between the Si/Al ratio and the analcime-wairakite content under hydrothermal conditions and illustrate that repository material interactions may promote the formation of zeolites in the analcime-wairakite solid-solution series during heating events in the subsurface.

58 GEOSCIENCES↗

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗

Large Non‐Resonant Infrared Optical Second Harmonic Generation in Bulk Crystals of Van der Waals Semiconductor, SnP 2 Se 6

2D van der Waals (vdW) materials have emerged as a highly promising candidates for nonlinear optical (NLO) applications. This study presents the synthesis, comprehensive linear optical, and optical second harmonic generation (SHG) characterization of a novel 2D vdW semiconductor SnP2Se6 in its bulk single crystal form. It exhibits an indirect bandgap of ≈1.47 eV and an exceptional non-resonant SHG coefficient of d 33 ∼ −222 ± 30 pm V −1 at a fundamental wavelength of 2 µm, which is ≈7 times larger than that of the commercial AgGaSe 2 with a comparable bandgap. Density functional theory (DFT) calculations of the linear and nonlinear optical properties exhibit reasonable agreement with the experimental measurements, revealing the chemical origin of the enhanced properties. Moreover, SnP 2 Se 6 can exhibit both type-I and type-II phase matching over a wide spectral range, fulfilling one of the key criteria for an ideal NLO crystal. These exceptional properties position SnP 2 Se 6 as a highly promising candidate for NLO applications.

36 MATERIALS SCIENCE↗

Critical Review of Brazil Disk Techniques for Tensile Strength Characterization With an Emphasis on High Explosive Materials

Mechanical properties are a critical performance metric for many high explosive (HE) materials and tensile strength properties are particularly important. Direct tensile measurements using dogbone shaped samples are the gold standard but they have the disadvantage that they are fairly large and require samples machined from billets. Diametral compression, more commonly known as Brazil disk (BD) testing, is an indirect method for measuring tensile strength on smaller and more easily fabricated samples. A review of the BD literature is presented with an emphasis on tensile strength measurements in high explosive materials. BD literature is reviewed in three primary areas: (i) rocks and concrete, (ii) pharmaceutical materials, and (iii) high explosive materials. The literature for rocks/concrete is extensive and dates back over 80 years; despite this there is no consensus on the validity/accuracy of the BD technique or the optimal variant of the BD technique to employ. The pharmaceutical literature is the opposite, being limited in scope and quantity of studies. BD literature on high explosive materials falls in between, not as impressive as in the rocks/concrete community but more substantiative than in the pharmaceutical community. After the review of the literature practical parameters for HE BD testing and recommended future work is discussed.

Brazil disk↗

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE↗

Crack mitigation in additively manufactured AlCrFe 2 Ni 2 high-entropy alloys through engineering phase transformation pathway

The far-from-equilibrium solidification during additive manufacturing often creates large residual stresses that induce solid-state cracking. Here we present a strategy to suppress solid-state cracking in an additively manufactured AlCrFe 2 Ni 2 high-entropy alloy via engineering phase transformation pathway. We investigate the solidification microstructures formed during laser powder-bed fusion and directed energy deposition, encompassing a broad range of cooling rates. At high cooling rates (10 4 –10 6 K/s), we observe a single-phase BCC/B2 microstructure that is susceptible to solid-state cracking. At low cooling rates (10 2 –10 4 K/s), FCC phase precipitates out from the BCC/B2 matrix, resulting in enhanced ductility (~10 %) and resistance to solid-state cracking. Site-specific residual stress/strain analysis reveals that the ductile FCC phase can largely accommodate residual stresses, a feature which helps relieve residual strains within the BCC/B2 phase to prevent cracking. Our work underscores the value of exploiting the toolbox of phase transformation pathway engineering for material design during additive manufacturing.

36 MATERIALS SCIENCE↗

Advances in vat photopolymerization: early-career researchers shine light on a path forward

Vat photopolymerization (VP) has emerged as a promising additive manufacturing technique to allow rapid light-based fabrication of 3D objects from a liquid resin. Research in the field of vat photopolymerization spans across multiple disciplines from engineering and materials science to applied chemistry and physics. This perspective brings together early-career researchers from various disciplines in academia and national laboratories around the world to summarize the most recent advancements with special emphasis on the research highlighted as part of the Gordon Research Conference (GRC) 2024 meeting on Additive Manufacturing of Soft Materials. We provide an outlook on next-generation polymer processing methods from synthesis of novel materials to multimodality manufacturing and performance engineering. Further, this article combines the ideas of many of these junior researchers to present a vision for the future of the field by highlighting the challenges and opportunities that lie ahead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallization and assembly at interfaces: Celebrating the achievements of a vibrant research community

Crystallization is one of the cornerstones of modern materials science and engineering and plays a critical role in industries ranging from petroleum derivative manufacturing to microstructural engineering of structural materials and the defect-free growth of silicon single crystals for integrated chip technology. Also, in the realm of environmental and biological processes, the mineralization of diverse compounds has shaped the vast array of ecosystems we observe today. Conversely, understanding the crystallization and assembly of building blocks of various sizes at interfaces has broader impacts on materials synthesis, performance of energy storage devices, optimized processing conditions, and more.

36 MATERIALS SCIENCE↗

Evaluating Polymer Properties with Different Additives for Carbon Capture and Other Applications

Anthropogenic climate change is one of this generation’s most pressing concerns, with the potential to completely alter the delicate balance we’ve struck with nature. Already, global temperatures have risen 1.29°C, leading to disrupted weather systems, extinctions, increased risks of wildfires, and sea level rise, to name a few effects. Carbon dioxide emission from the combustion of fossil fuels and other industrial activity is a large driver of this phenomenon, as it absorbs heat before it can be radiated away from Earth, trapping it. Carbon dioxide has reached unprecedented levels in our atmosphere, showing a 50% increase from preindustrial averages to a whopping 430 ppm. Thus, reducing the amount of carbon dioxide via carbon capture technology is an important endeavor that serves to benefit everyone. The Microencapsulated CO 2 Sorbent (MECS) team at Lawrence Livermore National Laboratory (LLNL) has turned to microencapsulation to approach this endeavor. Microcapsules provide an attractive approach to carbon capture, combining large surface areas for more efficient mass transfer, regenerative abilities, reduced solvent loss, and improved handling. Additionally, while existing carbon capture technology relies on industrial plants, capsules could present a modular approach to carbon capture, reducing the need for extensive physical infrastructure. The MECS team’s design consists of a polymer membrane that contains a liquid carbon sequestering sorbent, aqueous sodium carbonate. The carbon capturing reaction occurs in three distinct steps, the first of which is the dissolution of carbon dioxide into the sorbent solution and its conversion into carbonic acid (H 2 CO 3 ), shown in equations 1 and 2 respectively. Because this step hinges upon the ability of carbon dioxide to reach the solution inside the capsule, it is necessary that the microcapsule shell is permeable to carbon dioxide gas. The MECS team produces these microcapsules using the in-air droplet encapsulation apparatus (IDEA) shown in figure 1, which can produce uniform micron-scale droplets at speeds much faster than traditional single-dispersal microfluidic-based techniques. The IDEA Is 100 times faster than these current techniques and can reach up to 1000 times their speed when incorporating a multi-nozzle design. Additionally, because droplets are produced in-air via vibration, IDEA can decrease post-processing times and material waste by 99% and can fabricate microgels that are 10 to 100 times more viscous than can be produced via traditional microfluidics. While this design represents a breakthrough in the throughput, efficiency, and tunability of microcapsule production, it imposes a major constraint on the microcapsule curing process. Because microcapsule shells are crosslinked with UV light while falling 30 cm through the air, this gives them a reaction window of approximately 0.2 seconds. Thus, the system and shell formulations must be optimized such that the shells can be fully crosslinked within this very narrow window, prompting investigations into curing behavior.

36 MATERIALS SCIENCE↗

SnSe 1-x S x Alloys: Anisotropic Van der Waals Semiconductors with Tunable Bandgaps

Alloying is one of the main tools of bandgap engineering, allowing the tuning of crystal structure, lattice parameters, and electronic structure of 3D and 2D/layered semiconductors. Among the latter, it can play a key role in tailoring the properties of tin monochalcogenides, a class of van der Waals semiconductors of interest for optoelectronics, thermoelectrics, ferroelectrics, and valleytronics. Here, the study investigates the synthesis and properties of large flakes of the anion substitution alloys SnSe 1-x S x . Alloy flakes across a wide range of compositions are obtained systematically by repeated growth from the same mixed (SnS, SnSe) powder precursor. Combined experiment and theory show full miscibility for all compositions, along with tunable lattice constants, bandgaps, and vibrational modes. Atomic resolution imaging demonstrates the accumulation of S and Se in alternating layers in the SnSe 1-x S x unit cell, attributed to growth kinetics. Polarized Raman spectroscopy confirms anisotropic vibrational modes; the calculated and measured band structure shows systematic changes in the band edge energies and anisotropic electronic structure due to the anisotropic in-plane lattice of the monochalcogenides. Cathodoluminescence, finally, indicates that a unique configuration of two non-degenerate, direct valleys along orthogonal k-space directions persists all the way from SnS to SnSe, making SnSe 1-x S x alloys interesting for valleytronics.

36 MATERIALS SCIENCE↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Self-consistent hardness measurements spanning eleven decades of strain rate on a single material surface

A comprehensive understanding of material strength across strain rates typically requires the combination of results from different methods, which often vary in loading conditions and/or sampled volumes, leading to discrepancies in material behavior. This study presents a microindentation approach to measure hardness covering eleven orders of magnitude in strain rate, from quasi-static to phonon drag-dominated rates, on a single material surface under uniform testing conditions. By engineering the geometry of impactors used in laser induced particle impact testing, we extend the breadth of accessible strain rates, including multiple distinct rates exceeding 10⁵ s⁻¹. This self-consistent approach provides clearer insights into high-rate deformation mechanisms. Our results demonstrate a gradual increase in hardness with strain rate from quasi-static up to ultra-high rates, where a sharp upturn in hardness is observed.

Engineering↗