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DOE OSTI2024

Perovskite Grown in Gallium Nitride Nanowire Matrix for Stable and High‐Efficiency X‐Ray Detection

High-quality quasi-2D perovskites in a GaN nano-wire matrix are grown to build a 3D hetero-structure for high-performance X-ray sensing. In the 3D hetero-structure, GaN nano-wire matrix serves as an n-type charge collector that can rapidly extract carriers through the bulk film of the perovskite layer. Together with a p-type top electrode, a p–i–n diode with the 3D hetero-structure is built, that exhibits a rectified current–voltage characteristic. After analyzing the interface energy alignment, it is found that the fermi levels of the perovskite and GaN are aligned in the dark, and a quasi-fermi level splits upon illumination, introducing a built-in electrical field at the interface. As a result, strong photo-induced current is observed from the diode without an external field. Finally, the 3D diode for X-ray detection demonstration is used, revealing a sensitivity of 308.9 µC Gy air -1 cm -2 at an exceptionally low applied field of 0.125 V µm -1 . The X-ray-induced signal from the 3D diode is stable after 155 cycles of X-ray irradiation under a constant electric field. This demonstration informs a new 3D architecture for high-performance X-ray sensing, and it shows that GaN is a robust n-type interface for perovskite optoelectronic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Embedded Sensing in Additive Manufacturing Metal and Polymer Parts: A Comparative Study of Integration Techniques and Structural Health Monitoring Performance

This study presents a comparative evaluation of post-process sensor integration in additively manufactured (AM) metal and the in-situ process for polymer structures for structural health monitoring (SHM), with an emphasis on embedded sensors. Geometrically identical specimens were fabricated using copper via metal fused filament fabrication (FFF) and PLA via polymer FFF, with piezoelectric transducers (PZTs) inserted into internal cavities to assess the influence of material and placement on sensing fidelity. Mechanical testing under compressive and point loads generated signals that were transformed into time–frequency spectrograms using a Short-Time Fourier Transform (STFT) framework. An engineered RGB representation was developed, combining global amplitude scaling with an amplitude-envelope encoding to enhance contrast and highlight subtle wave features. These spectrograms served as inputs to convolutional neural networks (CNNs) for classification of load conditions and detection of damage-related features. Results showed reliable recognition in both copper and PLA specimens, with CNN classification accuracies exceeding 95%. Embedded PZTs were especially effective in PLA, where signal damping and environmental sensitivity often hinder surface-mounted sensors. This work demonstrates the advantages of embedded sensing in AM structures, particularly when paired with spectrogram-based feature engineering and CNN modeling, advancing real-time SHM for aerospace, energy, and defense applications.

additive manufacturing↗

DOE OSTI2026

Band Structure-Driven Design of a α-CsPbI 3 Ammonia Sensor for Industrial Applications

We investigate the defect-dependent electronic structure and gas-sensing potential of cubic α-CsPbI 3 using first-principles density functional theory and nonadiabatic molecular dynamics. Among the intrinsic defects, interstitials, vacancies, antisites, and switches studied, the I Pb and Pb I antisite defects exhibit transition energy levels near the middle of the band gap, thus functioning as deep traps. Short-term adsorption of ammonia selectively modifies the electronic structure, coordinating with Pb at Pb I sites and Cs at I Pb sites, significantly altering recombination pathways. Detailed analysis reveals that NH 3 reduces anharmonicity at I Pb defects, enabling enhanced recombination at elevated temperatures, while trap-assisted recombination dominates at room temperature. Other analytes, including CH 3 NH 2 and NO 2 , show negligible impact on the band gap or recombination dynamics, highlighting the potential selectivity of NH 3 interactions. Ab initio nonadiabatic molecular dynamics simulations at 300 K and 600 K further demonstrate temperature-dependent modulation of carrier lifetimes, with NH 3 accelerating recombination at ambient conditions and suppressing certain pathways at higher temperatures. These findings suggest that α-CsPbI 3 can serve as a selective and sensitive ammonia sensor over a broad temperature range and offer insights for ammonia detection under industrially relevant conditions.

ammonia sensor↗

DOE OSTI2025

Machine learning-driven design and self-sensing capabilities of automotive bumper lattices for adaptive impact response

We present a novel approach to design an automotive bumper energy absorber using carbon fiber reinforced polymer composites, optimized to meet conflicting performance requirements for two distinct impact scenarios. The design must satisfy both a low-speed (2.5 mph) pendulum intrusion test, simulating vehicle-to-vehicle collisions, and a high-speed (25 mph) leg flexion test, replicating pedestrian impacts. These tests demand opposing deformation characteristics: high flexibility (deformation < 85 mm) for the former and high stiffness (deformation < 22 mm) for the latter. To address these contradictory requirements, we developed a machine learning (ML) framework for inverse optimization of lattice designs and material selection. Unlike traditional iterative design processes, our ML model directly outputs optimal design parameters and material choices based on target performance inputs. The energy absorber was fabricated using advanced additive manufacturing techniques, including extrusion deposition and digital light processing. The integration of carbon fibers provides multifunctionality to the bumper structure, enabling self-sensing capabilities through changes in electrical resistivity under compression. This electrical response demonstrates high repeatability under multiple cycles at 2% compression and exhibits distinct signatures during crack formation under high deformation. This research offers adaptive performance through innovative design methodologies and smart material integration. The approach has potential applications in various fields requiring adaptive energy absorption and real-time structural health monitoring.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

DOE OSTI2025

An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment

Cataloging and classifying trees in the urban environment is a crucial step in urban and environmental planning; however, manual collection and maintenance of this data is expensive and time-consuming. Although algorithmic approaches that rely on remote sensing data have been developed for tree detection in forests, they generally struggle in the more varied urban environment. This work proposes a novel end-to-end deep learning method for the detection of trees in the urban environment from remote sensing data. Specifically, we develop and train a novel PointNet-based neural network architecture to predict tree locations directly from LiDAR data augmented with multi-spectral imagery. We compare this model to a number of high-performing baselines on a large and varied dataset in the Southern California region, and find that our method outperforms all baselines in terms of tree detection ability (75.5% F-score) and positional accuracy (2.28 meter root mean squared error), while being highly efficient. We then analyze and compare the sources of errors, and how these reveal the strengths and weaknesses of each approach. Our results highlight the importance of fusing spectral and structural information for remote sensing tasks in complex urban environments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Self-Sensing Composites via an Embedded 3D-Printed PVDF-MoS 2 Nanosensor for Structural Health Monitoring

Carbon fiber (CF)-reinforced epoxy composites are widely used in vehicle applications, where early damage detection is crucial for reliability and safety. To address this need, we developed a self-sensing epoxy/CF composite by embedding a PVDF-MoS 2 nanosensor via an embedded 3D printing method. By harnessing the intrinsic curing kinetics of epoxy, we tailored its rheological properties to optimize the embedded printing process, enabling precise and reliable support for sensor filaments without compromising the composite’s structural and functional integrity. Through comprehensive rheological and kinetic analysis, we established a quantitative relationship among curing temperature, conversion rate, and resulting yield modulus─defining a narrow processing window essential for successful sensor integration. Specifically, we identified that an epoxy yield modulus range of 180–294 Pa and a conversion rate below 10% are critical to support the PVDF-MoS 2 filament architecture. Here, this embedded 3D printing method produces complex and multimaterial PVDF-MoS 2 sensors within an epoxy matrix with minimal deformation and reduced postprocessing, which is scalable and adaptable for industrial applications. Under cyclic loading, the embedded sensors exhibited stable signals under constant loads and increased voltage signals in response to crack formation (17–35% higher) and catastrophic failure (1 order of magnitude higher), effectively capturing structural changes in real time. This study demonstrates the potential of PVDF-MoS 2 nanocomposite sensor materials for real-time structural health monitoring in epoxy–CF composite systems, enabling early detection of defects and stress anomalies, significantly reducing the risk of unexpected failures, and enhancing structural reliability.

PVDF-MoS2 sensor↗

DOE OSTI2025

Binding energies, charge radii, spins, and moments: Odd-odd Ag isotopes and discovery of a new isomer

We report on the masses and hyperfine structure of ground and isomeric states in 114,116,118,120 Ag isotopes, measured with the phase-imaging ion-cyclotron-resonance technique (PI-ICR) with the JYFLTRAP mass spectrometer and the collinear laser spectroscopy beamline at the Ion Guide Isotope Separator On-Line facility, Jyväskylä, Finland. We measured the masses and excitation energies, electromagnetic moments, and charge radii, and firmly established the nuclear spins of the long-lived states. A new isomer was discovered in 118 Ag and the half-lives of 118 Ag long-lived states were reevaluated. We unambiguously pinned down the level ordering of all long-lived states, placing the inversion of the 𝐼 = 0 − and 𝐼 = 4 + states at 𝐴 = 118 (𝑁 = 71). As a result, we compared the electromagnetic moments of each state to empirical single-particle moments to identify the dominant configuration where possible.

90 ≤ A ≤ 149↗

DOE OSTI2024

Enhanced electronic sensors

A micro-structured device that can improve sensitivity and signal-to-noise for electronic sensor materials is embedded in electrically resistive materials. The technology includes a three-dimensional embedded electrode structure and fabrication methods for making the device for electronic sensing in bulk resistive materials. Embedded electrode structures address issues in conventional sensors by allowing independent control of sensitive material thickness, area, electric field intensity, and field direction.

Doty, Fred Patrick↗

DOE OSTI2026

Computer vision-based rock bolt detection in orthomosaic imagery obtained in the Waste Isolation Pilot Plant underground facility

Assessing structural integrity of large underground tunnel facilities is often a time consuming and human-labor intensive task. Thus, research using various modes of sensing and automated detection of key structural components in mines is posed to aid in safety assessments and establishing overall structural health. We propose an approach utilizing off-the-shelf camera and lidar technology fixed to a custom sensing platform, image stitching techniques, fine-tuned object detection models, and specialized model-inference methods to automatically detect, count, and map roof bolts for assessment of structural safety in man-made underground tunnels. Results show a novel workflow for effective object counting in orthomosaic tunnel ceiling images generated from collections in GPS-denied mining environments. Additionally, we demonstrate effective fine-tuning of EfficientDet object detectors utilizing state-of-the-art image augmentation techniques known as the mosaic and mixup transformations. Our work is demonstrated on sensed data and imagery collected from the Department of Energy (DOE) Waste Isolation Pilot Plant (WIPP) where miles of tunnel ceiling must be assessed for structural integrity.

42 ENGINEERING↗

DOE OSTI2025

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

DOE OSTI2025

Real-Time Ammonia and Humidity Monitoring with Ultra-Fast Conductometric Sensors Based on Porphyrin and Phthalocyanine Complexes

Organic semiconductors like porphyrins and phthalocyanines are attracting a wide range of researchers due to their versatile electrical properties and sensing performances in conductometric sensors. In this study, we investigate two types of π-extended porphyrins, which share the same macrocyclic structure but differ in their central metal. These porphyrins are employed as sublayers in bilayer heterojunction devices, with the lutetium bisphthalocyanine complex, LuPc 2 , serving as the common top layer. Remarkably, the central metal in the porphyrin macrocycle significantly influences the solubility of the materials and, consequently, the surface topography of the resulting bilayer heterojunction devices. This structural variation translates into distinct electrical and sensing performances. The device incorporating nickel as metal centre (AM2) demonstrates superior sensitivity towards NH3, with a relative response (RR) of ca. -7% at 90 ppm, an ultra-fast response time of about 9 s, and an impressive limit of detection (LOD) of 250 ppb, whereas, the device that has zinc as metal centre in sublayer (AM3) exhibits RR value of ca. -0.9% at 90 ppm with t 90 of ca. 120 s and LOD of 2 ppm. Both devices are evaluated under randomly varying NH 3 concentration and RH value. The results shows that the AM2-based sensor allows following NH 3 in real-time, while the AM3-based sensor delivers an average concentration over time. On the other hand, the AM2-based sensor exhibits slow kinetics under RH exposure, while the AM3-based sensor precisely mirrors the pattern of random RH changes generated by the software, demonstrating its exceptional responsiveness and accuracy in tracking humidity fluctuations. In conclusion, these findings underscore the critical role of the metal centre in tuning the electrical and sensing properties of the heterojunction devices.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Polymorphism and Phase Control in Dion–Jacobson 2D 3-(Aminomethyl)piperidinium-Based Metal Iodide Perovskites

Two-dimensional halide perovskites exhibit rich structural diversity and tunable optoelectronic properties, making them promising materials for energy, sensing, and photonic applications. In this work, we report the structural mapping of four distinct polymorphs, γ (P2 1 /c), β (P4/mbm), α (P4/mmm), and δ (Cmcm) in the two-dimensional iodoplumbate, iodostannate, and iodogermanate perovskite so-called Dion-Jacobson series (3AMP)MI4 (M = Sn, Pb, Ge), where 3AMP is 3-(aminomethyl)piperidinium. The phases exhibit systematic evolution in octahedral distortion, lattice symmetry, and metal–halide geometry, enabling structural control over optoelectronic properties. Notably, the α-phase of (3AMP)SnI 4 represents a rare, ambient-stable, high-symmetry structure for Sn-based perovskites, without a phase transition down to 100 K. Variable-temperature single-crystal diffraction, powder x-ray diffraction (PXRD), and calorimetry reveal metal- and temperature-dependent polymorph interconversions, including the emergence of long range supercell reflections in Pb-rich compositions at low temperature. Optical spectroscopy and photoelectron yield spectroscopy confirm band gap tunability and band alignment trends, highlighting symmetry-dependent shifts and anomalous band gap bowing in mixed-metal systems, verified by electronic structure calculations. Calculations additionally indicate that the higher symmetry phases have reduced electron and hole effective masses compared to the lower symmetry phases.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Scaling Exponents of Turbulent Static Pressure Structure Function in the Inertial Subrange

The measured variations in the turbulent static pressure structure function D pp (r) with scale $r$ in the roughness sublayer above a subarctic forest are empirically shown to exhibit exponents that are smaller than $r$ 4/3 predicted for the inertial subrange (ISR). Three hypotheses are offered to explain these deviations. The first is based on conventional intermittency correction to the averaged turbulent kinetic energy dissipation rate, the second is based on shearing introducing deviations from locally isotropic state that must be sensed by both velocity and pressure structure functions, and the third is based on large and inertial scale pressure interactions that persist at values of $r$ within the resolvable ISR. The third hypothesis is shown to yield superior results, which allows a new formulation for D pp (r) to be derived that accommodates such finite interactions.

structure function↗

DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

DOE OSTI2025

Charge radii and electromagnetic moments of 214−218 Bi : Exploring the “southern” border of the 𝑍 > 82 octupole-deformation region

The changes in the mean-squared charge radii relative to 209 Bi 126 (𝛿⁢⟨𝑟 2 ⟩ 𝑁,126 ) and the magnetic dipole and electric quadrupole moments in 214−218 Bi have been measured using the in-source resonance-ionization spectroscopy technique at ISOLDE (CERN). Magnetic moments of odd-odd bismuth nuclei have been analyzed by the additivity relation. Previous tentative spin-parity and configuration assignments based on the 𝛽-decay feeding patterns have been supported. A normal odd-even staggering in charge radii of bismuth isotopes with 𝑁>126 has been observed. The new data for the 𝛿⁡⟨𝑟 2 ⟩ of bismuth isotopes allow a study of the isotonic dependencies in the charge radii, revealing jumps in 𝛿⁢⟨𝑟 2 ⟩ 132,126 and 𝛿⁢⟨𝑟 2 ⟩ 134,126 at 𝑍 = 84. This pattern could be explained by a sudden onset of octupole deformation at 𝑁 = 132 and 134 when going from polonium (𝑍 = 84) to astatine (𝑍 = 85).

fundamental symmetries↗

DOE OSTI2026

Processing-Dependent Structure and Poroelasticity of Nafion in Liquid Water

Ionomers act as the solid polymer electrolyte membrane in many modern electrochemical devices, yet the role of their nanostructure in modulating the poroelastic response remains poorly understood, especially in liquid water, where few techniques can measure simultaneous transport-mechanical properties. Poroelastic Relaxation Indentation (PRI) is uniquely suited for measuring time-dependent transport-mechanical properties of porous solids, specifically hydraulic diffusivity, elastic modulus, Poisson’s ratio, and intrinsic permeability, for porous solids. While ionomers such as Nafion are not porous in the typical sense, Nafion has a nanophase-segregated structure that, when fully swollen in liquid water, behaves as a poroelastic solid with a coupled mechanical-transport response. Using a poroelastic framework, we investigate how casting and pretreatment of Nafion membranes alter their poroelastic response in liquid environments. We characterize both extruded and dispersion-cast Nafion membranes pretreated in water at 25 or 100 °C and relate the mechanical-transport properties to the ionomer structure via hydrophilic and intercrystalline domain spacing measured using Small-Angle X-ray Scattering (SAXS). At 25 °C, dispersion-cast membranes exhibit distinctly lower hydraulic diffusivity and intrinsic permeability than extruded membranes but with comparable mechanical properties. Pretreatment at 100 °C increases hydrophilic domain spacing, improving transport but at the expense of mechanical stiffness. Dispersion-cast membranes respond more strongly to pretreatment than extruded membranes. Using the Carman-Kozeny pore network model and the hydrophilic domain-spacing, we estimate the pore radius and tortuosity to show how pretreatment reduces structure-related tortuosity differences between dispersion-cast and extruded membranes. Here, in this work, we show that nanophase-segregated materials such as Nafion can be rigorously characterized using poroelasticity, resulting in physically meaningful transport-mechanical properties. Coupling PRI with SAXS provides insights into the nanostructural features that govern the coupled mechanical-transport response. By establishing PRI for a nanophase-segregated material, this approach opens avenues for this technique’s application in other hydrated polymeric materials not typically considered to be poroelastic.

Shen, Margaret [University of California, Berkeley↗

DOE OSTI2025

Fluorogenic Biosensing with Tunable Polydiacetylene Vesicles

Polydiacetylenes (PDAs) are conjugated polymers that are well known for their colorimetric transition from blue to red with the application of energetic stimulus. Sensing platforms based on polymerized diacetylene surfactant vesicles and other structures have been widely demonstrated for various colorimetric biosensing applications. Although less studied and utilized, the transition also results in a change from a non-fluorescent to a highly fluorescent state, making polydiacetylenes useful for both colorimetric and fluorogenic sensing applications. Here, we focus on the characterization and optimization of polydiacetylene vesicles to tune their sensitivity for fluorogenic sensing applications. Particularly, we look at how the structure of the diacetylene (DA) hydrocarbon tail and headgroup affect the self-assembled vesicle size and stability, polymerization kinetics, and the fluorogenic, blue to red phase transition. Longer DA acyl tails generally resulted in smaller and more stable vesicles. The polymerization kinetics and the blue to red transition were a function of both the DA acyl tail length and structure of the headgroup. Decreasing the acyl tail length generally led to vesicles that were more sensitive to energetic stimuli. Headgroup modifications had different effects depending on the structure of the headgroup. Ethanolamine headgroups resulted in vesicles with potentially increased stimuli responsivity. The lower energy stimulus to induce the chromatic transition was attributed to an increase in headgroup hydrogen bonding and polymer backbone strain. Boronic-acid headgroup functionalization led to vesicles that were generally unstable, only weakly polymerized, and unable to fully transform to the red phase due to strong polar, aromatic headgroup interactions. This work presents the design of PDA vesicles in the context of biosensing platforms and includes a discussion of the past, present, and future of PDA biosensing.

Chemistry↗

DOE OSTI2025

Porogen‐Integrated Rapid Oxidation Enables Structured Mesoporous Metal Oxide Films

Structured metal oxide films have promise in optoelectronics, sensing, energy storage, and catalysis but their uptake is predominately limited due to their long and high‐temperature syntheses. Here, in this study, a self‐assembling polymer is used which can act as a chelating fuel source in a solution combustion reaction to generate highly structured mesoporous aluminum oxide films at <250 °C in a matter of minutes through a process termed porogen‐integrated rapid oxidation (PiRO). The resulting films with thicknesses up to 500 nm show an open‐cell, face‐centered cubic structure of spheroidal pores. Further, an additional ligand can be included to control the self‐assembly step to yield both through‐film ordering or tunable disordering for increased pore volume as confirmed by both grazing incidence small angle X‐ray scattering and ellipsometry. Finally, roll‐to‐roll manufacturing with PiRO is demonstrated on flexible polymeric substrates. The method offers a tunable, scalable, low‐temperature, and lower‐cost method to generate large‐area structured mesoporous metal oxide films.

36 MATERIALS SCIENCE↗