arXiv subjects

Sam Lilak

Publications and source records attributed to Sam Lilak.

5 recordsLinked to original sources

arXiv2026

Towards Atom-by-Atom Fabrication: Mechanosynthetic donation and abstraction

Enabled by inverted-mode scanning tunneling microscopy (IM-STM) and the use of functionalized molecular tools, we demonstrate positionally-controlled mechanosynthetic addition (donation) of carbon and subtraction (abstraction) of silicon atoms on a model build site: atomically clean and crystalline Si(100). The resulting structures represent the first demonstrations of an emerging ability to manipulate radical chemistry with positional control of specific atoms and moieties in 3D. Furthermore, by comparing the behavior of molecular tools designed for atomic donation versus abstraction, we highlight general principles governing molecular tool design for selective and reliable mechanosynthetic functionality.

cond-mat.mtrl-sci↗

arXiv2025

Inverted-Mode Scanning Tunneling Microscopy for Atomically Precise Fabrication

Scanning Tunneling Microscopy (STM) enables fabrication of atomically precise structures with unique properties and growing technological potential. However, reproducible manipulation of covalently bonded atoms requires control over the atomic configuration of both sample and probe - a longstanding challenge in STM. Here, we introduce inverted-mode STM, an approach that enables mechanically controlled chemical reactions for atomically precise fabrication. Tailored molecules on a Si(100) surface image the probe apex, and the usual challenge of understanding the probe structure is effectively solved. The molecules can also react with the probe, with the two sides of the tunnel junction acting as reagents positioned with sub-angstrom precision. This allows abstraction or donation of atoms from or to the probe apex. We demonstrate this by using a novel alkynyl-terminated molecule to reproducibly abstract hydrogen atoms from the probe. The approach is expected to extend to other elements and moieties, opening a new avenue for scalable atomically precise fabrication.

cond-mat.mes-hall↗

arXiv2025

Molecular Tools for Non-Planar Surface Chemistry

Scanning probe microscopy (SPM) investigations of on-surface chemistry on passivated silicon have only shown in-plane chemical reactions, and studies on bare silicon are limited in facilitating additional reactions post-molecular-attachment. Here, we enable subsequent reactions on Si(100) through selectively adsorbing 3D, silicon-specific "molecular tools". Following an activation step, the molecules present an out-of-plane radical that can function both to donate or accept molecular fragments, thereby enabling applications across multiple scales, e.g., macroscale customizable silicon-carbon coatings or nanoscale tip-mediated mechanosynthesis. Creation of many such molecular tools is enabled by broad molecular design criteria that facilitate reproducibility, surface specificity, and experimental verifiability. These criteria are demonstrated using a model molecular tool tetrakis(iodomethyl)germane ($Ge(CH_{2}I)_{4}$; TIMe-Ge), with experimental validation by SPM and X-ray photoelectron spectroscopy (XPS), and theoretical support by density functional theory (DFT) investigations. With this framework, a broad and diverse range of new molecular engineering capabilities are enabled on silicon.

cond-mat.mtrl-sci↗

arXiv2025

A self-heating electrochemical cell with nine decades of programmable linear resistance

A programmable linear resistor with a compact footprint would have profound implications for microelectronics, enabling efficient in-sensor analog signal processing and in-memory computing. Non-volatile memory offers a potential solution but suffers from limitations due to the programming mechanisms that confine switching to nanoscale constrictions or field-sensitive semiconductor junctions, leading to non-linear current-voltage relationships and errors. Here, we introduce a tunable resistor that is programmed into non-volatile, high-precision resistance states spanning nine orders of magnitude, with linear current-voltage characteristics across the entire range -- significantly improving the performance and widening the application space of resistive memory. A key advance is an electrothermal gate that simultaneously spreads heat and electrochemical reactions during programming to enable large, bulk composition modulation. The volumetric modulation can host thousands of linear resistance states with 100x lower conductance errors than other memory. This enables direct processing of analog signals with high fidelity, and we demonstrate variable-gain amplification, division, and multiplication. Integration with CMOS is used to show resilience to electrical and thermal disturb in arrays and to demonstrate retention of analog levels at <1% average loss for more than 2 months across 100 devices. Simulations indicate matrix multiplication efficiency could approach >1,000 TOPS/W.

cs.ET↗

arXiv2021

Spoken Digit Classification by In-Materio Reservoir Computing with Neuromorphic Atomic Switch Networks

Atomic Switch Networks (ASN) comprising silver iodide (AgI) junctions, a material previously unexplored as functional memristive elements within highly-interconnected nanowire networks, were employed as a neuromorphic substrate for physical Reservoir Computing (RC). This new class of ASN-based devices has been physically characterized and utilized to classify spoken digit audio data, demonstrating the utility of substrate-based device architectures where intrinsic material properties can be exploited to perform computation in-materio. This work demonstrates high accuracy in the classification of temporally analyzed Free-Spoken Digit Data (FSDD). These results expand upon the class of viable memristive materials available for the production of functional nanowire networks and bolster the utility of ASN-based devices as unique hardware platforms for neuromorphic computing applications involving memory, adaptation and learning.

cs.ET↗