arXiv subjects

Robert G. Palgrave

Publications and source records attributed to Robert G. Palgrave.

5 recordsLinked to original sources

arXiv2026

Lifetime effects and satellites in the photoelectron spectrum of platinum metal

This work presents a comprehensive investigation of the electronic structure and many-body photoemission effects in metallic platinum using reflection high-energy electron energy-loss spec- troscopy (RHEELS), soft X-ray photoelectron spectroscopy (SXPS), and hard X-ray photoelectron spectroscopy (HAXPES), supported by ab initio calculations. Shallow and deep core state spectra enable the systematic characterisation of intrinsic line-shape asymmetries and satellite structures. Correlation of photoelectron satellites with RHEELS loss features allows the assignment of inter- band transitions, surface and bulk plasmons, plasmonic overtones, and semi-core ionisation losses across the Pt spectrum. Several previously unresolved satellite features and spin-orbit splittings are identified and discussed. Comparison of experimental valence band spectra with orbital-projected densities of states calculated using ab initio density functional theory (DFT) and G0W0 approaches, with and without spin-orbit coupling, demonstrates the critical role of relativistic effects in reproducing the Pt valence electronic structure. Together, these results establish a unified, internally consistent spectroscopic reference for metallic platinum, providing a robust framework for interpreting photoelectron spectra of Pt-containing catalysts, electronic materials, and related 5d transition metal systems.

cond-mat.mtrl-sci↗

arXiv2026

A Shift-Invariant Deep Learning Framework for Automated Analysis of XPS Spectra

X-ray Photoelectron Spectroscopy (XPS) is a crucial technique for material surface analysis, yet interpreting its spectra is often challenging for both human analysts and automated methods due to the prevalence of variable spectral shifts and overlapping peaks. This project introduces a machine learning solution using a Spatial Transformer Network (STN), a type of neural network that implicitly learns to align spectra. An STN model was designed to classify the chemical environments present in an input spectrum, using functional groups as a proxy. The model was trained and tested on a large synthetic dataset of 100,000 spectra, created by linearly combining real experimental data from a library of 104 polymers. \cite{RN22} To simulate experimental variability, random uniform shifts and broadening were applied to the data. The STN was found to effectively correct for random electrostatic shifts (up to 3.0 eV) and achieved relatively high accuracy ($\sim$ 82\%) in identifying functional groups, despite utilizing a much simpler architecture than previous work. These findings demonstrate that neural networks can effectively learn the underlying relationships between spectral features and chemical composition when they are able to intrinsically account for variable shifts. This work advances the development of more reliable automated XPS analysis, offering potential as an assistive tool for researchers and as a core component in future autonomous systems like self-driving laboratories.

cond-mat.mtrl-sci↗

arXiv2026

Boosting high-current alkaline water electrolysis and carbon dioxide reduction with novel CuNiFe-based anodes

The transition to a green hydrogen economy demands robust, scalable, and sustainable anodes for alkaline water electrolysis operating at industrial current densities (>1 A/cm2). However, achieving high activity and long-term stability under such conditions remains a formidable challenge with conventional catalysts. Here, we report a novel trimetallic CuNiFe anode fabricated through a rapid, single-step electrodeposition process at room temperature without organic additives. The catalyst exhibits an exceptionally low overpotential of <270 mV at 100 mA cm(-2) and operates stably for over 500 hours at 1 A cm(-2) in 30 wt% KOH. In a practical anion exchange membrane water electrolyzer (AEM-WE), the CuNiFe anode enables a current density of 2.5 A cm(-2) at only 2.5 V, with a voltage efficiency of 66.8%. Beyond water splitting, this anode also significantly enhances CO2 electrolysis, tripling the CO2 reduction current density and steering selectivity toward valuable multi-carbon products when paired with commercial copper cathodes. A cradle-to-gate life cycle assessment confirms that the CuNiFe anode reduces the carbon footprint by an order of magnitude and decreases environmental impacts by 40-60% across multiple categories compared to benchmark IrRuO2. Our work establishes a scalable, high-performance, and environmentally benign anode technology, paving the way for cost-effective electrochemical production of green hydrogen and carbon-neutral chemicals.

cond-mat.mtrl-sci↗

arXiv2022

Evaluation of the Thermal Stability of TiW/Cu Heterojunctions Using a Combined SXPS and HAXPES Approach

Power semiconductor device architectures require the inclusion of a diffusion barrier to suppress, or at best prevent the interdiffusion between the copper metallisation interconnects and the surrounding silicon substructure. The binary pseudo-alloy of titanium-tungsten (TiW), with $>$70~at.\% W, is a well established copper diffusion barrier but is prone to degradation via the out-diffusion of titanium when exposed to high temperatures ($\geq$400$^\circ$C). Here, the thermal stability of physical vapour deposited (PVD) TiW/Cu bilayer thin films in Si/SiO\textsubscript{2}(50~nm)/TiW(300~nm)/Cu(25~nm) stacks were characterised in response to annealing at 400$^\circ$C for 0.5~h and 5~h, using a combination of soft and hard X-ray photoelectron spectroscopy (SXPS and HAXPES) and transmission electron microscopy (TEM). Results show that annealing promoted the segregation of titanium out of the TiW and interdiffusion into the copper metallisation. Titanium was shown be driven toward the free copper surface, accumulating there and forming a titanium oxide overlayer upon exposure to air. Annealing for longer timescales promoted a greater out-diffusion of titanium and a thicker oxide layer to grow on the copper surface. However, interface measurements suggest that the diffusion is not significant enough to compromise the barrier integrity and the TiW/Cu interface remains stable even after 5~h of annealing.

cond-mat.mtrl-sci↗

arXiv2020

Bandgap Lowering in Mixed Alloys of Cs2Ag(SbxBi1-x)Br6 Double Perovskite Thin Films

Halide double perovskites have gained significant attention, owing to their composition of low-toxicity elements, stability in air and long charge-carrier lifetimes. However, most double perovskites, including Cs2AgBiBr6, have wide bandgaps, which limit photo conversion efficiencies. The bandgap can be reduced through hallowing with Sb3+, but Sb-rich alloys are difficult to synthesise due to the high formation energy of Cs2AgSbBr6, which itself has a wide bandgap. We develop a solution-based route to synthesis phase-pure Cs2Ag(SbxBi1-x)Br6 thin films, with the mixing parameter x continuous varying over the entire composition range. We reveal that the mixed alloys (x between 0.5 and 0.9) demonstrate smaller bandgaps (as low as 2.08 eV) than the pure Sb- (2.18 eV) and Bi-based (2.25 eV) compounds, with strong deviation from Vegard's law. Through in-depth computations, we propose that bandgap lowering arises from the Type II band alignment between Cs2AgBiBr6 and Cs2AgSbBr6. The energy mismatch between the Bi and Sb s and p atomic orbitals, coupled with their non-linear mixing, results in the alloys adopting a smaller bandgap than the pure compounds. Our work demonstrates an approach to achieve bandgap reduction and highlights that bandgap bowing may be found in other double perovskite alloys by pairing together materials forming a Type II band alignment.

cond-mat.mtrl-sci↗