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SUMMARY:Preisach-percolation dynamics of multilevel resistive switching in
  phase-separated LPCMO
DTSTART;VALUE=DATE-TIME:20260416T153000Z
DTEND;VALUE=DATE-TIME:20260416T155000Z
DTSTAMP;VALUE=DATE-TIME:20260412T084707Z
UID:indico-contribution-284@fisindico.uniandes.edu.co
DESCRIPTION:Speakers: Juan Gabriel Ramirez (Universidad de los Andes)\nWe 
 investigate the complex interplay of competing phases in bulk La$_{5/8−x
 }$Pr$_x$Ca$_3/8$MnO$_3$ (LPCMO) to demonstrate the coexistence of volatile
  and non-volatile multilevel resistive switching (RS) within a single devi
 ce. In this system\, ferromagnetic metallic (FM-M) and chargeordered insul
 ating (COI) phases spatially coexist across a broad ∼160 K temperature w
 indow. While volatile RS is driven by a reversible\, electrically induced 
 metal-insulator transition\, the non-volatile RS is governed by the therma
 l history of the FM volume fraction. Specifically\, voltage pulses that he
 at the device into a critical 90–210 K window permanently alter the phas
 e fraction\, modulating the resistance by up to seven orders of magnitude 
 (∼300 Ω to ∼109 Ω). The metallic state is fully recoverable by cyc
 ling the temperature above the charge-ordering threshold (∼210 K). To qu
 antitatively capture this phase-fraction control\, we implement a Preisach
 –percolation framework. Calibrated directly from experimental R–T hyst
 eresis loops without free parameters\, the model extracts domain switching
  distributions and utilizes a percolation threshold of $p_c = 0.65$ to suc
 cessfully predict both macroscopic resistance at 2 K and magnetization at 
 5 K following specific thermal pathways. Ultimately\, we demonstrate the s
 tabilization of three distinct\, highly reproducible resistance states ove
 r 25 cycles with ratios exceeding $10^3$\, showcasing phase-fraction engin
 eering as a robust mechanism for multilevel memory in correlated oxides. \
 n\nKeywords: resistive switching\, phase separation\, Preisach model\, per
 colation theory\, LPCMO\, neuromorphic computing. \n\nAcknowledgements\nTh
 is work was conducted in collaboration with Diego Carranza-Celis (Universi
 dad de los Andes)\, Pavel Salev (University of Denver)\, Ali C. Basaran (G
 eneral Atomics)\, and Ivan K. Schuller (UC San Diego). J.G.R. acknowledges
  support from the Facultad de Ciencias and Vicerrectoría de investigacion
 es of Universidad de los Andes. This work was also supported by Project No
 . INV2021-128-2313 of the Faculty of Science at Universidad de los Andes\,
  Bogotá\, Colombia. The research at University of California\, San Diego 
 was supported by the U.S. Department of Energy’s Office of Basic Energy 
 Science\, under Grant No. DE-FG02-87ER45332.\n\nhttps://fisindico.uniandes
 .edu.co/event/23/contributions/284/
LOCATION:Universidad de los Andes ML-513
URL:https://fisindico.uniandes.edu.co/event/23/contributions/284/
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